In this episode of Founded and Funded Madrona Investors Aseem Datar and Sabrina Wu sit down with robotics expert and University of Washington Professor Sidd Srinivasa to talk about the technology and sociological trends that are leading to innovation in the robotics space, where Sidd sees opportunities for founders, and why now is the time to pay attention to what’s happening in the space. Sidd also shares why he is what he calls an “accidental roboticist” and some of the hard-learned lessons from throughout his extensive career.

This transcript was automatically generated and edited for clarity.

Coral: Welcome to Found it and Funded this is Coral Garnick Ducken, Digital Editor here at Madrona Venture Group, and this week we are diving into a topic that I think we can agree everyone loves to talk about — robotics. George Devol created the first digitally operated and programmable robot back in 1954. And since then, we have been awed by the likes of C-3PO from “Star Wars,” Tipsy, the cocktail serving robot in Las Vegas, and Scout — Amazon’s delivery robots in Snohomish County here in Washington. Robots are transforming productivity, efficiency, cost, output, and product quality for companies, and many trends are coming together to push the move to automate from the pandemic, of course, which has pushed for a more touchless remote-first way of operation to an enduring labor shortage, to technological innovation in computing, AI, and machine learning to technology, infrastructure and data quality advancements that means the use of computer vision in real time is now possible. All of these trends come together to create almost endless opportunity for founders in the robotics space.

So, this week, investors Aseem Datar and Sabrina Wu are talking with robotics expert Sidd Srinivasa about all of this and so much more. Not only do we learn how Sidd is actually what he calls an accidental roboticist, but he outlines the areas of robotics that he sees are ripe for innovation and some of the hard-learned lessons from throughout his extensive career. With that, I’ll hand it over to Aseem and Sabrina to dive in.

Aseem: Hello everyone. My name is Aseem Datar and I’m happy to be here today with one of my fellow investors, Sabrina Wu and our guest of honor, Professor Siddhartha Srinivasa to talk about our favorite topic — robotics. So recently there’ve been a whole bunch of technological advancements in the field of robotics. That means that the world is prime for accelerated innovation and adoption, especially within sectors like industrial, manufacturing, logistics, and many, many more. At Madrona, we’re excited to see where entrepreneurs take it and the kind of companies that they buried using this technological building block per se. We wanted to bring in one of the foremost experts in robotics to talk about some of these recent trends and why now is the time to pay attention to what’s happening in the space.

Sidd, thank you so much for joining us and welcome to this conversation.

Sidd: Thank you so much for having me, Aseem and Sabrina. It’s a pleasure to be here and it’s a pleasure to chat about robots. One of my most favorite things to talk about.

Sabrina: Yes, Sidd thanks so much for being here. We’re really excited that you were able to join us today. You know, looking at your background, you were previously at Carnegie Mellon University for 18 years, and many of those years you were running the robotics institute. Thankfully we were able to steal you away from them and have you join the University of Washington, where you’re now an endowed professor focusing on human robotics interactions. Uh, You, of course, we’re also one of the First Wave Founders of Berkshire Grey. Now publicly traded on the New York stock exchange after having revolutionized the use case of robotics and AI for fulfillment at scale. So, you know, why don’t we start though with how you really got interested in robotics in the first place. Was there a pivotal moment for you when you were growing up that got you interested in the field or, you know, really what was it?

Sidd: That’s a tough one. I wish I could say that there was some origin story one day in which I had this revelation. But I’m actually a very accidental roboticist. It was in 1999. I was ready to go do a Ph.D. in mathematics at CalTech or in fluid mechanics at Cornell. The then director of the Robotics Institute Raj Reddy, visited IIT Madras, where I was doing my undergrad, and he happened to come home and was talking to us — my dad was a professor there as well. Then he asked me what are you going to do with your life? And I said, “Oh yeah, I’m going to do one of these things.” He said, “Nope, you should do robotics and apply to this robotics Institute place”— that, you know, back in 1999 was fledgling. I said, “Why not?” I still remember after I got my acceptance, my dad sat me down and said, “Son, you know what the future is? It’s turbines. It’s not robotics. Robotics is just a fad.” I still talk to him about that, about how turbines are doing compared to robotics. I’m sure they’re doing really well. But certainly, I’m glad that I pursued robotics. Then ever since, it’s been such a pleasure waking up every morning, working on robots. I just continue to be flabbergasted that people pay me money to do something that I would in a heartbeat do for free.

Aseem: That’s awesome. I thought that there was going to be some, “I was watching “Small Wonder” kind of story'” but maybe now, and who knows maybe your someday going to build robots that operate turbines, and you’ll bring the best of both worlds together. I think we have the most fun learning about backgrounds — these stories that don’t surface on LinkedIn. So, thank you for sharing that. As we at Madrona are thinking about robots, the one obvious question we sort of always come across in our minds as we think about the spaces and build a prepared mind kind of framework is why now? What’s changed in the world — robots have always existed in some way, shape, or form for decades. Following on that question, what are some of the driving factors that you believe are leading toward the acceleration, the investment in the field and ultimately toward adoption?

Sidd: It’s been a slow boil of robotics. I must say. It’s not that there’s been some step-function improvement. One of the things that has actually been hugely beneficial is Moore’s law. Computers are getting faster and faster day by day. Essentially the same algorithms that we used to run 20 years ago when I started my Ph.D., now take seconds to run instead of tens of minutes. I think that’s a huge win because one of the interesting things about robotics is that your clock is set by nature. It’s set by gravity, right? If you have a coffee mug that you’re trying to pick up and it starts dropping, then you can slow down time so that your computation reaches up to it. You just have to make it not fall. You have to grab it. I think the ability of our computing to finally catch up with nature and potentially exceed nature has been a huge tailwind for us. I think additionally, there are a few other factors. One is hardware, particularly perception hardware, which has gotten much better and much cheaper.

Some of that has been driven by the self-driving car industry. You know, back when I started my Ph.D., you had to pay tens of thousands of dollars to get a FireWire camera and then buy a giant board that then you would attach to your computer and have to write like custom software to even be able to grab pixels out of a camera.

That’s no longer true, things are much cheaper now. And that’s super useful. It’s super useful, not just to bring down the bond cost of your product. But it’s also super useful to prototype things. It’s much faster and easier to prototype things when parts don’t cost tens of thousands of dollars. That means that now we can very speedily go through several iterations of a robot or a robotic system, without necessarily having to think too much about like, oh, what am I purchasing right now, so you don’t have to prematurely optimize just yet.

Aseem: Yeah, that’s so interesting and so relevant. I remember the time when I was writing code on embedded systems, and you would think about memory management, right? Like you would think about how much memory is my algorithm using. And now when you graduate from college, you’re just commissioning another VM. You’re just buying more compute at cents on the dollar, right? I think that’s just fascinating in terms of where the world has gone. Sidd, what about networks? What about latency? Is there something to unpack there in terms of 1) time to making a decision getting faster and 2) what about advances in hardware itself — in terms of precision arms, in terms of actuators and so on? Is there something there that’s also a, I would say light tailwind that’s pushing this forward?

Sidd: I think one of the things that we’re seeing recently is that there has been a greater availability of compliant manipulators, you know, things that can work with and around people. We call them human safe, but essentially, they have the ability to feel forces and respond to them just like our arms do. And one of the advantages of that is that it transfers a lot of the complexity from the metal to the silicon. These robots that are not industrial manipulators, but combined manipulators are much more complicated to program and manipulate, but they are intrinsically safe and intrinsically more capable because they are able to feel forces and modulator their forces.

And I think our ability to wrangle this new piece of technology better is going to be a big unlock for the future. You’re already seeing how, if you look at even automotive, a majority of their manipulation or their assembly is done by these giant industrial manipulators that just pick and place. But a lot of their relevant and important manipulation, particularly of flexible things like brake lining or seat cushions need forces and torques and very careful manipulation. And that even now is done by people. That is particularly challenging. I think a future that I can see is the ability for robots to be able to perform those careful force-guided tasks that we humans do so effortlessly.

Aseem: I think that’s a great characterization of what things are coming together. You hinted a little bit at the industrial sectors and so I want to go down that path of how do you think about the market? What are areas that you see are ripe for robotics to play a huge role in? How do you think about industry focus? What are industries where robots are an obvious solution? And tell us a little bit about your thinking around the application of robots to those use cases.

Sidd: One thing I would say is that I have a bias to be a very full-stack roboticist. I like nails and I like to hammer them with whatever hammer is available. I think for me, there are a few criteria that are really important when trying to decide what the right nails are. One is how relevant is it? There are a lot of places where we may think robotics is relevant, but the technology that’s needed to do it is not there at all. Part of the reason for that is that we tend to anthropomorphize. We think, oh, this is easy for me so surely this must be easy for a robot and that’s sometimes true, but it’s more often not true. So, I think being able to find the intersection of something that robots are capable of doing and something that is of value to people is really interesting.

From a sort of vertical point of view, I think there are a few places where robotics has a lot of potential. And I think a lot of that is related to how complexity can be addressed via either changing the process path or changing how the work is done. One of the places that I am particularly excited about is being able to use robotics in farming or agriculture. I think that there’s tremendous potential in being able to merge the way food is produced, the science behind how food is produced, and the way food is harvested, and the way it’s packaged, and the way it’s sold. I think sometimes we assume that, and this is funny because we assume that strawberries have to grow in a particular way. But that’s not even true, right? Like we humans have manipulated the way strawberries grow and appear based on a lot of criteria that we care about. But you can imagine a world where we are optimizing those criteria, not just for our consumption, but also for the ability for robots to be able to pick them. The ability for robots to be able to identify them. The ability for robots to be able to package them. I think when you think about it holistically as my goal is to be able to produce really delicious food and to be able to automate its harvesting and delivery to a person, then you can really think of ways in which you can automate the entire process and think about how you can manipulate the entire process. So that’s certainly something that I’m interested in.

I think another piece that to me is really interesting that I continue to be fascinated by is last mile. You look around outside and outside any doorstep, there are packages and it’s interesting and challenging to understand how those packages can be delivered faster, better to you. Right now, it’s both labor-intensive and energetically inefficient. I don’t just mean packages, right? Even if you think about food delivery, I think of it as a full stack of how would we imagine the preparation and the combination of the food such that it continues to be delicious.

But also, something that can be automated and delivered on time to us. Some foods are actually very, very hard to deliver as we all know. Getting fries delivered at home or getting a nice, like Indian samosa delivered by let’s still crispy and not soggy is super hard. But I think part of that is because of the way those food items are created — because they were never created to be packaged in a box and delivered to us. They were created to be eaten hot off of the tava or the plate into our mouth. So, I think, thinking through how that entire process might work, I think it would be interesting and valuable.

Aseem: That’s so cool because it’s complimentary to our view we have yet at Madrona around, there’s a strong wave around, you know, COVID start us that, a lot of systems, processes now are moving towards more autonomous touchless, contactless as well as, high-quality outcomes, right? Because the more systematic approach you take, the more consistent quality comes out of it. An area that we’ve not talked about here but it’s interesting to us is also around the smart factory, the autonomous vehicle assembly. I think all these things coupled with the problem of like, you know, an aging workforce slash shortage of labor, we believe are just areas that are ripe for disruption, or I would say opportunity from a robot standpoint.

Sidd: Yeah, I completely agree with that. I also think that part of this might be to rethink. How processes are engineered. As an example, if you wanted a robot that would do your laundry, this is everybody’s favorite robot. Building a robot that like is in your home, that’s loading your washer, pulling it out, putting it into the dryer, taking it out, folding your clothes might be incredibly challenging.

But you can imagine a world where some entity takes all of your dirty laundry, takes it to some centralized location where there’s a larger physical space, which does all the cleaning for you and delivers it back to you as quickly as possible. By changing the way things are processed and turning it from many small things to one aggregated larger thing. I think you can get potentially a lot of wins. That of course demands that we, as humans, change the way we want to live to some extent. But there’s a lot of evidence to that. Right? In that, like, we’re willing to change the way we work, and we live if it is longer term more convenient for us. We haven’t talked about consumer robotics — robots in the home. I find that to be the most challenging market and something that like I haven’t particularly thought about because building something boutique for everyone’s home is way, way, way harder than building something that sits in its own physical space that can be controlled and manipulated by you and everything goes to it and comes out of it.

Sabrina: We have this debate a lot at Madrona as well of just where is the best use case for robotics? Is it in the enterprise setting? Is it in the consumer setting? And I’m curious, you touched upon it a little bit about the different verticals in agriculture and other, but to be a little bit more specific, if you’re a future founder you know, listening to this podcast today, what opportunities are you seeing? What white spaces are you seeing for a founder to come in? Is it specifically within verticals or applications or do you see it more on the hardware or software side? Just curious what your thoughts are around that.

Sidd: I do think that there is potential everywhere. My own personal interest has always been in trying to find a vertical opportunity and then do whatever it takes to solve that problem. Also specifically look at a place where automation is not necessarily a must have but can be a ramp function value add. I think if you start off with,” Hey, if I don’t build Rosie the robot, then I don’t have a business.” Well, then you’re in trouble. I think we want to make sure that there is a business case even with very limited automation. Even there like I would stair-step automation as oftentimes quality assurance prediction is much easier than actual physical manipulation. If you can actually have a value add that’s just about having sensors in your world that help you understand your process better or someone’s process better such that it can make it more efficient. That’s already a big win. And every single motor that you add to your world is an order of magnitude, greater complexity because everything breaks when you interact with the physical world. So, I think even there, when you’re starting to add automation, at first ask the question. Can you add automation that doesn’t move but that is able to monitor and enhance your process path through AI, computer vision, machine learning, and then subsequently use that to bootstrap how you might want to integrate physical automation in.

I think that’s a place where I think that there’s a lot of potential, right? Like even thinking about quality assurance. I think the biggest challenge with just inference and perception as a business is that you might get sharded by so many different applications. You know, someone has a light bulb that they want to assure, someone else has a PCB. Someone else has a salad that they want to know whether any of the produce is old or not. Someone else may have bananas. Someone else may have other things. So, I think the challenge that is in making sure that there aren’t so many different verticals that you’re chasing, that you end up doing a poor job of any one of them. I think this is the biggest challenge that I see in this particular space is that sometimes people either focus too much on a vertical and that’s too narrow. It’s one of the teeth in a comb and it’s too small or they try to build infrastructure and that becomes too broad, like, I don’t want a machine learning model. What I want is a managed service. I want someone not to hand me over like a piece of code. I want someone to solve my problem. My problem might be, I want to be assured that the chicken I’m selling are all of the right shape, or I want to be assured that the fries that I’m selling are all numbered, 37, there are 37 fries in each bag that I’m selling. I think being able to produce value while still being able to not be sharded by too many teeth in the comb is interesting and challenging. I don’t think anyone’s cracked that yet, but I think that there’s a lot of opportunity in that space.

Aseem: Yeah, you alluded to this, but I want to ask you this million-dollar question, or maybe it’s a millions of dollars question these days with how companies are performing and creating value. Hardware, robotics, or software robotics? Let me qualify that a little bit. There’s generally healthy tension on — do I solve a problem using hardware smarts and precision and building more complex arms, or do I actually solve it using the power of software and intelligence and ML models and CV? How should one think about that?

Sidd: I think about this a lot, I must say. The way I think about it is so first of all, I don’t have an answer. I just have a thought about it. I think that the constraints of the built environment often tell us what’s possible and what’s not possible. So, if you look at automating your kitchen, for example, it’s very hard to put belts and pulleys and tubes in your kitchen that plop food on your plate. Just the natural constraints that you created because it’s a kitchen that you want to use — it’s a kitchen that has certain dimensions — makes certain hardware choices possible or not possible.

The fewer constraints you have, the easier it is to solve using only hardware. You can use off-the-shelf mechatronics to solve a lot of these problems. Our beer factories and our Frito-Lays factories are great examples of solving a very hard food manufacturing problem effortlessly because we’ve removed a lot of the constraints that exist there. My personal taste is in looking at spaces where the constraints of the built environment make it nearly impossible to use off-the-shelf mechatronic solutions that compel us to use a combination of what we call robotics. Whether it’s robot arms or more complicated actuators and a lot of intelligence — computer vision, machine learning nonlinear control.

I think those are the spaces that lie at the intersection of things that are very valuable because no one has a solution for it and things that are fundamentally going to get better. Our compute is always fundamentally going to get better. So, I think to answer your question of like hardware versus software, there are many problems that can be solved using just hardware. But I think I gravitate towards problems, which are much, much harder to solve, either constraint wise or from a value proposition point of view, with off-the-shelf mechatronic solutions.

Aseem: That’s very cool. A slightly related question. There’s always this concern around safety, robotic operation, like human in the loop. You know, what happens when a robotic system like Tesla goes off the road and what’s the correction mechanism. I know Sidd, last time we chatted, you had a really cool posture on how you think about humans in the loop. I remember distinctly your comment about these things will fail. We know that they would fail as we are building and getting better. How should you design for that?

Sidd: First of all, I do agree that safety is a requirement. It’s not a nice to have, it’s a must-have. I think also that we have to assume that robots will fail. I always believe that it’s not the happy path. It’s not the YouTube video that you should be looking at. You should just be looking at all the times that the robot fails, right — the unhappy path. And I think that humans also have perceptions of robot capability based on happy path that they see. I think as an analogy if an alien being watched YouTube videos of 7- to 10-year-old children, they would think that their virtuoso pianists, incredible gymnasts, amazing singers, the best at math — can recite thousands of digits of Pi because they don’t see the unhappy path. Which is they’re running around kicking and screaming most of the time. I think it’s the same with robots, right? I think when people look at videos of robots, what they see is the happy path of robotics.

A lot of what I do is anticipate what the unhappy path will be and address it. This is actually hard because sometimes your robot doesn’t know when something goes wrong. This happens commonly, you know, the robot fails to grab something, and it doesn’t know that it’s failed to grab something.

So, there’s an observability question of we need to make sure that the robot knows that something has gone wrong. I think the second piece is around creating exception paths, such that you can gracefully fail. In most situations, you can gracefully fail. There are a lot of opportunities for correction, particularly if you own the full stack. A lot of the design engineering that is needed is to make sure that we are able to identify what the exception paths are and handle them. Actually, if you watch a high-speed video of yourself grabbing a coffee mug, you’ll notice that you’re just fumbling all the time. You’re failing and failing, and then grabbing the coffee mug. But all of that happens in less than 10 to 15 milliseconds. So being able to react to these in an elegant way is important.

In terms of human in the loop. One of the things that I believe strongly in is to be able to leverage human feedback whenever and wherever possible. You always want to build systems where you can either offline or even online annotate data, annotate the robot, such that it’s able to learn from its experiences as well as it’s able to learn from human supervision. I think that we have a lot of tools available now that help us do that. We have the ability to capture large amounts of data. We have the ability to send that data to annotators who are able to annotate it for us. I think that’s, to me, being able to build continual learning algorithms and being able to formalize that is a way to capture human insight without necessarily having to rely fully on it.

Sabrina: That’s fascinating. I’d love to pivot a little bit and have you tell us about your journey at Berkshire Grey? You were one of the first founders of the company, and now they are one of the leaders in providing robotic picking and packing technology used by companies like Target and FedEx. Can you tell us a little bit about how that came to fruition? What were the challenges you saw in the industry at the time? And I would love to learn a little bit more about your experience, scaling the business and ultimately making a bet on the future.

Sidd: I still have such warm feelings about my time at Berkshire. I really loved it. It coincided with my daughter being born. So, it was pretty epic time for us as a family. I see my daughter grow —she’s seven years old now. I can tell how old Berkshire Grey is based on how much Sameera has grown. Obviously, full credit goes to a lot of people. I’m just one of the people who is part of this journey.

But I think the central thesis was always this idea of being able to build a full robotic stack for automation. One of the things that we had observed was that there were some really amazing companies that were out there, but they were providing a Lego block that would attempt to fit itself into a giant jigsaw puzzle. Like Saying, “Hey, I have a nice picking system, or I have a nice system that can move a tote from one place to another.” You realize very quickly that to integrate a picking system with a very complicated warehouse management system that has so many inputs and so many outputs is much harder than building the picking system itself. Even if you have the best picking system in the world, your ability to integrate it with even one integrator is very hard and to think about like having to integrate with 10 or 20 of them, right? Those kinds of businesses were failing. Not because they didn’t have a beautiful, perfectly crafted Lego block, but it’s because it didn’t fit in the house. It was too much work to make it fit in the house. You have to take the house apart and put it back together. The sort of central pieces of Berkshire Grey was, give us an empty space. As an input, trucks come in and as an output, packages come out and, we won’t tell you what’s in this empty space and you don’t tell us how to control that empty space. It was a huge bet for us to think about automation that way. Because we had to believe that people would give us this empty lot. It’s a huge investment on people to give us this empty lot, but the positives were that we could fill this empty lot with whatever we wanted — people, robots, anything — and we controlled the entire experience. That was what we really sought to do. I must say, initially a large part of it was not automated, but still, the input-output relationships were maintained. I think over time as more and more maturity came about — and obviously, since I left Berkshire Grey, they’ve become even more mature on everything that they’ve been doing. I think you fill out more and more pieces of this Lego house, but you control everything that happens in there. So, I think that was a big learning for me. I think another learning is also that you know, when we were four people each one of us had to write code, talk to vendors, be a program manager, weld robots. I really enjoyed that. I really enjoyed that because I just love building robots. As the company grew to like 100 and then 200 people, I think we had to organize ourselves into various roles. A lot of fun too, but fun and a different way and potentially needed a different set of people. Obviously, I’ve done a few things since Berkshire Grey, and I realized that it’s almost like shedding skin. You have to have one skin and then you molt, and you shed that skin and then a new skin comes about. And you have to just accept that the people who were part of the original skin may not necessarily be the ones who are ready for the next one. The one after that. Some people might grow into those roles and those opportunities. But I think just acceptance of that was valuable.

I think another lesson that I learned was customers don’t want to tell you anything. This is incredibly frustrating for us because we just wanted to know what actually they wanted to solve.

If we knew what they wanted to solve, we could do it, but it took us a material amount of time before we earned sort of their trust for them to be able to open the door more and more. I think that was really interesting for us.

Sabrina: That’s awesome. I hadn’t heard that story before. You know, from your experience at Berkshire Grey, and as you mentioned, you’ve now worked with a lot of earlier stage companies and ideas since then, curious to hear what mistakes you’ve seen, people make along the way, and any advice that you have for new founders as they think about their journey in robotics.

Sidd: Oh, boy, I haven’t made a lot of mistakes. So, I think that in some ways the scars that we have are what help us not make those same mistakes again. I think that’s probably the only value that I provide is that I’ve made more mistakes in robotics than other people. So, I cannot just tell you what not to do. I think it’s really important to carefully think about what your minimum lovable product is. I cannot stress how important that is. I think that people fall in love with a certain way of doing something or fall in love with a certain piece of technology, and they forget that in the end it has to be valued and loved by your actual end customer. This was, frankly, a big struggle for me too because I’ve been building robots for so long that I have a way of building robots. I have to unthink that sometimes, because I don’t want to be stuck in that same rut. I think the other thing is that a lot of people who want to build robots come from software or AI or machine learning and forget about, or at least don’t have enough scars from, just long lead times for getting anything. I was actually just talking to somebody who is fascinated by how hard it was to do integration testing in robotics. They were telling me, “Oh, you know, with software, you just click this button and then you can run a, you know, integration tests on everything. How do you do that with hardware?” I was like, “Nope. It can’t be done.” You have to actually have a QA team that goes out and does these tests for you? You have to pay them a fairly significant amount of money to go do that and that takes a significant amount of effort.

So, I think there are certain mental models when you’re only building software that you need to undo yourself of. That said, there are other people who will only build hardware who want to build robots? You know, they build amazing, beautiful hardware systems and there too, there’s a failing because you believe that everything can be done with hardware ingenuity. Whereas, you know, I keep telling them, computers are free and instead of building a mechatronic way of, let’s say isolating a part, “Hey, just put a camera there and then it’ll tell you where it is”.

So, I think that robotics is a funny space, which requires you to know both hardware and software, and I think my advice would be make sure that you have enough people in the room who have enough scars of making enough mistakes in hardware and software and have the nuance to be able to.

Lead them to do the right thing. I think that’s been the biggest learning for me.

Aseem: Yeah, very profound. It’s almost like go hire the people who make mistakes so that the robots don’t make the mistakes. It’s amazing what we take away from this conversation. Hey, Sidd, I know that the only thing between you and dinner is us and ever since you mentioned samosas, I’m envisioning, you’re going to go off to a room it’s a Bat Cave in your house, you’re going to press a button and the robot is going to start frying a samosa.

Thank you so much for making time. I think there’s a lot of aspiring founders that we’ve talked to who are deeply interested in, you know, very passionate about this space and I’m sure they will take a lot away from this conversation. So, thanks for spending the time and thanks to those of you who tuned in.

Sidd: Thank you.

Coral: Thanks for joining us for this week’s episode of Founded and Funded. If you’re interested in learning more about Madrona’s investments in the robotics space, you can check out the show notes for Aseem and Sabrina’s contact information. Thanks again for joining us and tune in, in a couple of weeks, for our next episode of Founded and Funded with Snorkel’s Alex Ratner.

We just wrapped our 2022 annual meeting, which we were able to have in person for the first time in three years. Madrona has worked with many of our investors for well over a decade, and they span all types of foundations, universities, pension funds, and family offices.

The annual meeting, with about 150 attendees this year, was a much-needed dose of human connection that reminded many Madrona investors why they got into this business in the first place — people and more specifically — great founders. During the day’s events, the audience heard about Madrona’s results, of course, but the stars of the show were the founders and leaders at our companies — and we took the opportunity to check in with them on this week’s episode of Founded and Funded.

Full Transcript – This transcript was automatically generated and edited for clarity.

Welcome to Founded and Funded. This is Coral Garnick Ducken Digital Editor with Madrona Venture Group. We just wrapped our 2022 annual meeting, which we were able to have in person for the first time in three years. Madrona has worked with many of our investors for well over a decade, and they span all types of foundations, universities, pension funds, and family offices.

The 2022 annual meeting, with about 150 attendees this year, was a much-needed dose of human connection that reminded many Madrona investors why they got into this business in the first place — people and more specifically — great founders. During the day’s events, the audience heard about Madrona’s results, of course, but the stars of the show were the founders and leaders at our companies. I thought it would be a great opportunity to check in with some of them on the challenges they face last year and how they were able to overcome these challenges. And we spoke about what they’re focusing on in 2022. And here at Madrona, we’re always looking for and working with new founders. So, I asked them for a piece of advice, they’d share with someone just setting out.

Clari

One of the first companies to present during our 2022 annual meeting this year was Clari. Co-founder and CEO Andy Byrne updated us on his enterprise SAS company that arms chief revenue officers with artificial intelligence that allows them to drive more revenue and boost the predictability and accuracy of their forecasts. And while growth is certainly on the agenda for him in 2022, and he has a plan focusing on expanding value for customers, Andy recognizes that 2021 had some growing pains because of the massive growth the company saw in direct response to the COVID 19 pandemic. Companies wanted visibility into their forecast and pipelines more than ever, and Clari had just the tool. But being ready for that growth and required scale at the flip of a switch is not easy, Andy said

Andy: A lot of things broke, and we had to go about moving from what I would call scrappy startup point solving to scalable machine actual system solving. And that’s really a different mindset shift as you get into the level of scale that we’ve experienced. That was probably our biggest challenge. And the graduation from that sort of scrappy startup to machine actual has been really a joy to experience.

Booster

Coral: Frank Mycroft co-founder and CEO of Booster faced another sort of transition in 2021. Not only did the transition from 2020 to 2021 mean another year of unexpected pandemic restrictions and working in a mostly virtual environment for his team, which is re-inventing cleaner fuel delivery services. But he also had a new addition to the family. The birth of his third child came mid-year. While it was a bit more challenging than he remembered. He said it gave him some new perspective.

Frank: I was expecting the baby, I was not expecting how difficult newborns are. They’re really not self-sufficient, are they? And I had forgotten that. I felt like 2021 was a year where it was easy to have short attention spans. And it was easy to have group think because everybody was reading the same things and on the same Zoom calls. So being very intentional about saying no to things you didn’t want to do and carving out time to be intentional first-principles thinking on your own was really important.

CommerceIQ

Coral: Another company that was very intentional in 2021 was CommerceIQ run by founder and CEO Guru Hariharan. Commerce IQ is an intelligent commerce platform that helps consumer brands like Colgate, Nestle and Kimberly Clark grow their e-commerce business. The company had growth goals, but because the platform is only appropriate for certain verticals, identifying expansion, targets was becoming difficult. But by asking hard questions and digging in, the company is better for it. And it actually just announced a $115 million funding round at an over billion-dollar valuation.

Guru: We had to do some introspection in terms of how we land and expand how we provide more value. We had to go back and do some soul searching. The way we did that was actually going back and asking our customers how they thought this market was going to be evolving over the next few years. And they told us “Look, point solutions are not going to work for us. I don’t expect in the year 2025 or 2030 to wake up to say, ‘I’m going to be looking at a supply chain system, taking an Excel file from there and pushing it out into a retail media system, taking an Excel file, from there and pushing into a promotion or a sales management system.’” They told us that point solutions are not going to work. But at the end of the day, we were a point solution at that point. It pushed us to sort of take a step back and really create the right vision for the company.

This is one of those where just using customer interviews, and the ability to work with customers in a way that we understand their problem, but we were not necessarily listening for solutions from them. So, we understood the problem that point solutions was not going to work. We connected the dots and we said, well, we need to then create a platform. And we went back with a vision that was fleshed out, and we showed it to them, and they said, this is perfect. So, our big learning was going back to the roots and trying to understand from a customer perspective what were the key problem areas, and then going back and actually creating some solutioning around it and then creating the vision for the company. It was a phenomenal experience. And frankly, that was one of the key reasons why we were able to raise a billion-dollar valuation round, because now we are making some significant waves by showing that vision to our customers and to the market.

Rec Room

Coral: It was really fun talking with Rec Room CEO Nick Fajt during our 2022 annual meeting. Rec Room, of course, is the virtual reality world where you can create and play games with your friends. And the metaverse is a huge topic of conversation with Facebook changing its name and both Mark Zuckerberg and Satya Nadella not being able to go through an earnings call without saying the word more than a couple of dozen times each, but Nick launched his company a few years before the pandemic hit, and since December 2020, when Madrona led the series C round, Rec Room has raised $265 million and has millions of player-created rooms. Usage also took off during the pandemic and has continued to grow. Coming out of the pandemic, Nick says he is focused on three big pillars for Rec Room.

Nick: The first is user generated content. Everything in Rec Room is built by players, and we’re constantly looking at ways we can improve the tooling and help people build whatever’s in their imagination. The second area we focus on pretty deeply is building a fun and welcoming community for everyone — what are the ways that we can use our unique reach and our unique platform to help people connect across geographies and across time to make those meaningful connections, make meaningful new friends and make memories with those folks. And then the last area we talk a lot about is being a radically cross-platform app. It’s really something that helps both the user-generated content because it means you can create content on any device and it will go to every device, and it means your devices can get out of the way for the social and the community aspect. For most technology, you really don’t want to connect your device to your friend’s device, you want to connect with your friend. So we take this radically cross-platform approach so we can help people connect regardless of what device they have. So, we’ll be coming to some new and exciting and unannounced devices later this year.

SeekOut

Coral: One of the most recent Seattle-based portfolio companies to land unicorn status is SeekOut following its $115 million funding round. Companies are all facing the great resignations, so recruiting and talent retention are top priorities. SeekOut’s intelligent application pulls data from across myriad sources to find companies the best and most diverse candidates. As SeekOut co-founder and head of product John Tippett looks to 2022, he said the company is focused on scaling and applying its considerable success in recruiting to building the tools needed for internal employee engagement and retention as well. I’ll let John explain.

John: The biggest thing we’re focused on as a company at SeekOut is scale. How do we provide more capabilities to more customers, so they can be more efficient and more effective with their talent as we get into this new world of work? So we’re building out all of our teams and we’re building on new capabilities. One of the things we’re also focused on is how can we turn all the things that we’ve done for recruiting new people into a company to helping you retain, engage and grow your internal employees. And I’ll give you an example of how we got to this. SeekOut’s passive sourcing product has the ability to look at talent insights about any talent pool. So, you could say, what do we know about accountants in Chicago? And when we show that to customers, they say, “this is amazing data — I wish we had the same kind of data for our own employees.” And it’s really based on that insight, we decided we could do this around talent insights for companies so that they could optimize where they’re investing, who they’re hiring, even where they’re building new offices when they eventually get back to that.

A-Alpha Bio

Coral: One of Madrona’s investment themes in recent years has been the intersection of innovation. And at this year’s meeting, we heard from David Younger at A-Alpha bio and Jesse Salk from TwinStrand. And of course, we also had the distinct pleasure of having Dr. David Baker from the Institute of Protein Design give the keynote address during the event. The opportunities coming out of combining the power of data and computer science with life science research seem almost endless. And Dr. Baker actually mentioned during his address that the students in his lab used to want to all become professors, and now they almost all want to start their own companies. So, the opportunity for madrona to help founders fund and build up companies in the space will hopefully be plentiful.

David youngers company, A-Alpha Bio actually spun out of Dr. Baker’s lab. The company combines high throughput, synthetic biology with machine learning to dramatically accelerate the discovery and optimization of lifesaving therapeutics by focusing on antibodies and molecular glues. I will let him tell you in his own words, what they’ll be focusing on for the rest of the year.

David: So, antibodies are protein therapeutic, so they’re made of protein and they function by sticking to other proteins. A-Alpha Bio is the protein, protein interaction company. So antibodies are right up our alley. Everything about them is protein, protein interaction. And so, in that space in 2022, we’re doing a lot of work to build and optimize our own internal antibody library and really go through the workflow of discovering novel antibodies for targets that are otherwise very, very challenging to find the right antibody properties for. So that’s a combination of partnering with leading pharmaceutical companies in the antibody space and also doing some of our own internal antibody discovery and optimization to build our own proprietary pipeline.

In the molecular glue space — molecular glues are small molecules, but they function by bringing together by essentially gluing together two proteins that wouldn’t otherwise interact. And this is an incredibly exciting and relatively new therapeutic modality. And what A-Alpha Bio is able to do very uniquely in this space is identify targets that are suitable for molecular glues. And so, we’ve started to do that with partners. Late last year we announced a partnership with Kymera Therapeutics, who’s one of the leaders in this field, but we’re also starting to build out our own internal capabilities to start programs of our own. So that’s a major initiative for 2022. And then all of this kind of falls under the umbrella of generating a lot of data that we can use to train and validate our machine learning models.

TwinStrand

Coral: Another company with a lot of data and the potential to impact a lot of us profoundly is TwinStrand Biosciences led by founder and CEO Jesse Salk. TwinStrand’s technology is working to utilize informatics to make existing genome sequencers 10,000 times more accurate so scientists and doctors can see subtle changes in DNA that are not only relevant to basic science but particularly to cancer patients. But launching its first product into a pandemic was not the ideal scenario. So, Jessie is looking forward to seeing what the company can do with restrictions lifted.

Jesse: We are really looking to get out in the field, work with more customers, work with more of our clinical and research partners, go to more meetings and generally get an opportunity to spread our wings and use all the sophisticated infrastructure we’ve built the last two years while we’ve been a bit stuck at home. This is my first company — I’m a trained scientist and a physician. So, this is my first time doing this, so it’s been a little bit, challenging to be operating with so many different variables, but I think we’ve done Pretty well. And, you know, part of our technology is about, high accuracy, high sensitivity, and understanding evolution of cancer and cancer cells and so we think we also need to be able to evolve and we’ve done a pretty good job.

Advice

Coral: I promise advice from founders who spoke at our 2022 annual meeting. And I’m going to start here with Jesse because while his may seem straightforward, I think it’s something people often forget.

Jesse: I think you need to have some humility — be very open with what you’re good at and what you’re not good at and what you need to learn, be willing to recognize that there are many colleagues around you who know where you are and are a few years beyond you and are willing to give advice. I learned a lot, and I had tons of support from Madrona, from our other investors, from colleagues and CEOs of other companies. And, just be very comfortable with who you really are and take stock and use others as resources. And I think I’ve tried, to give back and kind of do the same thing because there are certain things, that are not rocket science, but it’s just, you know, you’ve got to learn it and there’s no reason to make everybody reinvent the wheel.

Coral: Next. We have Clari CEO Andy Byrne.

Andy: Take your idea, get with three to five customers that believe in your idea and your vision that they just fundamentally say, “You build that and I will figure out how to get it into my company, and we’ll try to use it and together let’s go build something great.” And that entrepreneur needs to identify who those early adopters are and then you’ve got to go find the person inside that company that’s also saying, “I’m willing to take a risk. I’m willing to turn it on and be a champion internally for you.” So you find those three to five and then you partner together and you co-design and you never, ever, ever give up. And you listen incredibly carefully not with happy ears, with ears that are like, well, if the customer says, “Oh, I would love you to build that.” You need to say, “Well, hold on. Why?”
“Well, because we might use it.”
“Well, why would you use it?”
“Well, because we…”
“Well, why is that valuable?”
And you get down to the depth of knowing, okay, this is actually something that I can monetize. And if you do that level of work of identifying the logos, getting the people in those accounts — three to five of them — and have all this tenacity and the ability to MVP and exceed the customer’s expectation with a product that blows them away that they got earlier than they thought they would. Then you start to get momentum off of your base foundation of customers that become your key marquees that allow you to then build on top of that foundation and start growing incrementally to your next handful of milestones. So that would be my advice to a young entrepreneur who’s starting out and never, ever, ever give up.

Coral: Finally, I’ll leave you with advice from Booster CEO Frank Mycroft.

Frank: You got to sell the product first before it even exists. Take that time you would’ve spent developing it and get out to your customers. Go talk to them even better. When we were starting out, we lived, we literally lived and worked in offices right next to our first customers. You’ll iterate so fast on the idea and you’ll save yourself so much time. And when you finally get to the build part, try to build on the riskiest thing. First, this is not easy for an early entrepreneur. You want to work on what you’re comfortable with, what you know, really what. But if you want to really win, I think you’ve got to figure out the scariest thing, and go work on that first, because if it doesn’t work, you’ll be grateful. You didn’t waste a lot of years doing other stuff before you figured that out.

Coral: Thank you for listening to this special episode of Founded and Funded. Tune in next time, as we launch a series spotlighting our IA 40 winners.

In this episode of Founded and Funded, Madrona Managing Director Matt McIlwain and Partner Aseem Datar sit down with Qumulo CEO Bill Richter to talk about developing meaningful partnerships. Madrona was an early investor in Qumulo when it launched in 2012, and the company recently partnered with Microsoft to launch Qumulo on Azure as a Service. Startups often partner with large enterprise companies to accelerate growth, but there are benefits to both parties, and in this episode, we take a look at it from both perspectives.

Transcript below

Welcome to Founded and Funded. I’m Coral Garnick Ducken, the new Digital Editor for Madrona Venture Group. And in this week’s episode, Madrona Managing Director Matt McIlwain and partner Aseem Datar sit down with Qumulo CEO Bill Richter.

Bill is no stranger to Madrona bringing 20 years of technology experience to the team when he joined as one of our Venture Partners. Madrona also invested in Isilon back in 2001, and Bill was the CFO when that company went public in 2006 through its $2.5 billion sale to EMC four years later.

Then, of course, Madrona was also an early investor in Qumulo when it launched in 2012. In simple terms — if we can talk about the cloud and data storage simply, Qumulo is a cloud-based data management platform that gives companies more flexibility when it comes to storing, managing, and running massive unstructured data workers.

The company, of course, partners with Microsoft Azure, which is what sparked the idea for the conversation on partnerships today. Yes — we’re talking about partnerships. They are often thought of as an important tool to scale from a startup into a growth phase company and then onto becoming fully mature.

But why partner? What are the actual benefits? And when you do partner, how do you make it work and leverage that partnership to truly bring value to your customers. These are the questions that Bill and Aseem, who was previously an Azure executive, are going to break down for us today.

So, let’s kick it off.

 

Matt: Thanks everybody for joining us for this Madrona podcast. I am Matt McIlwain and one of the managing directors at Madrona, I am just delighted to have one of my fellow partners Aseem Datar here with me as well as CEO Bill Richter of Qumulo. And what’s fun about this conversation is that we’re going to be able to look at.

How companies partner with large enterprises with large platforms and, look at that journey from a couple of perspectives. let me start with Bill. And I think there’s a more abstract question here to ask, which is, why does a rapidly growing private company want a partner? What are the benefits of that to you? Vis-a-vis going directly to market with customers.

Bill: Hey, Matt, for you and the Madrona gang, and Aseem, I just want to say it’s absolutely great to be here with you. I’ve had the distinct pleasure of being able to work across four or five companies now with the Madrona community and it is just, it’s been an outstanding experience.

Okay. For your question, why do it? That’s a great place to start. Look, I think in any successful startup or growth-stage company, like Qumulo, focus is everything. And we constantly ask ourself this question over and over again, inside the company: what are the one, or very small number of things, that we’re going to do better than anybody else in the world. And I think that’s a very wise strategy. The other side of it though, is if you’re doing one, two or three things extremely well, that implies that there are dozens, if not hundreds of other things that you don’t do. And by being able to partner and complement best-in-class capability with somebody else’s portfolio in service of customers, it’s a very sort of simple and sound strategy.

Bill: And that’s really where the notion of partnering comes in for us.

Matt: So within the context of your strategic focus, are there ways to get leverage out of partnering with others – that’s leverage that is mutually beneficial?

Bill: That’s right. Leverage is a great way of expressing the kind of business element of this. And that’s something that’s obviously important. And um, I say customer leverage like customer value leverage. So, we have customers — nearly a thousand that know and rely on us for a very specific set of capabilities and helping them manage their unstructured data at scale. They know that they can rely on us as incredibly powerful, reliable, and capable, and then they have all sorts of other things. They want to be able to create more and more connections with their applications. They want users to be able to harness that information more readily and rapidly. They want to be able to use the environment of their choice. And that’s, I think we’ll get into Azure a little bit later, but a lot of our customers have made the decision to standardize on Azure.

And so, when you think about those things, the discreet capabilities that those customers want, and then the power of choice, freedom, and flexibility to run their applications, where they want. That’s a very powerful value proposition for customers. And then if you take the power of that value prop for customers and work backward to a partnership, things make a lot more sense to both sides, much more quickly.

Matt: Yeah, that customer centricity, I think, we’ll keep coming back in, in our conversation, but Aseem, when you had your Microsoft hat on for many years and you were working with third parties outside of Microsoft, why partner from that perspective? What were the goals of a big company around partnering with other software companies?

Aseem: Yeah, it’s a great question. And I think Bill alluded to some of it, which is, it starts with the customer, so I won’t repeat that point in terms of deriving customer value, but I think two things are super critical. One is, in general, Microsoft has always been a platform-centric company — like the companies built platforms. If you go all the way back to the Windows days, and even with Azure, like it’s a horizontal platform. And from a customer standpoint, platforms are great. But you also need solutions on top of the platform. And that’s when the focus that Bill talked about, that Qumulo delivers combined with the power of the platform will complete the solution in that particular scenario.

And while platforms get bigger and richer, the value that somebody like Qumulo provides is completing the solution, getting deeper and deeper into those verticals. And doing, you know, not just based on the value prop, but also last mile, you know, excellence that creates value for customers.

The second part of that is scale. Microsoft operates at a lot of verticals, a lot of customers and while I think somebody like Qumulo starts off with a deep focus, Microsoft, as a company also sees varieties of those applications applied in different industries.

And so, to be able to use the power of the field, the power of the sellers, the power to transcend industries is what gets you massive scale. So, Bill and team can focus on building great product, and Microsoft can work with them hand-in-hand to go achieve that scale once a flywheel is established.

Matt: That’s really helpful. And maybe we can jump into this actually, Bill, before we get to Azure. Let’s talk about one of your other prior partners. One of the very unique and differentiated things around Qumulo is that it’s a software-only solution that scales across any type of hardware.

Whether it’s a box or a cloud, and a lot of your customers even still today prefer to have their implementations in the private cloud. And so that took you down a path of partnering with some hardware companies. Tell us a little about that.

Bill: Yeah, sure. And this was one of those things that just happened. It started with an individual customer. I’ll tell you a story. We had a customer — it was a well-known animation studio in Los Angeles. One that makes many of the movies that we all enjoy, and they became enamored with our technology. They tested. They loved our software and then they told us, “Hey, Qumulo, we actually have a private cloud agreement with HPE. (Hewlett-Packard Enterprise) That’s the standard that we’ve chosen for our private cloud.” And actually, they put it to us. They said, look, you’re a software-defined. That’s why we bought you. Now. We want you to deploy on HPE. Now what a great way to start a conversation off with HPE. Where one of their large global customers is saying, “Hey, I like you and I like them. I want you to work together.” I will tell you that experience cuts through so many barriers that might entail a partner program and a step-by-step process because it gets the attention and the emotion of senior executives on both sides.

And so we started with that customer. It was an easy certification for us. That’s the value and the power of our software. They deployed it. And then we worked backward from there to start asking, hey, this use case is now established. There are so many other customers, like Aseem mentioned the notion of a flywheel, and that’s what everybody’s looking for in these partnerships. And we began to dominate that vertical of media and entertainment. And then very quickly after we started stacking up the adjacent verticals where we really serve customers, places like life sciences and healthcare organizations and oil and gas companies and research centers.

That was about four or five years ago. If you fast forward today, that is an at-scale partnership that’s been enormously successful for Qumulo. It’s enormously successful for HPE and both sides would say, Hey, we’re just getting started. And maybe one last point, and then I’ll pause is just the strategic fit.

Bill: HP is a great brand. It’s legendary in Silicon Valley. In fact, many would attribute it to starting Silicon Valley. But what they didn’t have is a scalable, unstructured data service, like Qumulo, and they recognize that. And what we didn’t have is global scale with tens of thousands of customers in every country around the world.

And so, you put one and one together and it really does make 11 rather than one and a half or two and a half. And I think that’s the secret to our success.

Matt: Let me pick up on two things there. One is this idea that the partner has something complementary to you and in this case, not only a complementary go-to-market organization, but also an international one, I’d love you to speak a little bit to that, that the leverage that gave you in the company and working with HPE from an international perspective Well, I’ll start there.

Bill: Working with any large organization, the power of their geographic presence is enormous. We have Qumulo deployed today in something like 50 countries around the world, all the big ones that you’d expect, all the major economies, but also some of the smaller ones all across South America, all across Asia into Africa.

And then of course, with a lot of concentration in the economic centers, that’s incredibly difficult for an emerging company to do on its own. And also, not just the logistics of it servicing customers around the world, but the brand recognition. If you’re way out and Chile or South Africa or in Taiwan the brand recognition of a global company, whether it’s Microsoft or HPE or some of the others really matters to those companies, it gives them a sense of trust.

The flip side of it, is you sort of think like, well, what’s in it for the big company or what’s in it for the platform player. I think it’s a real disappointment for customers if they’ve adopted a platform player, even the biggest companies on Earth, and then they get the feeling that they’re in a walled garden and the only services or products that are available to them are branded by that company.

Bill: Because they know that there’s going to be parts of that stack that are either missing or very underdeveloped. And so, it’s the open organizations the ones that open up their platforms and let customers know, hey, when you come here, you’re either going to get the best product that we’ve created that leads the category, or very easily, you’re going to be able to adopt other technologies that are best in their space. And you’ll never have a walled-garden experience. I think that’s very powerful, and we’ve seen that certainly with our partnership with Azure and some of the others as well.

Matt: No, I think that’s really well framed. And the other dimension here is the time and timing. You said, hey, look, we’re four to five years into this HPE partnership. It’s now really at scale. And I think sometimes it’s hard for younger companies to know that something’s going to take, two to three years, let alone two to three months to build out. These partnerships do take time. So, I’d love to hear When are these companies far enough along that they’re ready to actually work with a platform player.

Bill: Look, there’s a, there’s a sine curve of emotions when you’re developing these partnerships. There’s the excitement of getting the attention of a larger company in the early work people strategize together and see the opportunity. There’s a dip somewhere along the way where you realize, hey, there’s some really hard integration work to do or figuring things out there’s commercial agreements and stuff like that, that um, is hard work but necessary.

But then, the real thing that has to happen is you have to find your first customer. One is the hardest one to get. But one makes three and three makes nine and nine make a hundred.

And there is an element of being steadfast about recognizing the strategy, knowing it’s going to take time, knowing it does start with one. And being able to create some repeatability there because especially for a larger company the first thing that their fields will ask is, hey, how many of these have we sold? Or how many customers have we made successful? And so, every incremental win together makes that easier. And then the flip side of that is the early wins are the hardest.

Aseem: My perspective on this is I think it really comes down to two buckets. And I think the first bucket is what gets the technology companies and platform providers interested. And I think it starts with incremental value that you can go create for your customers.

Like the solution that you have as a platform and the solution that in this case Qumulo brings — can that create incremental value for customers that then creates differentiation in market. So, I think, the question that a platform provider would ask is, so why does Qumulo plus Microsoft make it better than any other solution in the market?

And is that something that’s long enduring and can that continue to provide customers the value that they need over time, and can it only grow? So, I think that addresses. The why question? And can we go tackle these white spaces? Which gets everybody interested. And then the how and what of that is really around what I call the Happy Meal Litmus test. Which is, do we have five happy customers using the product day in and day out? And it’s hard to get the first five. And, as much as people think that Microsoft is a very, orchestrated big ship, you know, my boss used to say it the best, which is it’s a bunch of mini canoes all going in the same direction. And to align all those things from the outside in is incredibly hard, but nothing gets the attention more than customer demand and customer usage. And if you’ve gotten a path to get five happy customers on the platform you start to identify all these friction points as companies partner, and then it’s a matter of like, how do you smooth these out over time, one by one. And then the sixth gets easier. The seventh gets easier and then very quickly everybody including engineering, product, go-to-market, sales, like these things start to sing in, in one integrated fashion. And that’s when I think the flywheel gets established.

Matt: Well, That’s I think really helpful, strategically, conceptually. I’ve heard you both talk a lot about, bringing the customers. Bill. Maybe you can talk us through now bringing us forward into the Qumulo, Azure partnership and some of the early days of getting that partnership going and finding that first customer.

Bill: I guess the first thing to talk about is just to spend a little time on the tech. Qumulo has built the world’s most powerful software defined, scalable, unstructured, and file data management service. And what all that translates to for our customers is they have petabyte-scale environments with millions or billions of pieces of unstructured data. It could be a genetic sequence. It could be a radiological record. It could be a PDF document, but they’re at scale. And those customers derive value by being able to consolidate that information into a single place and then be able to reason over it.

And the at-scale part is really hard. In fact, we just won our 35th patent last month as we’ve built this technology. And when you look through the Microsoft catalog, there’s obviously Azure has an enormously powerful services, but in this section, they were missing something. And so, by working together and being able to help customers build these environments in Azure, it’s really win-win-win. Azure will end up allowing a customer to get more out of their services and deploy more applications, more thoughtfully and more rapidly. Qumulo wins for obvious reasons that for us, it’s a SaaS service sale. And these customers, it’s a real problem for them that we solve together. And before we embarked on this partnership, you can imagine that we spent a lot of time interviewing our customers about what they were trying to achieve, particularly in the public clouds. How they wanted to do it, how they wanted to consume our software and then we got a lot of advice from Microsoft as well. Like, Hey, what have other partners done? How has it been successful? What are the pitfalls? And we took all that aggregated knowledge together, and as Aseem said, you always have to start with one. And um, know our first one was one just within the last six months. And when we explained to the customer Hey, what can we offer you together? They jumped on top of it, and that one lights up the imagination of the Microsoft field in our field.

Bill: And we’re able to go to customers that are like for like, and solve that same problem for them. And then the flywheel has begun. That’s a little bit of the journey. And again, it starts with technology and maybe a better way to put that is the unique value on the problem that you’re solving and who solves what problem and who doesn’t. And then that forms the framework for what I’d say is a healthy partnership.

Aseem: If I might add to that. The other nuance to consider is that the first couple of customers you get are more product-led sales versus go-to-market motions. And I remember the engineering team in Azure, leaning into partner with Bill, as we talked to, I think it was Casepoint if I remember right. Leaning in and saying, look what must be true and what must we do in order to make the product deployment super successful for Cause on Azure. And I think that’s an important nuance to call out because the go-to-market, the sales motions are not established because they’re not there.

And so engineering leading in, making sure that, you’re around 24/7 in a services world to make it successful, to get mission critical applications on the platform. It is really the first, I would say P Zero step to success. Once you’ve got that nailed down, then I think, you know that you’ve got a product that works.

And then I think things follow on the go-to-market and the sales side and the partner programs kick in. But that, that I think mindset of product-led sales is important to begin with.

Matt: Yeah, I agree. I agree with that. Go ahead Bill.

Bill: I was just going to jump in because I don’t want to lose this point here. It’s super important and it is a nuance. Aseem is right. We spent a lot of time with really great product folks and engineers inside the Azure organization. And that’s where it should start. If you haven’t solved it there, then it the solution probably won’t get off the ground.

What I learned along the way is that to know the difference between a product sale and a field-led sale and know where you are, as Aseems’ pointing out in that journey, because, the, I think the failure mode here that ought to be avoided is sort of assuming that since you’ve solved the product part this equation with the products in an engineering organization that, “automagically,” the field will know what to do And so there is a sort of a transitional period where you have to move you maintain and continue to invest in your product relationships with these organizations and then know that there’s more work to be done and really accessing, and frankly, making it’s brain dead simple for the field to be able to bring to their customers if it’s even remotely complex, most fields will stay away from it.

Matt: Aseem, you, you’ve got a wealth of experience in these areas, helping, outside companies navigate Azure. What are your perspectives on these topics?

Aseem: Yeah. Great. Going back to that model of, I think once you’ve gotten your first five, I’d entertain that next step and say, okay, you’ve gotten the crawl now let’s get the walk. And how do you go from five to a hundred? And in that sense, I think it’s important to probably pick a few industries to target. And like Bill mentioned, make it super easy to succeed in that industry and you probably have some proof points for the first five, right? So, let’s pick media and entertainment as an example that Bill, you were on, and say, okay, great. Now let’s make every seller in the field, who is a media seller, equipped with what they need to go sell. And it includes battle cards, compete cards, and really compelling case studies of others in the industry like you use Qumulo and here’s why they found success and here’s how it was successful. So that way you start to nail that industry and it’s almost like you’ve got to establish your birthright in that industry and say, Hey if this is an industry that I’m going after, I won’t fail. And every opportunity will be Qumulo plus Microsoft opportunity. So once you’ve established those set of hundred customers, then I think you can say, okay, what are the adjacent industries that are then easier to go into, so then you’ll go from a hundred to the next hundred and beyond.

There is an interesting element here on, even within the hundred, as you’re chasing those, given that these are highly involved technical sales, you’ve got to bet a little bit on the sellers who are very tech savvy, who are forward-leaning and who want to take a long-term bet. Which is not just how do I meet my quota in a quarter, it’s almost like, how do I make my year? Which is, you know, the next year and the year after that. So, I think a colleague of mine put it very well when I was at Microsoft — you’ve got to bet on the heroes. And I think you’ve got to curate the global black belts, as we would call it within Microsoft, which is an elite group of sellers who would be incentivized to not just sell, but also make sure that the deployment is done and there’s high amount of customer satisfaction. So, you’re shepherding, not just the sale, but also the customer experience.

Matt: I love the bet on the heroes, and I think you’re right. Finding these champions that not only are aware of this better solution, but they really want to deliver differentiated value to their end-user customer. And they’re technically savvy enough and they listen to their customer enough to want to be the hero on solving a problem better than they can solve it. Otherwise, which gets into an interesting question, and this kind of issue varies from partner to partner, but oftentimes, certainly in the case of the cloud service providers, they also have their own first-party solution that’s similar to your third-party solution. So, Bill, I think that’s probably an area that you’ve had to wrestle with before. I know that we’ve had across a bunch of our portfolio companies, including the likes of the Snowflakes and Amperities but how has that journey been for Qumulo?

What lessons do you have that you’ve learned there?

Bill: If you put yourself in a customer’s shoes and there is a first-party service that meets your needs and it’s great. And it’s owned by the platform player, you should have a working assumption that will continue. And look, we do everything in service of customers and if I were them, I would probably do the same thing. That’s the easy button. So, understanding that to start off with, I think is really helpful. I meet a lot of fellow CEOs that are like, Hey, why isn’t the cloud provider selling my stuff more — they ought to do that for me. And maybe they should, but that’s just not realistic. So, the approach that we’ve always taken is, Hey, I have to be 10 times better from a starting point against whatever sort of neighboring first-party service might exist. And then I have to continue to be better. And that kind of mentality will solve a customer’s problem in a unique way that’s powerful for them — meaningful for them — and it will enable the platform player to want to take you seriously and move forward with you. I’ll sum that up, have to be wide-eyed, you have to start with the customer, and you frankly just have to be fundamentally better.

One of the things that Qumulo offers is cross-environment capabilities. You can run Qumulo on Azure. You can run it on AWS. You can run it on GCP and you can run it in your private cloud. That’s just a capability that any first-party service cannot offer and that’s strategic for customers and it’s powerful.

Matt: Yeah, that’s a really great point. One of the things sometimes the earlier stage. Get a little bit frustrated with and caught up in is you referenced certifications before and becoming a pro in the preferred program and complying with a whole bunch.

Kind of rules and at some level I think we all get this that, the big companies need to know and be able to be competent in the third-party solutions are recommending. But sometimes that feels like a little bit, being lost in the desert a bit for a while before you’re seeing any of the fruits of your labor in terms of customer wins.

Bill, can you speak a little bit.

Bill: Yeah, and this is I think a really good topic. It’s something that we’ve learned a lot about as we’ve done this over the years. Putting myself in the shoes of the platform player. You’re lending your brand to a smaller company, and you want to have some level of credibility that you’ve vetted it and that you’re willing to put your customers on it, so I completely understand the notions of the certification programs. The other thing is for the big platform companies, there’s hundreds or thousands of ecosystem partners and they need some way to scale that organization or scale those interactions. So, it’s all understandable. I think the mistake is to believe that all those enabling steps are results. The results will come from the customers. And so, if you go through the. 15 step process, and then you’re done. And then you wake up one morning and go, okay, now, great. Where’s all the sales.

I think you’ll wake up very unhappy that day. If you deploy some amount of resource to make sure that you’re partnering well and working with these platform players and the way that they like to work with, but at the same time, making sure that your organization knows their job is to add value to customers and win customers, hearts, and minds.

That is really the best practice, so ones necessary, but not sufficient. And you really have to do both.

Matt: I think we’re getting a little bit more now into some of the, the nuts and. I’m curious in order to build beyond the necessary pieces, the programs and stuff. What’s the cadence and the resources that you would recommend, it doesn’t strike me it’s enough just to have a quarterly business review between the CEO of the company and some key partner leader at the other company, there’s got to be more resources and weekly daily activity going on in the field.

Bill: Hey, Aseem. I’d love to hear jump on this one.

Aseem: I can’t answer the resourcing question, Bill, that’s you, but to the stage of engagement, especially when you’re trying to get your first couple of customers or your first five, I think quarterly is not enough because what typically happens is both teams get together, they decide on some activity, people go and work on their own and they come back in, in quarter and realize, Oh we’ve barely made any progress, even though they’ve been at it. I think, to the extent of setting mini-milestones in saying, Hey, what needs to happen in six weeks, and treating it as a sprint is something that’s really been worthwhile. And what I’ve seen work in really successful cases where you’ve got a customer, you’ve got a three-way essentially between the customer, the company like Qumulo and Microsoft. Because then all three parties are equally involved in all three parties want to make it successful. That’s the recipe for success. And I think faster turns to get to outcome. Is where I would put my bed on versus a quarter cadence. I think once you graduate from first customer to fifth, yeah, you can go to the quarter, but I think the first two or three, like it’s gotta be like a 6-week type of sprint.

Bill: Yeah. I agree with that. I, I would just say in general more is better. You have big company and small company. And one of the expectations of a big company, they know that they might be slow because it’s, there’s a lot of people and organizations to manage. And so on. The expectation is the small company would be fast. That’s one of the reasons why I think some of these larger companies like partnering they learn from startups about how fast things can get done. But that also implies, as the emerging growth company, you have to live up to that you have to be fast. And by the way, our cadence is more like weekly with our partners, if not more frequently. And the idea is to be incredibly responsive as Aseem said, have a lot of turns really quickly because that’s what generates momentum. The thing I wouldn’t do is defer to the larger partner, just simply run at their cadence because they have a lot going on. And um, you know, you might find that in the conversations with them, they’re like, geez, you’re slow. And you’re like, no, I’m working at your cadence. And they go, that’s what I mean.

Matt: well, hey, let me, just really briefly touch on. To two topics that kind of come from the same thing, but from different angles, which is the, how do you approach getting to the contract and the economic alignments in these partnerships, which sometimes feels like it drags on forever. But then conversely, how do you build genuine people-based trust relationships, which I think is the more enduring thing cause inevitably, both sides of these partnering relationships are going to have moments where they surprise and exceed expectations, and there’s going to be disappointments and falling short of expectations.

Bill: Oh boy. Yeah. At least in the first point we, that’s probably another podcast, but look, it’s hard. The large organization has really long contracts that are very often, to Aseem’s point, not Built in is bespoke way. In other words, you look at the contract, you’re like this isn’t even written for me. And so that takes a fair bit of work. At some point, there is some element of holding your nose and, making sure that you’ve protected your organization, but moving on, which is I’d say some science and a lot of art and maybe even some legal fees.

I did model my daughter’s cell phone contract — my personal contract with my daughter about how much he cell phone, using one of these.

It was very one-sided, and I modeled it off of one of these contracts, not actually from Azure, but somebody else. But maybe more importantly on the other point around. Building trust in these relationships because you’re right, Matt. You hope for there to be nothing but a lot of success, but you also have to figure in day-to-day life something, at some point it goes wrong. and I would just say the single most important thing is transparency. It will be okay if you communicate well and you’re transparent, you do the right things. I, my sense is that any organization has seen plenty of challenges and know that you can work through them as long as you’re both sides are being transparent. Where it really breaks down is if somebody is worried about scaring somebody and, tries to sweep something under the rug that almost never ends well. So, if I had one word, it would be transparency.

Aseem: Yeah, I echo that, and we used to call it, embrace the red internally, which means that look, if you’re embracing it, you can own it. The only way to go is up. And, we have this notion around let’s not have watermelon metrics, where they look green on the outside, everything is great, but you ask two questions and it’s remaining red

Matt: Great. Well, hey, this has been fantastic. I really want to thank Bill and Aseem a lot of great nuggets of insights there. And I hope that this is helpful for other folks as they’re looking to partner with the big cloud service providers and other partners in the innovation ecosystem.

Matt: Thanks again, guys.

In this episode of Founded and Funded, partner Aseem Datar sits down with co-founder of Spiceai.io to talk about the power of building tools for developers, the difficulty of integrate AI (SpiceAI is making this easier for developers) and moving from a big company to building a startup.

Transcript below

Welcome to founded and funded, I’m Erika Shaffer from Madrona Venture Group. Today, partner Aseem Datar, sits down with founder Luke Kim of Spice AI. Spice is a new startup focused on helping developers integrate AI into their applications. The founders Luke and Phillip LeBlanc recognized that in order to integrate AI, developers need data engineers which is a high bar for startups, so they set out to build tools to alleviate this requirement.

The first implementation of Spice is focused on their blockchain data platform. This public platform, enables developers to access Ethereum and smart-contract datasets, like Uniswap, across real-time and historical data with a single SQL query.

Spice plans to extend the platform to other blockchains, like Bitcoin and Binance Smart Chain (BSC), and to traditional time-series datasets. It will be available in beta next month.

Aseem and Luke dive into the power of building tools for developers. They talk about the transition from working at a well established company to building a startup and the different skills that are necessary to make that successful and how AI is something developers want to leverage to build intelligent applications – but it’s not easy.

You can learn more at Spiceai.io

Aseem: Hey, Luke. Thank you so much for joining us today. I’m really excited to have you here and get the opportunity to chat.

Luke: Thanks, the same. It’s also good to be here. Yeah, I appreciate the warm welcome.

Aseem: Awesome. Awesome. What part of the world are you at?

Luke: I’m in Seoul, South Korea. And yeah, fun fact about me. The first thing a lot of people ask me about is my accent. I was born in Korea, but I grew up in Australia and spent most of my childhood and University there. And then came over to the U.S. about 12 years ago, spent the last 11 years working out of Seattle for Microsoft, which is of course where we first met.

Aseem: Yeah. It’s amazing that I was just recollecting and counting backwards. I think we’ve known each other for over 10 years now, which is amazing, and I think in cloud world, its dog years, so it’s a great to be reconnected.

I’d love for our listeners to know a little bit more about your background. How the journey at Microsoft? What did you do at Microsoft and what team you’re on? Any exciting projects you worked on? So, it would be great to start there.

Luke: Yeah. For sure. As I mentioned as that 12 years at Microsoft. Even before that, I had done internship and I was part of the student program. But in the last two years, I was in the office of the Azure CTO reporting to Mark Russinovich, which there which is just an amazing experience. I got to build an incubator there where we worked on a whole bunch of interesting projects.

Some have been released. Most of them were open source and some have yet to still be. Just an amazing opportunity. You got to work with people across Azure, the industry, a bunch of customers, and what comes from cool stuff. So, three years before that worked with Nat Friedman, who just stepped down as the CEO of GitHub, and built a bunch of the services and infrastructure behind both GitHub and GitHub actions. Along with a product that we had called AppCenter, which helps develop his build and operate mobile app mobile applications. And yeah, so most of my career been building tools and services to help developers build software be more productive.

Aseem: Well, that’s amazing. I think what a stellar career at Microsoft, working on two big products, of course, GitHub and then Azure. Tell us a little bit more about, what excites you. I know you talked a lot about like working with developers but give us a little bit more color on what is the exciting part, tell us a little bit more on the project you work at Microsoft.

Luke: Yeah, for sure. There are two things that come to mind. When I think about developers in kind of that track, I just think that it’s an amazing way to scale. If you think about the leverage that you have, you can, if you’re a developer, you can build an application. You could build that overnight, and that could affect millions of people, right?

That is there’s very few other places in the world where you could spend a week building something and affect so many people’s lives. I think. Now if you take building tools and services for developers to help them do that, you almost get this double leverage. I just think that’s an amazing way to contribute back to the world.

That kind of leads into the second thing, which excites me is, I think at some point we’re all asking the question, like how can we contribute back to the world? How can we contribute to people? For me this like amazing set of leverage through helping develop is help other people. I’ve been privileged enough to be in my career at Microsoft in positions where I’ve been able to do that and lead teams and build teams. I was literally hired out of a university as a grad hire. It was probably just a year into my career. I was working on visual studio, and I was working on the debugger like some deep level stuff. At the time we were just transitioning to Windows. And that’s a new architecture. So, we didn’t have the tools to write that software productively.

Those are set of tools called ‘system internals’. That helps you do diagnostics and write software. Mark Russinovich at the time, he had just had his company acquired by Microsoft, a technical fellow who had helped write the tools. I was like this grad hire and I was struggling with writing the software.

And so, I emailed him, and I said, “Hey, Mark, are these tools available for this new architecture? Because it would really help us run the software.” He replied, “No, sorry.” But it turns out that I was a little bit bolder and so I replied, and I said, “Hey, if they’re not available, would you be willing to give me the source code? And I will go and convert them and put them over to this new architecture, because it would really help me out my job.” And he said, “that’s an interesting idea.”

At the time, only just a couple of people in the company had access to the source code. So, he emailed me back. There was no Git at that time. So, he literally emailed me, “see files” and I started doing this port and I would email them back to him. I did a couple of tools and within about six months, a bunch of people across the company were using these tools to build windows.

That’s how we first got to know each other. From that point on, I was working. This is internal source for the rest of my career. For like the next 10 years, I was like a pseudo developer or manager for these insistent tools.

Yeah.

Aseem: How wonderful and I think it’s amazing to be a part of such a large enterprise yet have the personalization and the drive. Two things that you said stood out for me. One was the ability for you to work on scale projects. You talked about the two for one kind of thing. When you build tools for developers and when developers build solutions for the world, you get the double benefit and the second thing, which you also highlighted, right? Finding these white spaces, right? These spaces of opportunity that can then be converted into products that many people can use, which is the example that you cited working on working with Mark. So, coming back to what we were talking about, you had a wonderful journey at Microsoft and a wonderful career. You’re moving mountains. Tell us a little bit about this thing called DAPR that you worked on, where we’d love to understand what that was and how that has bearing into what you’re doing today.

Luke: When I first went and joined Mark’s team I said, “what should it work?” And he’s like, “well, there’s a couple of people in my team. They’ve been looking at this runtime that helps develop is build distributed applications.” Because as we’ve moved to the cloud and not just the cloud, but the cloud and edge, these applications have become more and more complex.

So now before you had an application, which was just on a single machine, 10 years ago, now you’re dealing with all these distributed pieces across the different servers, different infrastructure. How can we make that even easier and benefit developers so they can just focus on their business application?

What DAPR does, is it abstracts away a lot of the complexity. So, if you just need storage key value, you instead of going and having to, not only choose a technology if they must choose Reddis or Cosmos or some other store, but I can also just use a simple abstraction over HTTP rest APIs to store my state and focus on my application.

That’s what DAPR does, it provides a whole bunch of these building blocks in terms of state. It has Pubsub, it has Secrets Management, it has a whole bunch of these like basic things that you need to build a distributed application. It lets you just focus on building an application and not doing all the distributed systems behind the scenes.

At the beginning it was called Codename Actions. They’d spent maybe I think, two months on it at the time. I came in and we built an entire team around that and built up this project and released it probably within the first three months.

So, we released like a private preview of it. There’s a whole bunch of lessons from that, one of the things was that it was radical, it seems basic right now, but it was a radical idea when we first did it. We got a lot of pushbacks both internally and across the, I wouldn’t say necessarily across the industry, but a lot of developers ask, like why do we need this?

We just pushed through; we keep kept working on it. After about two years, when we developed it out, we had so many people come back and some of those same people are like, why do we need this? To say, this is a savior. This helps us be so much more productive.

I think as a founder you always go through these moments at the start where you’re doing something just a little bit crazy, just a little bit out there. A little bit beyond what people have as their normal mindset. And you’ve got to be able to see the vision and push through that.

What I say to some of the guys on my team, though, at the very start, they were getting a bit down because, they’re getting not as much of the attraction that they thought they were going to get. Look, I said to them, this seems like a crazy idea now, but wait, in two years’ time, some of these people will be telling us that it was their idea all along.

It was just so funny. Like two years after that we had people come back and say this was like our idea like we believed in this from the start. People will come around. If you truly have something. Yeah, I’ll say, in terms of the fanboy movement, was you just think this is just a small open-source project, but I had the opportunity to be in a Satya a staff meeting, and Satya knew about DAPR and he was supportive of the project. That was just super cool. Like we were part of these massive organization. I think it was like 140,000 people at Microsoft. Yet Saatchi, like he knew about DAPR. He knew how it worked and he knew how it makes life better for developers.

We were able to present that to him. One of my fanboy moments was, I was able to debate with him how we could make applications better in a staff meeting. So yeah, I thought it was cool.

Aseem: No, that’s awesome. I remember being in that meeting and I remember the red side but that’s a story for another day. Hey, as you, one thing I think our listeners would love to hear from you is, a great time at Microsoft. You’re on a meteoric rise as far as career is concerned, but then I think eight months ago you left to go build this thing called Spice. ai. Tell us a little bit about like, how you thought of the opportunity? What you’re seeing in the world.

What are the challenges that developers face today? You talked about building applications for the future, which is a theme. We call it as ‘intelligent applications’ over here at Madrona and we have a thesis around it. We’d love to hear from you on your, in your own words, on what challenges are you seeing today? What are the core value prop that you’re building forward and how do you expect to change developers’ lives in the future?

Luke: Yeah, that’s it. There’s a lot. That is a great question. In terms of transitioning from a big company to do a startup, it’s a journey, right? If you’re in a big company it’s, especially today in tech, it’s such, I think a great opportunity to you. You have the ability, have all these resources at your disposal to really go make a massive impact. Of course, you also have a bunch of the safety and security in terms of just regular paycheck and all that goes along with that. Stepping out into going and doing like into a bunch of ambiguity, a bunch of unknown, and doing something really takes I think, you to be intentional and make a choice about what direction you want to go in your life.

Coming back to what I said about this stuff, to me, you get to a point in your life where you want to decide, like how you want to contribute to the world. For me, I always knew, I had done some stuff like a long time ago, 12 to 13 years ago. I knew for me that the way I wanted to contribute back to the world is in like leaps of innovation, like in ways where we can really move the needle.

To me that was like doing a startup and doing my thing. Honestly, there was a lot of fear that we had to work through to get there. There’s a great book. It’s called Feel the Fear and Do It Anyway. That was the theme. It was like, yeah, it’s scary. At some point you got to choose how you want to contribute.

For me that was leaving the safety net of a big company and going, doing. Yeah, if you can find people to go do it with, I think there’s also something special about the start of a startup. I’ve heard this before in that it only ever happens once.

Like you can never go back and redo like the startup something, it’s like the start. And I think experiences are also even better when they’re shared. If you can go find a couple of your friends or a couple of people that you really respect, you can go and do that style of this startup and do it together and have a lot of fun. I think everyone should experience in my opinion, at some point in their life.

Aseem: That’s great. I’m going to, I’m going to bookmark that reference to that book and make sure I read it. But more importantly, I think what you said is as along the lines of finding your own tribe, right? Like finding the people that you deeply respect that you’ve worked with in the past and who would be allies in going and solving those tough challenges. So, coming to understanding the developer space like a space that, we’ve looked at from close quarters, both at our time at Microsoft and even now, like what challenges are you seeing in the ecosystem? How is Spice. ai positioned to think about solving those. Maybe I think I know the story, but it would be great to learn about how the idea came to you what you experienced in your time and how did you formulate this thinking around building Spice .ai?

Luke: Yeah. So, in terms of in intelligent, like you mentioned intelligent applications and you have a whole thesis around that. Well, it all really ties together with developers. I think there’s going to be a few challenges going forward. One I think a lot of people in the tech space already know, there’s just so much demand for skills. I think it was even back like 2018. I remember Saatchi, one of the conferences saying that more developers were hired outside the tech industry then within the industry. So, people who are lucky in banking or insurance or whatever, there’s more developers outside. That was just a, it was like an ‘aha’ moment to me, an amazing a statistic because if you follow that to directory, then this is going to be more and more demand for software, more and more demand for developers.

If we are going to meet that demand in the world, to make all the software and to make all these applications that people need. Then we’re going to need help to build software. To me, what I saw or both at Microsoft and across the industry, and in my own side projects, that it’s still too hard. One, I think to really be productive and build a software. But also, if you think about that demand for software, we’re going to need help. What I believe is that help can come from AI because AI is not a magic bullet.

It’s not like some magical thing that’s going to solve their problems, but what it does do, and it does do well, is it helps. It basically you write a program that runs program for you, right? So, like you could take a hundred developers in 50 years and do like a whole bunch of image processing and just normal code.

Or you could build an AI model that will go and write that code for you. So, what I believe as a thesis going forward is that intelligent applications are not just going to be a nice to have but are going to be required. It’s going to be a necessity in the next 5 to 10 years to not only compete, but just meet the demand of how much software that we need. Because we’ll use AI to help build software as developers, it’s still too hard to leverage AI, to help build applications and help you build a better application faster.

It’s really the thesis of the company. We want us to go out and solve that problem and solve that gap. It’s honestly a difficult problem to solve, but if we can help developers build better applications faster using AI, then I think it’s going to not only help developers but help us thrive in kind of this world going forward.

Aseem: That’s amazing. Look, and I think we share that worldview. Making lives easier by, by being able to create software at a faster pace. That’s more intelligent and that can self-sustain to a certain extent. I think one of the things that you said that’s most interesting is how you get the scale effect, right? If you’re able to empower developers, then you’re helping them write software faster, which means that you’re getting to the meat of the problem and the solutions faster in whatever industry. There’s a saying where every company is a software company and I see that true more and more in today’s day and age, especially because of distributed computing, because now you have access to all these tools, memory, compute, storage that otherwise you would you’d be hard pressed to get. So that’s a big point of view that I wanted to highlight.

Luke: It’s just like one anecdote on that in terms of scale, like we saw his company and they had spent three years building this algorithm to basically do routing on the edge. Then after the three years, someone came along and said, “Hey, I wonder what would, happen? Just as an idea, what would happen if we tried goodie and our AI model to see if we could do this right. Could we get Cyprus?” They spent like three months on that AI model, and they got better performance. They got like a ten for one scale by applying AI to the solution. Now, of course, like I said, AI is not a magic bullet, but it gives you an idea of just how much faster you can develop some things then just a traditional approach.

Aseem: Yeah, that’s cool. I think that sort of ROI is amazing from a developer point of view and who wouldn’t want that. So, following up on the Spice .ai conversation, tell us a little bit about, potential customers you’re talking to, any lessons learned so far, and maybe just give us a little flavor of the use cases that you guys are finding interesting, especially with Spice .ai at this early milestone.

Luke: Yeah. So, with this Spice the idea behind it was to help developers build these intelligent applications, not just do AI. I think there’s a ton of AI companies out there and we’ve made a ton of progress. But if we can use some of the techniques that we’ve really matured as an industry of the last 10 years, things like I really felt, Dev Loop, we live preview, so the idea is can we take some of these things and help develop is built in an intelligent application, faster, better.

If you think about, what you would do as an intelligent application, like what is the intelligence? For us, it boiled down to basically a decision engine as the main core thesis. If you think about what you’d want an AI to do in your application.

Well, we think it’s to help make decisions. If you think about a couple of use cases around that, we had a food delivery application and Uber Eats and they basically had to, when they got an order, they must decide about what delivery driver to route that order to, like what’s going to be the best. What’s going to get it to the fastest. That’s a decision. When they first started, they just use people, they just hired people. They would get orders and route it to people. Route it to these drivers. If you could take a decision engine and put that there, you can get the order, have AI decide fast, which is the best way.

There are so many different cases like that that you can choose. Everything from even just like retail trading, these days really took off with the things like Robinhood. But deciding like what stock to buy. That’s a decision, right? We had a case around, retail shops where you order online, and you pick up in store. Well, what store do you want to pick up that item from?

Right often it’s not actually the store that’s closest to you. And so, it’s a decision. What we started to really realize is there’s a lot of interesting cases where you can build an application where you’re making these intelligent decisions. We started really working on that, but of course, as a startup, you must really focus and where we started a small team, three people. What we found is there’s quite a lot of interesting use cases right now in the FinTech space. You can imagine there’s also a lot of decisions to be made. So not only just like trading decisions, but for example these days especially in the blockchain space, distributed finance there’s many different exchanges that you could, send your order to.

That’s a decision, right? What exchange is the best exchange throughout my order through. So, there’s quite a lot of different cases around this.

I think going forward into the future, especially around like web three, if you have things like, well, should I interact with this person or not? Does this new token, is this going to be a scam or not? And that’s really what we’re going after right now.

Aseem: Yeah, that’s amazing. I think the way I’m thinking of it is you’re really building out an intelligence platform or a decision engine that can have vetted applications all the way from FinTech to retail. Shopping to food delivery. It’s amazing that, so much of these decisions in the future can be thought of as intelligent and automated, which then saves, whole lot of logic writing as well as like individual point solutions. Which is what, what makes it very exciting. I’m privileged on behalf of Madrona to be a part of this journey with Spice.

So, thank you for that. We couldn’t be more excited to see these come to life soon. One of the shifts gears a little bit, Luke, and talk a little bit about, the journey of the startup and as you’re going through building Spice .ai, like how are you thinking about, building a team? Are you thinking about, any early lessons that you’ve seen and learned so far, that would be good to share with the people?

Luke: Oh, so many. One thing, I think just coming from big company to a startup, that a lesson that we learned, it’s a completely different mindset. So, what makes you successful in a big company often is the ability to be very responsive and very reactive, right? So, a problem comes along, and you go back and solve it, right?

We must respond to this thing in the market, then you go solve it and you can have a lot of success that way. Often the opposite, you must go make things happen. Customers don’t come to you, like you’d go out and make them. In fact, we hired an AI ML engineer. One of our first hires, the way that we found him is I literally went through Reddit posts, and I looked at people who had posted good analysis of deep learning frameworks at the time in the area that we were looking at.

I was like, this guy is he’s obviously written some really good content. I just DM’ed him. You’ve got to as a start, just go out and chase down these opportunities and make things happen. So, I think as a startup founder, that’s one thing that you really must switch your mindset from.

From having stuff come back for you, these opportunities show up and just going in and making things happen, chasing us down. So, we started really building this thing in July last year. When we first started, we knew this general thing that we wanted to help developers, but we had no idea how at all, like we literally had no idea.

So, we started 1st of July, by the end of July, we’d build a prototype. We just liked different ideas and we started showing that prototype around. We didn’t expect to do any funding or early raising at all. We thought we’d probably go for a year before we would have to, or even want to do that.

But we shared around and gelled with different people. We were excited, we have some awesome investors on board. People like Mark, for example. Nat Friedman as well as on board. Thomas Dohmke, the current CEO of GitHub, and these guys all really believe in the same philosophy, which is help developers help people. To what happened was in terms of the fundraising journey, people started asking to invest in. Once they saw this thing and so we decided to do a very small pre-seed round in about July/August and that I’d never raised before. Like I did everything from scratch.

Go find people who are like one or two steps ahead of you. So, we were like doing a pre-state. So, we found people in the seed round and a series A round. Who’d just been through that. Cause obviously things change and got advice for them. So, I have a good friend whose David Siegel, who’s a CEO of Glide Apps, which is like a No Code App platform solution. He’s two steps ahead. In between a seed round at the time. So, he gave me so much advice on how to do it. So as a founder, go find these people to do that. The second thing is, really lean on like a lot of VCs that are investors will come to you and say, look, how can I help?

Take that help, lean on it. So, with Madrona early on and with you, Aseem, it was the same. Also, Tim there at Madrona were just so amazing. So how can I help? And I just leaned, I said, look, this is all the ways you could help.

We need help hiring. We need help figuring out like this direction. We want to decide here and how should I also think about fundraising? Like how much money should I raise, for example. I think that support even for when we first did our PR and the kind of announcement about our raise. Madrona did so much help.

I had no idea how to do a PR thing. I had done some PR at Microsoft, but we had a team. The way I did PR at Microsoft was I go to the PR team and work through them. Madrona really helped us do that. So overall, it’s just it’s been a really been an awesome partnership together.

We have, I think, 33 investors all up and we fit them all into this small 1 million rounds. We were offered a whole bunch more money, but we turned it away because we really wanted to focus on solidifying what we’re building first, before we took a whole bunch of money. I would say, there’s a whole range of people who get really involved and help you out and people who, I’ll give you my money and you go, you run with it type thing.

So out of those 33 investors, I think Madrona just helped us out a ton and it’s clear to see who’s on point and on their game. Tim and you, Aseem, have really helped. So, thank you.

Aseem: I couldn’t be more thankful, thanks for the warm words, Luke. But I do think that you’re right about, it takes a village to go create something amazing and I’m so pumped to be a part of the journey. I’m positive that, we do build something amazing and you’re already on the journey. You’re two steps ahead in your own words on this journey. So, it’s amazing to see the progress that you’ve achieved in shadow such a short amount of time.

One last question before we let you go is, what’s your take on the Seattle ecosystem? We’ve talked a lot about the last 10 years, the growth that Seattle has seen, the Northwest is experienced with, the Amazon, the Microsoft, the Google, being in the backyard and becomes the cloud capital of the world. How are you thinking about hiring? How do you think about adding talent? Then any comments or observations of the Seattle ecosystem.

Luke: Yeah. I often think we tend, I’m not sure it was also developed is like this, but we tend to think things in like binary, like it’s this all bad. To me, I often look to think about things in hands, not ours. To me in terms of a lot of the world going to remote, I think that there’s benefits, obviously, remote there’s also benefits of coming together. I believe, Brian Armstrong from Coinbase has written about this quite a lot, it’s in terms of his transition from going to a remote first company. In that the reality is the chances of getting top talent.

The chances are that they’re going to be within, a 15-mile radius or whatever of your HQ is obviously very low, not true. So, if you want top talent, you’re going to have to go chase them around, chase them down across the world. At the same time, there’s a huge amount of benefit to like human connection, and really being together in the same place. I think there’s so much innovation and creativity. I think we’re moving to a world where you must chase down talent, wherever it is, and enable remote work at the same time, have opportunities for people to get together. So that might be like offsites, coming together once a quarter, meeting people in different places. In terms of this yellow tech ecosystem, I totally believe that it’s cloud capital.

If you want to, if you’re in distributed systems. Also, AI. There’s a whole bunch of AI stuff that happens in Seattle. So, if you’re anywhere in that space, in Seattle, it’s a great hub to do that. So, it’s like you have remote teams, but you also bring them together. I think Seattle is an awesome place to bring your team together. Also connect with other people in that ecosystem that really has deep experience in both cloud and AI.

Aseem: So cool. So cool. The way you think about it. I think what’s mostly energizing is there’s distributed systems, there’s distributed development, and now there’s distributed teams. So, you, I think you summarized it well. Talent first, and I think everything else follows, which is a great mantra to live by.

Hey, I’m so excited to have heard from you and, being a part of the Spice journey obviously, people know where to get ahold of you. I know, you’re hiding in the area and beyond, to anybody who wants to reach out to Spice. I think the best way would be to communicate with you and fill that.

Luke: Yeah, absolutely. So, if you just go to Spice ai.io/team. Sorry, slash career, that is careers. That’s where you can see our job postings. You can also just grab us on Twitter, LinkedIn, all the usual places as well. Yeah, so Phillip and I co-founders, you can search us out.

We have a tech crunch article out there, which also gives a little bit of background on what we’re doing as well. Just search for Spice .ai on Tech Crunch.

Aseem: Awesome. Hey Luke, it’s been an absolute pleasure talking with you and we’ll look, I know, you release updates about Spice on GitHub and that’s another place where developers can go to check you out and see the progress you’ve made. We’ll look forward to continued dialogue with you soon. Hoping to see more awesome news from Spice shortly.

Luke: Yeah, absolutely. Yeah. So, our project, the underlying engine we really believe is build up with the community. We are developers. So, it’s all opensource. You can go grab it, all free, and you can run it yourself. One thing, I just want to encourage founders as a last note is, if you take that story from the start where I was a grad hire, there was a technical fellow, you don’t often like just go email these people. I’ve emailed Saatchi before I’ve emailed all these people. Like I would say, as a founder, you’ve got to go do those things and don’t be afraid, be bold, right? So, if you must go email like a CEO, you must go reach out to somebody, go do that. I really encourage you to go make things happen. Don’t be afraid to be rejected or whatever it is, even if you think you don’t, you’ve got no writer to do this because of your position or whatever, just go after it.

If you email someone like you could lead into a great, like for me and Mark, led into 10 years of development together. Yeah. I just encourage you to go through those things.

Aseem: Awesome. Wise words, Luke. Thank you so much for making time out of your busy schedule. I know you’ve got a business to go build. Thank you so much for taking time.

Luke: Thanks, the same. It was a pleasure. Thank you.

 

 

 

In this week’s Founded and Funded, Madrona Partner, Chris Picardo, sits down with Terray Therapeutics founders (and brothers), Jacob and Eli Berlin as well as Terray’s lead data scientist, Narbe Mardirossian to talk about the power of bringing together transformational wet lab processes with ML and AI to speed drug development. Terray announced their $60 million Series A which Madrona led (and Chris wrote about here) in February of 2022. Terray Therapeutics brings together novel methods of creating vast amounts of data around small molecule disease targets, and then applies ML and AI to map the interactions between these molecules and the causes of disease. This is a company at the intersection of innovations between life and computer science and this was a great conversation. You can listen below or on any of the podcast platforms.

This transcript was automatically generated and edited for clarity.

Erika Shaffer: Welcome to Founded and Funded I’m Erika Shaffer from Madrona Venture Group. On this week’s Founded and Funded, Madrona Partner, Chris Picardo sits down with the team leading Terray Therapeutics. That is CEO and founder, Jacob Berlin, CFO, COO and founder, Eli Berlin, and Head of Computational and Data Sciences, Narbe Mardirossian.

Madrona first invested in Terray right before the pandemic hit and all business, especially wet labs, shut down. And we are excited to lead their 60 million Series A. Terray Therapeutics brings together novel methods of creating vast amounts of data around small molecule disease targets, and then applies ML and AI to map the interactions between these molecules and the causes of disease.

Based on research from founder, Dr. Jacob Berlin, the company was formed by brothers, Eli and Jacob to bring an interdisciplinary team, that works together to bring life saving new drugs to patients in need. This is one of Madrona’s intersections of innovation companies. And without further ado here is their conversation.

Chris Picardo: We’re thrilled to have the Terray Therapeutics team on the podcast today and also super excited to lead their Series A, having been a big participant in the seed, which all got announced recently and super excited to chat with Jacob, Eli, and Narbe on all things Terray Therapeutics and combining the wet lab with really cutting edge machine learning. So, before we jump into it, I’ll kick it over to Jacob, Eli, and Narbe to quickly introduce themselves.

Jacob Berlin: Thanks so much, Chris, it’s wonderful to be here today. It’s wonderful to be working with you and the team at Madrona and to be building a fabulous company here together. I’m Jacob, I’m the CEO and co-founder here. My background is all in science and chemistry. I started that all the way back in college at Harvard making small molecules and looking for applications to them, how we could make better drugs.

At Caltech, I also worked again on making new molecules. After a postdoc at MIT, I had done a tremendous amount of design and development of molecules, but also recognized that the way we were doing it as a field was slow and pretty hard. We’ll hit those themes a lot today.

I went to do a second postdoc at Rice University. Down there in Houston, I worked on nano materials and trying to ultra-miniaturized things and dramatically speed up how fast we could do things. That’s really where Terray started to come from, I really built it out here at City of Hope, where I was a professor for eight years. My lab there worked at the intersection of nanomaterials and synthetic chemistry. It’s there that we began the process of building the technology that became Terray. Over six and a half years, we built it before spinning out the company and I’m excited to tell you and the listeners all about it throughout the rest of this podcast.

When we launched the company in late 2018 and raised the seed round in early 2019, I left my tenured job to be here full time. Since then, it’s been a tremendous time with an amazing growth throughout the company. We’re seeing fantastic science and outcomes and excited to talk about it today and wonderful to be here.

I’ll turn it over to Narbe and we’ll close with Eli.

Narbe Mardirossian: Hey Chris, it’s great to be here as well. I’m excited to talk to your listeners. My name is Narbe Mardirossian, I’m Head of Computational and Data Sciences, here at Terray. My background is in machine learning and quantum mechanics, quantum chemistry, that’s what I got my PhD in. After I got my PhD, I moved to Amgen working in the therapeutics discovery organization and small molecule discovery on the computational side, of course, working on physics-based models, machine learning models, and moving all of our on-prem compute to the cloud. So I moved here in November of 2020 and have been here ever since.

Eli Berlin: Hey, I’m Eli, the Chief Financial and Operating Officer here at Terray. My background is all in finance. I did 10 years of private equity and growth equity before joining Jacob to co-found this business back in 2018 and I’m super excited to spend the time with you today, Chris. So thanks for doing this.

Chris Picardo: That’s great to have all you guys on, and I’d say it’s been a pretty awesome time already working together. Narbe remember when we hired you and how thrilled everyone was. So that’s exciting now to all get together. Before we dive in, I think it’s just interesting to note that, Madrona first invested into Terray right before COVID hit.

And I remember that round closed and then the world went into lockdown for two years, in some cases it still is. So it’s been a great time working together and I know you guys have had a lot of creative solutions of how to work through COVID and we to hit a bunch of those today.

It’s been amazing to see the progress you’ve made even with a bunch of unforeseen headwinds from the world in the way. So it’s been fun to be along the journey. Before we jump into the detail, I think it’ll be fun, Jacob, just to talk about how you decided to form a company around the academic research.

You’ve been at City of Hope for awhile and you decided to formerly spin it out and bring Eli into the fold. I’d love to know the motivations behind that.

Jacob Berlin: Thanks, Chris. It has been a wonderful journey and it’s always an interesting question. When is something ready to be commercial? Personally I’ve always been really fascinated and driven to have my work have impact on people in their everyday lives. I’ve been fortunate, as I mentioned in my background, that I participated in the development of a catalyst that is used across the world and saw compounds that I made in my first post-doc become part of preclinical drug development, and then had a lot of my work in my second post translate into start ups. So I’ve always had an eye on having my work have a real impact. I think the way to deliver solutions to make people’s lives better is through commercialization.

This is a project that honestly on day one, when we wrote it on the proverbial napkin, we were like, “Wow. This one is obviously a company someday. We’re building a technology that allows us to screen hundreds of millions of molecules in minutes and record their interactions with the causes of disease. Of course this is a drug development technology. That’s what we should use it for. That’s where it goes. This obviously doesn’t belong in academia because academia is not the place to develop a bunch of proprietary IP protected secret items that have to be developed, commercialized, scaled up, manufactured and sold.”

So from day one, I called Eli and was like, “man, this idea is so cool. This is going to be a company.” Eli is my closest friend and also harshest critic. He was like, “that sounds fantastic, Jacob. But does it work?” And I was like, “nah, it doesn’t even exist, but it’s a really cool napkin and we’re going to get after it.” And so my other co-founder Kathleen, who is still leads a lot of our R and D and development here today got going on it. We started working on it at City of Hope. And, as I told Eli, and I’ll tell everyone, science is hard and it takes a lot to make the machine work that we run today.

We spent six and a half years painstakingly developing all of the technology for it. Honestly, all along the way, I’d call Eli to talk about something and he’d be like, “does it work yet?” and year one, it was like “a little bit” year two is “yeah, most of it is looking pretty good.” Year three is “yeah, we’re starting to apply it” and by year six and a half, it was, “yeah, it totally does. We’re ready to roll. it’s reading out your interesting solutions to problems in academia. It’s ready to go provide solutions in the commercial space.” At that moment, we put our heads together and we launched the company, and we haven’t looked back. I think it’s been a fabulous home for the technology.

We’ve scaled tremendously. We’re using it to develop medicines to treat immunology disorders and bring therapeutic benefit to patients. I’ll kick it over to Eli for his side of that journey, but that’s really how it went from idea to company.

Chris Picardo: Yeah. Eli, before you jump in, I’m interested that you and Jacob are brothers. Obviously being the harshest critic is a nice natural role to inhabit. Then, at some point you guys decided to get together and actually build the company and backgrounds are a little bit different from what you’ve done professionally.

So it would be fun just for everyone to hear your perspective on the story and what has been like building the company together with your brother.

Eli Berlin: Absolutely! Look, for me, Terray is an exercise in, if you can’t beat them, join them. I did a decade of private equity and investment banking before co-founding Terray as I mentioned and the sort of short story here is that Jacob’s the smartest person I’ve ever met, and he’s disarming in his humility, and he rarely shows excitement for any of his achievements.

There’s this one time Jacob was in high school. So, I was in the middle school, and he tells my parents that there’s an award ceremony at school that we should go to. So we go, and he’s in like shorts and a t-shirt and it turns out it’s the Year End Academic Awards. And Jacob wins legitimately every single award that is given that night.

And, at one point, they tell him to stop going up to the podium and back to his seat. And, he had presented it to the family, like whatever, no big deal, I would have been like, I would have probably sent out invitations to my extended family. And, so for Jacob to show excitement about something is a really high bar and Terray, as you mentioned, was totally different from the start.

He was excited about it from day one. He used to say to me, we should make this a business. It took them a really long time to get it to a point of maturation where we could make it a business. I just always felt that Terray was an extraordinarily rare opportunity. If you believe that, you live and you die, this was one worth doing.

I believe that Terray deserved to exist as a commercial venture. And that for all the hard work in academia by the founding team and for all the promise, it deserved a chance. I’m convinced now four years in that the opportunity ahead of us is really extraordinary to transform drug discovery at an incredible scale.

So I think, it’s been there just aren’t that many opportunities in your life where you can work on a business with purpose where the end goal is advancing human health, do it with your brother and do it with novel technology. And so it’s been an extraordinary journey. As regards working with Jacob, there’s no, I just don’t think there’s any way to replicate the durable trust that we have being brothers.

It just drives us extraordinary efficiency. He talked about me being his harshest critic. That’s probably true. And I think the level of direct and honest communication that we can have because of that trust is totally unique. I also think, I’m not sure anybody listening to this would know, but we are very different people and have very complimentary skills and very separate responsibilities here at Terray.

That’s worked really nicely with a ton of mutual respect. And look, he’s my brother. So I know that before we go pitch investors in the morning, he should have breakfast and we make sure that’s on the calendar. So you know it runs the gamut.

Jacob Berlin: We are different. If Eli had won those awards in middle school, he probably would have rolled into the awards in a three-piece suit. But everything Eli has said right there is true. The durable trust, ability to build it together and work in complementary areas has tremendously accelerated the growth of Terray. We’re super excited to be here.

Eli Berlin: That’s just for listeners. That was like Jacob’s funniest joke ever. I’m also much funnier as the younger brother. And Chris, to your question, I don’t know, we’ve learned a lot over the years, but I think for me, this has been about confirming the thesis.

Jacob’s really, truly brilliant. He’s a tremendous listener. He’s a great strategic thinker. Terray is really novel and working together with purpose, is just a once in a lifetime opportunity. I can’t say enough good things about the opportunity to be on this journey.

Chris Picardo: I’ll say just for myself, it’s been fun working with everyone. I can second all of those things that you guys have both said minus the stories from high school. I want to ask you Eli one more thing before we jump into the platform, because I do want to talk a lot about the platform and the Teray difference and how we approach the world.

But I think one thing that’s really interesting for everybody in this kind of hybrid space between tech and software and traditional wetlab as teams are coming together, how do you join a company, or in your case, build a company where you might be the one with significantly less of the technical background. It obviously helps to have a brother who’s a world-class scientist and can talk to you about chemistry, but you and I have talked about this a bunch and I’ve seen your learning curve. I’ve had my own of right trying to just ramp up. How do you think about approaching that?

We talked to lots of more, less science-oriented people who’d love to go join a company like Terray, and they’re worried about the science side of it. So, what was your approach to moving up the learning journey there?

Eli Berlin: Yeah, I think there are two answers. I think it’s really hard to join a scientific organization from the outside without a scientific background if you’re trying to diligence the science, right? If you’d asked me four years ago, when we started this. How good was the science on a relative basis?

I would have said I spoke to a few folks, gray haired folks who spent a long time in drug discovery and development. They were excited about it, but I couldn’t underwrite the technology. I think that was a benefit because it gave me the leap of faith that, I just trust that Jacob is brilliant, the science is novel, the IP is there.

And so I do think that’s a hurdle. How do you get around, underwriting the technology as you’re thinking about joining a company? And what I would say is, I think you can learn a lot talking to a handful of folks in industry and get yourself over the hump. I think the second piece of it is, at its core, Chris, the technology is extraordinarily complicated.

When you get down into the technical weeds, which you’ve suffered through in a few board meetings, it is deeply complex, but you don’t need to know that. And I think that’s true of any Company like ours, you don’t need to know much about those details. You need to know about what it can do, the why in the technology. And I think it’s been a steep learning curve, but one that I’ve been being grateful for where. I understand the differentiation. I understand the competitive positioning and I understand the opportunity that’s in front of us. And none of that relies on figuring out the linker strategy for our core platform. That all is just transferable from one industry to the next.

For folks who are first and foremost technologists thinking about crossing over into a biotech business. I think it’s an extremely exciting opportunity. I think it’s one where you can work with purpose to advance human health, which is totally unique and gives every day new meaning.

I think there just shouldn’t be that hurdle, because I think it’s all imminently learnable, even if you don’t have full command of every one of the details.

Chris Picardo: Yeah, that resonates a lot with me personally, certainly on my own learning journey. I’ve felt that in board meetings, as we dive into the details. I think everything you said there is relevant for thinking about these opportunities. It’s also a perfect segue into kind of back to Jacob and Narbe talking about Terray’s approach itself. I think that the first question I want to ask there is, Jacob, when you think about small molecule drug discovery as it’s been traditionally done, give us the 30 second version of that, and then the slightly longer version of why and how Terray really is changing the game on the core platform.

Jacob Berlin: Yeah, thanks, Chris. I think we’ll spare the listener today the full deep dive into the specific chemical reactions and linkers and the chips and all the various technical pieces that make our whole enterprise run. But it is, I think, really important to spend a moment and think through the current canonical, small molecule drug discovery.

Just for context, when we talk about small molecules, we’re really talking about medicines that can be put in pills, taken orally and are convenient. They’re the bulk of what people take as medicines today. When we use the term, we’re separating them from antibody therapies or things like that. But for small molecules, the first problem is always (and, really, for any drug discovery the first problem is) figuring out the problem. So the biologists work really diligently to find the cause of disease.

What could be a protein or an RNA molecule that plays a role in developing this disease or perpetuating this diseas? We call that ‘target ID’, and it’s a target because it’s the thing we want to then go solve and fix. So at that point, you go into the drug development process where you need to now start to find your starting points.

We call these ‘hits’, which are molecules that do something of what you want to do with that target. So your end goal may be to say fully turn that cause of disease off, not change anything else in the body. An example of this end goal might be a drug with very nice safety thresholds that you can take a big pill of. You can, in some ways, think of those as like antibiotics. We all are familiar with taking those giant pills. They kill the antibiotic, the bugs, they don’t hurt you. You get better and feel great.

The question is, how do you get there? And so we get there by starting with these starting points called ‘hits’, and they typically do one of the things you want to do.

They either interact with that cause of disease very strongly. So they go and stick to it. We call it binding. Or they impact some of its behavior, but they may be lacking in some other property that ultimately you need to be able to put it in a pill and take it orally and have it work. Then you hit the phase of drug development we call ‘hit to lead’, where we’re taking these starting points and we’re turning them all the way into basically nearly candidates for giving to people. So we’re optimizing all the other aspects the molecule needs to do. It needs to be able to be taken by mouth. It needs to dissolve, it needs to go into the bloodstream. It needs to get where it needs to go into the cell where it needs to go. It needs to interact with the target where it gets there. There all these layers that you work through as a drug development company. Then ultimately the last stage is of course, ready for clinical testing, which involves manufacturing, reproducibility, toxicity testing, and a larger scale and trying it out in humans.

Today that process is typically quite long. These are often, ten-year plus development timelines, and it’s also really hard. We’ve done great as a human kind improving human health and developing therapies, but there are also thousands and thousands of causes of disease that we don’t know how to fix.

Also countless failures along that road, where only a small fraction of what we try to test on people actually works. There’s huge opportunity to deliver better solutions faster.

Chris Picardo: So that’s the traditional approach, Jacob, and you laid out the timeline and how long it takes. I’d be curious to hear how you reformulated this problem at Terray and how we’re thinking about solving drug discovery in a totally novel way.

Jacob Berlin: We sit at like an amazing moment in time with the revolution in the biology capabilities and the ability to discover these causes of disease. So things you may have seen or heard like Crispr, siRNA and Gene Knockout have just continued to unveil opportunities to create drugs, but the chemistry side hasn’t kept up.

There’s not an ability to look at enough molecules and diverse enough molecules, fast enough to really address that explosion of opportunities and bring those timelines down. And ultimately be able to go from discovery to therapeutic in a much shorter and much more reproducible fashion. That’s really at its core Terray’s bet.

We’ve built technology that lets us actually measure far more molecules than any other technology out there. We can actually go and build the loosely drawn map of chemical space quite quickly at enormous scale. Then I’ll kick it over to Narbe, because the next piece is that even with all of that throughput, even mapping and measuring hundreds of millions of compounds, there’s still an infinite amount of chemistry to go through.

So, filling in more of it and knowing where to go next and taking an efficient route through this infinite space to find the solutions you need, the proverbial needle in the haystack, we turn to AI and ML tools and computational tools that are the right fit for the scale of data we work with, to allow us to make the next set of compounds that go iteratively back and forth from large-scale chemical measurement to computational prediction and back to the wetlab measurement of that.

That’s what lets us really compress the timeline and deliver therapeutics where otherwise, we haven’t historically. So I’ll turn to Narbe to say a few words about that complimentary side, where we used the design to accelerate the wet lab throughput.

Chris Picardo: This is such an interesting point. You’ve told me before drug development, isn’t just an algorithm problem. It’s a data problem. So talk about what you mean by that and how that is actually executed on a day-to-day basis.

Narbe Mardirossian: Drug discovery is both an algorithm problem, and also a data problem. But I think first and foremost, it’s a data problem and probably the best way to motivate this is that, big pharma sits on tremendous sizes of data sets. But what you really need in drug discovery is the iterative capability which Terray has built and is expanding.

I think, a lot of these models that are very novel today, neural networks and beyond like they only work when they have the proper data, proper amount of data, proper amount of clean data to seed it, to feed it. Historically, it doesn’t really matter if you use traditional models such as partial least squares or random forest.

Like all of these are going to perform probably equivalently on datasets of the size of ten or a hundred or a thousand, which is really what you’re looking at for a specific target that you’re trying to drug therapeutically. The promise of Terray is really the ability to generate data quickly, iteratively, and at scale and at the quality that’s needed to power regressors.

That can truly optimize chemical space and to take a step back and hit on why this is such a tremendous problem. It’s truly a needle in a haystack; the size of chemical space is something like 10⁴⁰ or 10⁶⁰. It is a tremendously large space that you’re trying to explore. You really do need the help of these modern machine learning approaches, plus the data that’s fed into them to traverse that space efficiently. If you look at the traditional process in big pharma, it’s always going to be iterative, but you’re generating about 10 to 20 data points a week.

That’s just not enough to be able to power these models that are improving on a daily basis, and you’re improving because the data is being fed into it. So I think it’s certainly both, you need the data. Only with the proper amount high-quality data, will you be able to unleash the algorithms that are present in probably all aspects of our lives today.

Jacob Berlin: Yeah, I think Narbe is spot on there and we’ve seen this opportunity unfolded across so many other industries that I think everyone listening is probably familiar with. What you should get recommended to shop for on the internet, where are you going to go to dinner, and how to get there. What you’re going to watch a Netflix. All of those algorithms probably started out not that accurate, but they all drew on iterative data sources that are enormous, millions and millions of people clicking on things or driving places or buying things or watching things.

So we have that opportunity in drug development as well, if we can provide the data sets. Drug development is an even harder problem than all of those probably. The key is to be able to be a little bit or even a lot bit wrong the first time, but have a dataset then that gets you going back on track fast and to get better each and every round and run those rounds fast enough.

So that’s really where the compression in development is. It’s where the Terray differentiation is that we build and measure large enough that we can get our algorithm going, get the model going, and then rapidly refine it to really incredible accuracy and precision. And that’s the Terray difference.

Chris Picardo: Yeah, this is a point that I’d love to go one layer deeper on, which is that I think another way to frame that is in these broader machine learning problems, Terray closes the loop on the data side. Not only do we create a ton of data, we then test that and model that, and then we can validate it again with actual physical chemical data.

And I go back to Narbe for a second. When you think about that versus maybe the pure algorithmic approaches are purely in silico approaches out there, I looked at, get your perspective on the importance of being able to close the loops on the models and move as quickly as we can on the data side.

Narbe Mardirossian: Yeah, closing the loop is absolutely essential. Honestly it would be any computational chemists or machine learning scientists dream to be able to develop these models, make predictions, and actually see those predictions tested in real life. That is something that’s different from the traditional process, because, you only have so many shots on goal a week and you need to make, 10 or 20 compounds and you don’t really have that opportunity to make millions of compounds literally in a week and test them.

I think absolutely one of the benefits of Terray is the ability to iteratively benchmark and improve the models that we’re building. I’m not talking about only about machine learning models. Machine learning models are great for learning from experimental data, but even physics based models that are very popular these days in computational chemistry and other realms, these can also be improved by learning about how the predictions are right and wrong. So the ability to have this feedback loop is absolutely essential. Truly, I believe that Terray is probably one of the only places where you can actually test and hypothesize and, validate your hypotheses iteratively within weeks or even days.

Chris Picardo: Yeah, the power of the platform is pretty immense. I think one thing I wanted to ask too, and this goes back to the question I asked Eli earlier, say I’m a computational scientist or machine learning engineer, and I’m really curious about either these types of problems or joining a company like Terray.

What makes this data so special, and why would I get so excited about working at Terray and building the models that we’re building?

Narbe Mardirossian: Yeah, I think Terray is an exciting place for a variety of scientists and people with technical backgrounds. I guess, let me start with computational chemists and machine learning engineers — one, I would say the molecular data, we have at Terray both in terms of the quality and the scale is unparalleled.

Nowhere will you find datasets of size 10 million, hundred million. Where you actually have high quality, believable data that you can model. I’d say from, in those disciplines, the ability to model data and use the feedback to improve algorithms consistently, whether they be machine learning based or physics based is it doesn’t exist anywhere else, but, molecular data, isn’t the only type of data that Terray has.

We have tons of opportunities for data scientists. All of our readouts for molecules come essentially from images. Just the path from going from raw images to processed photometries to the output that is then used for hit discovery, and machine learning models and compchem, is full of custom algorithms that we’re developing every day at Terray.

And I think, beyond that for data engineers and software engineers, the amount of data we generate is tremendous. This year we’re gearing up to hit 20 to 30 petabytes of raw image data, and that doesn’t even include the processed data. So there’s tons of opportunities, whether from the domain, domain specific fields, such as compchem or machine learning, all the way to data engineers and software engineers that Terray offers.

Chris Picardo: Yeah, we talk a lot in Madrona about the combination of machine learning and life science and the wet lab. And I think what’s amazing about Terray is not just that you guys have actually built that and are running it on a daily basis. It’s that pretty much inside to raise. You’ve talked about Narbe.

Absolutely. Incredible data science software in engine engineering, machine learning challenge going on daily, that itself could be right, like a data science focused company. I think when we talk about integrating those two it’s pretty awesome to see how Terray like really fully, is as a data science and wet lab company and that you can’t really pull the two pieces apart.

Narbe Mardirossian: Yeah, absolutely. I just want to add that one of the, to me one of the beautiful parts of Terray is the fact that the wet lab and the computational side are fully integrated. That is also not something you see very frequently in in drug discovery companies. Typically the computational team is viewed as like a support function where they’re contributing maybe 10-15% to various requests or projects. But here, without the computational side, the wet lab would not be able to function and vice versa. So I think this 50/50 integration is truly what makes Terray an exciting place to work for both computational people and wet lab people.

Jacob Berlin: This one will probably make the listeners chuckle if they are in the field at all. We built this from the wet lab side, initially. We wanted to see if the technology could be built and we could make the core of our technology, which is these little chips, the size of a nickel – the world’s most ultra-dense microarray. If we can make them and we can put the compounds on them and we can measure these interactions, which is where our raw data comes from, as Narbe said, it allows us to measure hundreds of millions of compounds.

In the academic lab, that’s where we started and we wanted to see if we could get the chemistry to work. Could we get the microscope to work? Could we get the chips to work? Can we get all the parts of this interdisciplinary process to work? The first time we made it work, we had no data people working with us at all. We were like, oh man, we just measured like a hundred million things, what should we do with that? Maybe we’ll put it in a Excel and filter for the top hundred and then see what we can do with that. Then the next day we went out and looked for someone to help us on the data side.

Now, of course, there’s been many years of working at the intersection of data science and experimentation. It’s staggering, and it’s a cliche that’s true. Working with an interdisciplinary team makes all the difference. We see stuff go back and forth all the time where the data team makes predictions out of the data or identifies things in the data that changed the way we do the wet lab side and vice versa.

Terray wouldn’t run the way it does without the data team, the chemistry team, the biology team, the automation team, the production team. All basically sitting together and talking together each and every single day, and it’s what makes it so special here.

Chris Picardo: That’s awesome. I get to witness it pretty regularly and have been down to Pasadena many times and seen the lab myself. It’s pretty great to just see it in person and see it all come together.

Eli, why don’t you also briefly tell us about the Series A and our big fundraising milestone that we just achieved and who’s been part of that journey.

Eli Berlin: Yeah, I appreciate it, Chris. So we’re super excited. We just announced our $60 million Series A which brings our equity capital raised to date to just over $80 million, including our seed financing. One of the things that’s been tremendous about this journey has been the partners we’ve had in the venture community.

That includes you guys at Madrona. It includes Two Sigma Ventures, Digitalis Ventures, KdT Ventures, Goldcrest Capital, XTX Ventures, Sahsen Ventures, Greentrail Capital, and the folks at Alexandria. As well as a whole host of other folks who’ve supported us along the way. We’re super excited about this moment and the opportunity been supported by the Capitol to massively parallelize our processes and throughput to deliver for patients in need.

Chris Picardo: I want to throw it back now, as we’re starting to wrap up to a couple of broader questions that I’ll pose to everyone, so feel free to jump in and take them as you see fit.

I think the first one is, and this is one that will probably resonate with most people listening, building companies it’s really hard. I think building companies that have complexity on both sides, the wet lab side and the machine learning side and trying to do both of those things is potentially even harder or at least more complicated.

What’s been the biggest challenge so far the biggest set of challenges, maybe Eli and Jacob that you guys have faced, and how have you thought about those?

Jacob Berlin: Chris, that’s always the question that keeps you up at night and everyone asks you what’s the hardest either retrospective or what’s coming next, that’s the hardest. We think about it a lot. I spend a lot of time on it, I don’t know if the answers will be exciting, cause they’re probably the same ones thematically that everyone who starts a business that builds at this interface faces, which is hiring the team. Building the expertise around the table, just always takes a lot. It’s always a tremendous lift to find people who are mission aligned, vision aligned and passionate and, perform at an excellent level.

We’ve been really lucky now to build a team of 50 with a seasoned management team with biotech expertise, as well as ML computational experience. We’re joined by a wealth of expertise now on the business development side, the drug development side, the computation side, but it took a lot to bring that team together and be at this remarkable moment.

I think alongside that, personally going from academia, or I guess it could come from anyone. Back to the napkin sketch; the appreciation for what scaling and industrializing that discovery is like. It is, I think, harder than you would guess on day one, to be able to run the exact same process and a high number of replicates at incredible velocity and scale and know it’s right every single time. We’ve done that, but it took a number of years to really dial that all in. And so I don’t think that part should ever be underappreciated. Eli, what would you say?

Eli Berlin: It’s funny, Chris your comment really resonates. It is so hard to build a business. I think back to my days in Private Equity, where, I’d come into the board meeting and have a bunch of thoughts on what needs to get done and I used to walk out of the meeting and go back to San Francisco and it’s so hard. Execution is so hard, but it’s also got enormous joy to it, because you get to work with people day in and day out, you get to create work that is worth doing, and it’s all worth it in the end.

I think for me, the two are recruiting and for us, the recruiting piece is about, attracting candidates and helping separate signal from noise. There’s so many AI drug discovery companies out there, and we’re really different, right? If you believe that the data unlocks the opportunity, we’re the only ones with that capability in the whole landscape. It’s a competitive ecosystem out there, and it takes a lot to recruit folks and get them interested in our technology. We’ve been quiet up until a few days ago. And we have a lot of teaching to do, when we meet folks who are interested in Terray.

The second piece is, Terray is a massively interdisciplinary Company so we’ve got chemistry, biology, machine learning, and computational chemistry with robotics and automation that go to make the engine deliver for us and ensuring cross-functional communication and collaboration is done with excellence and precision to deliver is really hard. It’s taken a lot of work to get us to where we are, and we’ve got a lot of work to go from here, and those are the two for me.

Chris Picardo: That all resonates with me. I t’s been fun to watch you guys solve those challenges and we’ve been along for the journey for part of the way, and we’ll continue to be along for the rest of the way. It will be good to keep working through these together and I’ll go right to my last question.

I like to ask the couple of people that I’ve done these podcasts with this question. If you roll the clock forward 10 years and you’re looking at what we’ve achieved, at Terray, what does the big vision look like? What is success, and what will that look like when Terray is at scale and started to execute on a bunch of this stuff that you guys set out to do?

Jacob Berlin: Yeah, I picked my career, Chris, because the big vision is making people’s lives better. It’s allowing everyone to live healthier, enjoy more. For us, what does it look like for Terray? It means Terray is a drug development company at scale, working across multiple different types of diseases and delivering therapeutics to patients faster.

It is unlocking all of the opportunity in that biology revolution with a chemistry revolution, where we can really go from identifying causes of disease, to people enjoying medicines that make them better reproducibly, reliably, and quickly, so that’s what we’re building.

Eli Berlin: That resonates. I think about the opportunity to build a company is a tremendous opportunity, but the opportunity to build a company where the end result, if we’re successful, and when we’re successful is more therapies to patients in need, faster. It’s an extraordinary vision to be a part of.

It really resonates across the company. Everybody who works at Terray does so with purpose and with mission as their number one. It’s an opportunity to work with world-class science and, deliver the next generation of therapies to patients in need. It’s really a unique opportunity and a tremendous goal as we push everything forward here over the next handful of years.

Chris Picardo: I don’t think I could end our conversation on a better note than that. So I wanted to say that, for us at Madrona, it’s been really amazing to be part of the journey and we’re super excited to continue to be part of the journey. I know it’s a busy time, so I appreciate you guys taking the time to chat with me today and share about Terray for really one of the first times ever. This has been a real pleasure.

Jacob Berlin: It’s a delight, Chris. There are two things along the journey that really make it wonderful. One is the science and seeing what we can achieve and move human knowledge forward. And the second is the people. And so we’re, privileged to work with the people we work with here, you, and the rest of Madrona ecosystem supporting us and the rest of our investor ecosystem. We just want to thank you again for having us today and delighted to tell everyone about Terray.

Erika Shaffer: Thanks for joining us for Founded and Funded. If you want to learn more about Terray, they can be found on the web at www.terraytx.com. So that is, T E R R A Y T X.com. Thanks so much for joining us and tune in, in a couple of weeks for another episode of Founded and Funded.

How do you join a company and lead from the day one? And how do you do that when you come from a completely different work experience than your startup? Trevor Thompson of Terraclear had a 14 year career in the Navy, including a decade as a Navy Seal, and is now president of AgTech company, TerraClear. In this episode of Founded & Funded, he talks to investor Elisa LaCava about the opportunity for companies to hire experienced veterans and how the company is executing on it’s mission to make a farmer’s life a little bit easier with their rock picker robot.

Trevor also talks about the DOD SkillBridge program – https://skillbridge.osd.mil/ which companies can use as a way to access talented veterans.

This transcript was automatically generated and edited for clarity.

Erika Shaffer: Welcome to Founded and Funded. I’m Erika Shaffer with Madrona Venture Group. And today I’m super excited to bring Trevor Thompson, who is the president of TerraClear here together with Elisa LaCava one of our investors. TerraClear is an agtech that is automating one of the worst jobs in farming, rock picking. Rocks rise to the surface each year and farmers most often have to pick them up by hand. And these are not small pebble size rocks. TerraClear’s end to end solution uses artificial intelligence combined with robotics to precisely map where rocks are in the field by size, and then remove them with the precision robotic implement. Today there is a farmer in the cab and tomorrow it is a fully autonomous solution to this age old problem. I’m just going to turn it over to you, Elisa, take it away.

Elisa LaCava : Trevor, thank you so much for joining us today. I’m really excited to have you here.

Trevor Thompson: Well, thank you for having me. Always exciting to talk to anybody with Madrona and talk about TerraClear.

Elisa: I was realizing today, we’ve worked together now for almost two years exactly. You’ve been at TerraClear for a few years at this point, and I’ve been able to join in part of the TerraClear story now for the past two. One thing, I would love to share with the rest of the world is how you got to TerraClear and your amazing background.

For those of you who don’t know Trevor, and you should, he has an incredible history, spending, I think was it 13 or 14 years in the Navy seals? 14 years as a Navy seal and, moved over to civilian life and joined TerraClear, directly after your time of service.

There’s so much in there, how did you think about the transition into startups after your service? What were you looking for? And then, critically for other veterans or soon to be veterans who are listening to this, what are some things that worked well in your kind of learning journey when you were thinking about your next steps?

Trevor: Where to start? I guess, I grew up here in the Pacific Northwest and was really focused on a career of service from a young age, just instilled in me from my family and my parents who had either served in the military or served in medical professions. So, I ended up attending the naval academy with that intent to serve in the Navy.

I was fortunate enough to have a couple of years at graduate school at Oxford, which was kind of a 180 in terms of cultural experience, and then went right back to basic seal training. That’s where I spent the next, more than a dozen years.

In that experience, it was exciting and challenging and what I think the highlights for almost anybody in that kind of environment, is the people and the team. You have this combination of an incredible peer group and talented people, that I got to work with from all different backgrounds, combined with hard problems.

When you can galvanize a group towards these hard problems, that’s really, I mean, it’s addicting, it’s fun and exciting. So as circumstances change in my life and kids started getting born and it was time for us to come back home and leave that exciting, fun world that is not super conducive to having multiple children.

Once we made that transition, that’s really what I was looking for again, that pattern of, I want an incredible team and I want a hard problem. You get the most personal growth from that and the most satisfaction. If you had asked me five years ago, if I would be operating farm equipment in central Idaho picking up rocks, the answer would obviously have been no. but I think—

Elisa: It’s more than that, but we’ll get into it!

Trevor: Yeah, exactly. It’s incredible. So, what I saw in TerraClear as I met the early team was just such a passionate team. A problem that is massive and has been completely underinvested in, and this recurrence of rocks that arise each year in farm fields.

Talk to any farmer and they will immediately smile and make a reference to how bad this job is, but that is such an opportunity to solve one of these problems that most farmers have honestly given up on. There’s a wide variety of solutions, none of which have really answered the call.

Now we’re at a point where some of the breakthroughs in robotics and machine learning technologies allow us to solve this problem in an elegant way. We can be the solution in a giant market. You combine that opportunity with a team that’s done it before and has, immense experience and talent focused on this problem. It’s really fun.

Elisa: I love hearing you talk about the parallels between your life in the military and your life now, and what you love the most, strong teams working on tough problems. How do I replicate that kind of an environment, but just pointed in a different direction? I would love to hear; how did you find TerraClear?

I’m talking to other veterans and soon to be veterans who are listening, what resources did you use, how did you use your network or what was most successful for you in finding what you wanted to do next?

Trevor:

Originally, I had lunch with Mark Mader, who’s the CEO of Smartsheet. I was really excited about the culture that I’d heard about at Smartsheet and him [Mark] as an inspirational leader. As I continued to talk about other folks, somebody said, ‘oh, you got to meet Brent Frei, who was one of the founders of Smartsheet’. So, I talked to Brent, and he said, in a very Brent way, ‘Smartsheet’s really cool, but you’ve got to come see what we’re doing now it’s even cooler’. That was TerraClear, and they were in those early days. So, I met with them early in TerraClear’s period, and got to know the team and grow with them as I was transitioning.

That was the experience there, I’d say, in terms of advice to veterans, there’s almost nobody that is going to be more of an advocate, for you when you come out. Because I think veterans who have been successful in different sectors, they really understand the upside there clearly. Right? So, they’re willing to invest in folks that they see that enthusiasm and humility and talent and say, I know that this, gal or guy can, can do something great, we just got to put them around the right kind of people and get them started on the right foot.

Spending time with those real advocates was incredibly valuable. Some of those came, into new networks that in Seattle were really valuable, like the Dartmouth network or the Harvard business school network, or the Madrona network. Where you meet one of these people, who’s an advocate and then they kind of spin you into a wide variety of different folks.

If I could just add one point to that, there’s two sorts of people. I think that you meet when, you’re transitioning from the military into, some other sector, and that is the ones who kind of shrug and say, “boy, this is really interesting. I’m not really sure what to do with you”. Then there’s the different, group that sort of says, “my God, you could have an incredible impact here. Like we could use somebody that has these skills”.

I think generally you get the people that have more experience and have seen the importance of team dynamics and energy and problem solving and operating within ambiguity. All of these, kind of cliche traits that you hear about. I think they really see those. They’ve seen them manifested and so they see the opportunity and the upside there. So, finding those people is important.

Elisa: It sounds like Brent was one of those people and you two immediately connected. One of the amazing things about your TerraClear journey, Trevor is you’ve like had this meteoric rise. You’re on the senior leadership team of the company in the span of a few years. One thing I would love to learn kind of in that first year of working at TerraClear, just a bit more about that transition.

How did you stretch your leadership capabilities or how did you really lean into the leadership capabilities you had already developed at the military? What served you well, versus what other areas were you trying to grow in most?

Trevor: That’s a good question. I think oftentimes one of the things you learn, or at least I learned in seal training. Is just how we ended up limiting ourselves more than almost any other external factor. That has a lot to do with, self doubt and negative talk and all these other psychological elements, but the ability to overcome those is actually really empowering and have the ability to say I don’t know everything.

I had come from a world where I was often. I was often, theoretically, in charge and responsible, but was not an expert in any piece of the equation. So, when we’re solving hard problems, there was somebody that knew the intelligence much better. There was somebody that knew the tactics much better, et cetera. So, I was pretty comfortable being honest with what I knew and didn’t know, which I think is really the first step in that quick growth period. Being around a team that was awesome, to put it in the simplest terms, that allowed me to grow really quickly in that area and allowed me to ask some pretty stupid questions that was really empowering.

It allowed me to take these really well-developed skills, like team organization, and goal setting and prioritization and all those things and account for some of the gaps, that you might encounter that you would expect and things like finance. Right? Areas that I did need to grow quickly. Having advocates on the team that understood my role was valuable and helpful.

Elisa: That’s amazing. So fast forward to TerraClear, you jumped into a company that has a really dynamic strategy. On the one hand we’re building, rock pickers, this is like metal and steel and, a real physical implement that you attach to, skid steers and different pieces of equipment on a farm. And then also there’s this amazing data and mapping component AI strategy would love to hear a little bit about the evolution of the company and what you think about, this world and ag tech and smart ag tech moving forward.

Trevor: The evolution of the company really started as a problem. Oftentimes in agriculture, what you’ve seen over the past decade is some of the lag on adoption has been the result of solutions looking for a problem. Fortunately, we really started with the hard problem.

I mean, physically in the field, picking rocks by hand, Brent had an epiphany that said, ‘good Lord, like there’s all this stuff that’s been automated. These huge elements of agriculture, harvesting and spraying and seeding and tillage, they’ve been really heavily automated. And then there’s these things that have been left behind that we all have to do as farmers’.

Solving those problems is really exciting. That’s where it started, and the solution really initially came in two areas. One is we’ve got to be able to identify this problem over large acreage. Farms are increasingly bigger and bigger with a smaller or equal labor pool. So, we need to identify the problem and then we have to solve it with a high degree of precision, which allows for really modernized farming, where you’re not digging through the ground each time, you’re just removing the rock. So that’s really where it started, and we had these kind of two parallel efforts to figure out what is the right solution for this, and we continue to iterate on those.

Elisa: I’ll give a fun plug. Earlier this year, at one of the board meetings, so TerraClear has offices in Bellevue, Washington, and out in Grangeville, Idaho. We had a board meeting out in Grangeville and a field trip day, and I had the distinct honor of driving a skid-steer that had the picker attachment on it.

As someone who didn’t grow up on a farm, never driven a skid steer in my life, I was able to get in by myself and I picked up what was it, Trevor? Like 15 or 20 large rocks in the span of two minutes. It was like driving this, Go-kart basically, which the skid steers are fun, but the beauty in what you and the team have created is this incredibly intuitive, very easy to use heavy duty system that is super fast and quite honestly like really fun.

Trevor: I think the important detail that you’re omitting is that you picked about twice as effectively as somebody had farmed for 40 years, right after you, so that was the really exciting part.

We’re really proud of the fact that it can be used by anybody on the farm.

So, a nine-year-old or an 85 year old can use this thing and really contribute effectively not to diminish your performance that day, but that’s really important for us is can we get this to be fun and easy because you take a job that was really the worst job on the farm, or certainly up there and make it the first job that somebody wants to do on the farm.

That’s a big transition.

Elisa: Right! I mean, because you think about some of these eight-inch rocks or 10-inch rocks, they are heavy. You can’t just manually pick those.

Trevor: It’s so fun obviously to get this in front of customers and, at different farm shows and all, but the face of farmers, when they see it just suck in a 300-pound rock, in an instant is pretty extraordinary. I mean, that’s, that’s a rock that is going to take a lot of time to figure out how to get out of there and potentially a lot of back pain as well. So, it is really, every single time we show this to somebody there’s this incredible reaction. That’s really fun.

We just sold this to a farmer, and he said, ‘unequivocally, the best thing that I’ve seen created in agriculture in my lifetime, just the most exciting kind of new thing’.

That is one of these, the ability to create something that didn’t exist that people didn’t think really was possible it’s not even a tweak on an existing product, it’s actually a fundamentally new approach to this problem. That’s something that we feed off of quite a bit.

Elisa: I also think, one of the unique aspects of building in ag tech is, your customers, farmers have these natural, really tight windows when they can be productive and do work on their fields in between all of the things that they do from prepping the field to seeding, across all of these stages over growing season.

I would love to hear a bit more from you on, what are you hearing from farmers in terms of top pain points that kind of surround their natural farming cycles and how does TerraClear fit into that?

Trevor: Those cycles are tight, and risk is really another way to think about that, and we think about it in terms of risks. Just to take a snapshot of, Brent’s family that, when he was a child, was farming under a thousand acres with the same number of people in the family fast forward to today and it’s almost five times that with the same group. So, they just don’t have the luxury of spending time on a field solving problems like this any more. Everybody is feeling that pressure. I mean, there it’s every sector of agriculture, similar to every sector, really across the economy. Really acute in agriculture is how do we then solve these problems with a higher degree of efficiency?

For us the answer is we can solve this problem in a way that reduces your risk during those critical periods. So, whether it’s planting or harvest, these are tight windows where missing a single day can cost you a percent in your overall revenue for the year and that’s considerable. Removing the rocks ahead of time, in a way that’s comprehensive, reduces that risk dramatically. It’s a relatively straightforward ROI for a farmer.

In terms of our actual solution, we’re accounting for that tight window by creating an autonomous tool that allows you to pick in a much wider window. Historically you turn over the soil, you go pick as many rocks as you can, and then you seed and you just kind of deal with them and you pick them by hand, if you can, after you seed. Well, having a tool that’s smart and has low ground pressure and low ground disturbance and meets the needs of the actual problem, widens that window, where we can solve it and transforms the way that, takes this from a problem that’s barely solvable to a problem that is no longer really a thing.

Elisa: Let’s talk about some of the challenges the company has faced. It’s been this wild world over the past year, especially I know as it relates to supply chain and some other issues when it comes to manufacturing a real physical product. What are some of the challenges that you’re seeing in your sector and for TerraClear specifically?

Trevor: In the sector in general, I think there’s so much promise with digital solutions in agriculture but in many cases, they’ve really met their match with the conditions in farming. I mean, you’re talking about low bandwidth areas, relatively, generally very remote areas, very large areas and so often these digital solutions provide that, they’re challenging. How do you transfer high amounts of data to be effective with machine learning tools and computer vision tools? So that’s one of them is how do we figure out how to operate in these remote environments very effectively? I think we’re making the right steps there.

On the supply chain and being optimistic here, but really look at COVID and the supply chains, two big challenges for every company that deals with any hardware over the past year, and we’re just, I think in both cases we’re better for them as a company.

COVID was challenging at first, but farmers are naturally socially distanced and so it allowed us to figure out other ways to reach them and be more effective and really get closer as a company. On the supply chain side, it’s interesting how it’s affected our engineering.

We wanted to build, twice as many units in this fall, as we were able to because of some supply chain constraints. Well, that forces us to look at, okay, what are the items that are holding us back and maybe make some engineering adjustments to get those to be items that are more mass produced, which oh, by the way, reduces your costs. On the supply chain stuff, I think the silver lining is that it has made us more conscious of some of these engineering decisions and frankly, a little bit more flexible as a company.

Elisa: I know you have a really neat program that you’re working with at TerraClear to help with employing veterans who are looking to move into civilian life and work in tech and startups. You’ve been an incredible resource to your network. We’ve talked about potential candidates who are looking into joining VC or joining an early-stage tech company, or even you’ve talked with your friends who are founding companies and being a part of that broader discussion when you’re thinking about hiring, I think TerraClear is hiring veterans too. Is that right?

Trevor: Yes, and just a quick plug and a thanks, from you who have also been a part of a lot of those conversations and Matt McIlwain, who’s on our board, both really active in that world of, helping folks find the right situation.

There’s no shortage of programs out there that help with transition. We had an incredible army captain that came out of Fort Lewis and spent a few months with us and was able to really make a big impact in just three or four months. There’s no shortage of things to do at a startup as everybody knows.

The program that I think is maybe worth highlighting is one called SkillBridge which we’re entering into now, which is an up to six months internship for a transitioning veteran. Their salary is actually paid by the department of defense. The company is not allowed to pay their salary in any way. As long as there is a path to a potential opportunity on the backend, and there’s a good faith effort there, you essentially get this incredibly talented, often times, veteran who can come in and work for free for six months and they get exposure to, figuring out what they want to do and being able to contribute to a company in an exciting way. We’ve got a rockstar coming in in January to do that program. That’s one that I think is available for anybody that wants to look into it. Again, it’s called SkillBridge.

Elisa: Great! The process for startups to reach out, to SkillBridge, it sounds like it’s fairly direct and easy to post a job description and get referrals that way.

Trevor: Nothing’s too easy with the government, but it is relatively easy if you go to the website and that is an area that there’s a little bit of a backlog right now, but it’s all there. It’s all spelled out clearly and it actually is a fairly seamless process.

Elisa: Trevor, as a leader at TerraClear, you have some incredible background and lessons you’re bringing from your experience as a Navy seal over into the startup. What are some things that you’ve directly taken from that experience and applied to the TerraClear team to help with team building, cohesion, getting people on the same page, and things like that?

Trevor: One of the things that is a hallmark of special operations is how close the teams are. That allows you to be resilient and flexible and deal with missteps much more effectively. The why behind that, I think, has a lot to do with how you’re just presented with challenging situations.

Training is artificial challenge and controlled environment that makes things very difficult and what you see time and time again, it’s very evident that when you go through hard things with people, you get much closer with them and you learn about much more.

Figuring out ways, without doing morning PT every day at TerraClear, figuring out ways that we can push through some of these challenging periods and spend a lot of time and really immerse ourselves in this environment amidst some, significant business challenges has really, I think, brought our team closer and that’s nothing that I’ve done. That’s something that was already part of the team, was finding people who are willing to be really pushed and challenged. If folks are looking at a relatively easy, nice little lifestyle job, it’s not the right company because we’re always pushing ourselves. We’re always challenging and asking hard questions to see ways that we can grow.

In training, I guess early on, I learned the value of leadership, which sounds extraordinarily cliche, so let me unpack it a little bit. Everybody kind of believes in this, but everybody has a different definition of what it is. It really materialized for me in a way when we were in basic seal training, you just do a lot of races and challenging group things with the same sized groups.

One example is you’re physically racing with boats on your head. It’s this a perfect team game, because if you pull your head down, the weight increases for everybody else on their team, whereas everybody, stands up tall, then it actually evens out the weight and reduces it. That one weak link affects the other five people on the boat. You just do these for hours and hours and days and days, and things like that, that are really challenging a group.

They do this thing where they’ll take the groups, maybe one group is getting first place every time and another is getting fifth place every time. The only thing they’ll do is they’ll swap the two leaders. So, the boats stay exactly the same with leader swapped. Shockingly time and time again, is that the poor performing boat, all of a sudden is winning races or coming close to it and the other boat drops off. So what is that, right? What are those traits that define that?

I spent a long time thinking through it, and boy, I have evidence that, that exists now, what are those things and how do you then replicate them moving forward? I think there are a couple of things, it’s a leader who is trying to celebrate and identify the strengths of the group as opposed to elevate herself or himself.

The ability to actually just think hard about what does this person want and how can I help them be more successful? That framework I think is what really has, I think, unlocked the good leaders that I’ve seen in the past. It’s a little bit liberating because you don’t have to have all the answers.

You don’t have to tell everybody exactly what they need to do. You just need to identify the things that they’re great at and really help celebrate those things and put them in the right positions to succeed.

An example is when I came in, I think Brent chose to see the upside of what I could bring to a company rather than the downside of what I didn’t know. It’s a great example of that as somebody who’s an enabler and an empower and I think that’s an important lesson.

Elisa: Wow. That’s incredible and then you do the same thing with your teams. That’s an incredible way to think about how do you succeed together? How do you recognize other’s strengths and set them up to be in a position of success to leverage those strengths, knowing that the rest of your team is thinking of you that way?

Trevor: Another exercise that we used to do that I think is a hallmark of a good company and you see it a lot is, the ability to be really harshly, honest with yourself, both at a personal level and at a company level. And so, we used to do, you had a training mission, or you do a real world mission. If something good happened or bad happened, the first thing generally after everybody got a glass of water, was to come back and do what’s called an after-action review. This is a breakdown of every part of it with an eye towards what you can improve. So shockingly little is celebratory, ‘how cool was it when we did this’? Like, there’s not much of that. It’s more ‘hey, it took us 10 extra minutes to get in. Why did that happen? Why did we judge that incorrectly’? What it does is it just kind of breaks down the ego pretty quickly when you’re just used to always talking about what you could have done better.

That’s something that I came into this company and really was looking for was a company that was honest with its own shortcomings and honest with its own degree of performance. I think that creates a culture where you can really get to rapid growth, both personal growth, and also, company growth is we’re just constantly asking how can we be better and trying to look at ourselves as honestly as possible.

It’s hard, right? I mean, we all have ego and it’s sometimes hard to address those things, but at least talking about them regularly and finding people that want to, aspire to that value has really been important for us.

Elisa: Right, and people who want to join that environment and learn how to do that from you and then contribute. That’s exciting.

Team TerraClear is this incredibly dynamic group of people. You have software engineers who have a background in coding and computer development and AI. You have folks with farming backgrounds, yourself as a veteran, all coming together in this world of ag tech and selling to farmers.

What is it like selling to the farmer customer and how do you galvanize the rest of your team to understand the problem sets of the farmer and, and work with them?

Trevor: The best solutions at TerraClear come when you combine, we think about it in three areas, business leaders, farmers, people in farming and agriculture and incredible engineers. The ability to blend those worlds is probably our best attribute as a company, as we’ve got people that have never even been on a farm who just want to solve a problem that affects a lot of people. Then other folks that have never don’t even know what deep learning is. We’ve actually got two glossaries that we have in our onboarding process. There’s the Grangeville, Idaho glossary, and there’s the Seattle Bellevue glossary. Oftentimes people have never heard of a combine or a header or, tillage. That’s totally fine, because as long as there’s enthusiasm and passion for the problem we’re solving that’s great.

On the other side, these are people who have been dealing with dirt and rocks and seed and crops for their entire lives, and don’t have a familiarization with the technologies and so constantly putting people in different environments. It’s the thing that I just love about the company, I mean, even culturally, there’s not a lot of companies out there that have that type of diversity, where you’ve got people from central Idaho and people from Seattle who are constantly interacting and we’re going back and forth all the time. So that’s really fun and it allows us to, I think really have an edge against a lot of other agriculture companies, because we can recruit such incredible engineers out of this region.

On the farmer side, working with farmers, farmers are really multifaceted and what they’re asked to do. They’re managing, budgets and then they’re fixing equipment and then they’re designing new solutions, with steel and welding. Then they’re really CEOs of a larger organization with a lot of employees sometimes. You’re asking so much of them that they can’t really live in the theoretical world. It’s very practical and often very physical.

This is why I said earlier, digital solutions often meet their match in agriculture is because, the idea of an insight for a farmer isn’t that helpful because they just don’t have time. You’ve got to give them an answer. A real practical solution that’s going to affect their bottom line this year. Sometimes, there are things that lag in agriculture because they’re not able to forecast out 10 years because the risk is too high. They need to focus on the immediacy.

The way that’s manifested for us is getting into fields and really understanding the problem firsthand but also understanding that we’ve got to provide real value from day one. That’s how we’re going to really grow as a company.

The rocks as a problem and as an entry point into ag automation, it just think is right on because it’s something that’s acute and visceral and nobody wants to do it and it’s the first thing they would love to outsource. If we can solve this problem for the vast majority of acreage globally, there’s just so much more that we can do in terms of bringing automation that’s practical to farmers.

Elisa: Thank you, Trevor. Thank you so much for joining us. It’s amazing to have this chat and to have you on the Founded and Funded podcast. Thanks again.

Trevor: Really a pleasure. Thanks for being interested in taking the time and for everything that you guys do at Madrona, you’re incredible and a great partner. So, thanks.

We are trying something a little different this week. I sat down with our new Partner, Aseem Datar, to talk to him about his journey to being a venture investor at Madrona. Aseem worked at Microsoft for 17 years in a wide variety of roles from developer to global sales to helping to build Azure into an over $20B ARR business. We talked about growing up in Mumbai surrounded by Jugaar – the Hindi word that means Hustle plus a lot more, how he got to Seattle, to Microsoft and to Madrona and what he looks for in a company.

Aseem also didn’t waste any time and led our seed funding of SpiceAI which is innovating in the Low Code AI space, helping developers integrate AI into their applications and he talks about that team and problem space too. You can listen here to the 20 minute podcast or find it on all of the major platforms! Aseem’s bio (and contact info!) is here.

In this episode of Founded and Funded, Madrona Partner, Chris Picardo, sits down with Dr. Ali Ansary, founder & CEO of Ozette. Chris and Ali talk about Ozette’s mission to uncover hidden information about the immune system to help with the efficacy of cancer treatments. Ali also speaks about the ability of biotech companies to attract traditional tech talent.

 

 

Transcript

In this week’s founded and funded Madrona partner. Chris Picardo speaks with founder, Ali Ansary about Ozette, Ozette is what we call an intersection of innovation company. Blending innovation in life sciences with machine learning and AI to uncover data not available through conventional means.

Ozette is focusing on the immune system and specifically how various cancer treatments interact with the immune system. As therapies for treatment, get more complex and doctors are evaluating how to combine various treatments, especially in the case of cancer treatments. Data like this. Derive from Ozette can have a direct bearing on a patient’s experience.

Ozette spun out of work and an open source project. Developed at the fred Hutchinson cancer research center. [00:01:00] Combined with incubation at the Allen Institute for artificial intelligence. Chris and Ali talk about building a multidisciplinary team. And the unique. Attraction that a life sciences based.

Company has for traditional technical talent.

Is a great conversation. Listen on.

[00:01:23] Chris Picardo: Ali super excited to have you here on the Madrona podcast. And it’s always fun to have these conversations, especially with entrepreneurs who are early in the journey and learning new things every day. So excited to have you join us. Ali is the CEO of Ozette which is a recent investment that Madrona made and was spun out of both the Fred Hutch and the Allen Institute incubator here in Seattle and we’re incredibly excited to partner on the journey. One thing that’s so interesting about Ozette is that this is another investment that Madrona has made and what we’re calling the intersections of [00:02:00] innovation, which is companies that are operating at sort of this intersection point between cutting a wet lab, life science techniques and machine learning and software. We are super optimistic about the future of companies who are working there and Ali will certainly share more of the reasons why we’re so optimistic. And, you know, we’re excited to have this discussion.

So without further ado, I’ll introduce Ali he’s the CEO of Ozette. Ozette is a immune intelligence company that combines the best of single cell analytics with cutting edge machine learning. When we say single cell analysis, we’re talking about the analysis of individual cells in a patient’s sample. It’s often used to diagnose conditions like leukemia, and there are many other emerging use cases and Ali will certainly talk about some of those.

Ali, that’s a lot of me talking. I think it would be great for you to spend a little bit of time on the background of Ozette and how it was founded, how you originally got [00:03:00] involved and where you guys are now.

[00:03:02] Ali Ansary: Well, I appreciate, Chris, you’re having me. I’ve been looking forward to spending a little time, I know you and I speak on a weekly basis, so I think it was a natural time for us to put this down into recording. I appreciate it the Madrona team has been absolutely supportive and like you had mentioned, you know, we we’ve been fortunate that, Ozette’s being built in a, what I would probably say the capital of humanology. A lot of it actually predates, Ozette and the work that had been pioneered at the Fred Hutch, with E. Donnall Thomas who had received his Nobel prize in pioneering work in bone marrow transplantation in the early nineties.

That basically put a springboard for the Hutch becoming a pioneer in cancer research, infectious disease. You had Immunex who was known for their therapy for Enbrel which Amgen had acquired. So, naturally what has been being set up for the last two to three decades, Ozette has been able to capitalize on.

I had the [00:04:00] opportunity to meet my co-founding team out of Raphael Gottardo’s lab, as you had mentioned, who was the Director for Translational Data Science Integrated Research here at the Fred Hutch. It was a whole new place where you’re integrating across data sets the science meeting computational biology. My two other Co-Founders Greg Finak and Evan Greene were all part of Raphael’s team, they were senior staff scientists at the Hutch as well, who joined as my CTO and VP of Data Science.

A lot of this actually spun out of this need to look at really high dimensional single cell data, as you had mentioned. I think the last few years we’ve seen advances in instrumentation that has been able to generate large volumes of data in a quick amount of time.

So I met my, I met my co-founding team and we sat down, as an opportunity to look at the work that they had pioneered in the field of single cell analysis. [00:05:00] Now, again, there’s a lot of background context here that I think is important to point out in the sense that, you know, biology had never had a large amount of data until just recently. Biologists, never had access to this large amount of data and the tools to analyze it. Now we’re creating such a large volume of data that some of our partners will tell you that they’re only looking at 10% of the data. In fact, they’re leaving 90% of the table and the fact that, Greg, Rafael, and Evan had pioneered a lot of the tooling to be able to do the analysis of single cell work allowed us to be in a unique position.

When we’re talking about single cell analysis, what we’re talking about is that immune system. Coming back to why the Hutch was a unique player in all this because of the resources around and uncoupling with the immune system has been able to do, we’re able to use our technology to really measure individual cells [00:06:00] as it’s coming off an instrument. That allowed us to not only just resolve what the immune system is doing.

As you know, I’m a physician by training and I still spend part of my time at the hospital taking care of hospitalized cancer patients. There’s this frustration of not knowing how patients are responding to treatment and understanding better how patients are optimized for the right treatment is super important in today’s environment. So the right treatment for the right patient, what does that mean? How do we find that? What are the instruments that are necessary? What are the platforms doing? So what we’ve essentially been able to do was, build a platform that’s automated the workflow for scientists in order to unlock the power of the immune system. That platform has also allowed us to use power of machine learning in order to unlock the power of the immune system.

[00:06:53] Chris Picardo: So, Ali, I think it’s really interesting, I’ll pick up on a thread that you just mentioned, which is that over the [00:07:00] last four years, five years, it doesn’t really matter, there’s been an explosion in the volume of data, right? The instrumentation for collecting and putting more kind of granular detail on this single cell data is really catalyzing that volume, how, without Ozette, would people analyze that data?

[00:07:23] Ali Ansary: They’re all analyzing it manually. This is the other part that gets us absolutely excited. The field of science is ripe for innovation to automate that workflow of data. So traditionally we have scientists, computational biologists, analyzing high volumes of data, but the dimensionality only recently has become very high. Before we’re looking at maybe only a handful of different parameters.

What I mean by that is, a computational challenge brings you back to your old math days. So two to the nth power, “n” being the number of proteins you’re measuring, or parameters, and two, whether it’s on or off, or there or not. [00:08:00] So in the past, we’re only measuring six or eight different components, so two to the eighth power means the search space is pretty feasible manually, but now that we’re measuring 30, 40 hundreds of different parameters, that search space is too large to do manually.

This is where the platform that we’ve developed allows you to do not only the analysis in real time of this high dimensional data, but allows you to explore that data and understand the visualization of that data and the impact of response rate to therapy. So,to bring it back, what you were saying is that there’s a large volume of data that’s being produced that was just being done manually.

It’s funny becauseI think that the bar for innovation is actually very low right now. That’s because we are only now starting to begin to see the opportunities that exist.

[00:08:56] Chris Picardo: Just put an example on the last thing you just [00:09:00] said, Ali, you know, give some color around the type of insight that you can derive if you can look at the data in higher dimension, versus when we used to only be able to look at four or five parameters.

[00:09:13] Ali Ansary: That’s right. So this is the part that gets me most excited as a physician because now I can determine response rate. I can now determine whether or not my patient is going to have Cytokine Release Syndrome or Tumor Lysis Syndrome, it’s that anticipation of treatments. When you look at these immunotherapies, these checkpoint inhibitors, for example, you’re unlocking the brakes of the immune system, right?

Now all of a sudden it’s going at a hundred miles an hour and, you know, Usain Bolt ultimately runs out of energy as well. With our platform you have, now, this ability to predict when the immune system is going to shut down and then you can augment that system as well.

Not to be too heavy in the analogies and I’ll have to give credit to my mentors for these analogies, it’s not something that I’ve come up with my own, but what we’re seeing is [00:10:00] that we can’t just be treating patients with single therapies any longer It’s going to be a combination of different therapies in order to treat an individual. It’s much like playing Beethoven’s fifth, it’s not just with one violin and you have to know when the various strings are coming in, in order to be able to have a beautiful symphony, and that’s what we’re seeing in immunotherapy today.

[00:10:22] Chris Picardo: Is it fair to say then Ali, that, Ozette sort of gives you that lens and that insight generating ability to be able to do some of the things you just said?

[00:10:34] Ali Ansary: Yes, so the opportunity here is not only in just automation of the data that’s coming off the instrument, but it’s also to learn from that data. It’s to be able to build a corpus of data against different disease processes, and then to be able to integrate across different data sets. You can use NLP to query against existing data against the publications, against publicly available data. There’s a large component of computer [00:11:00] vision with actual visualization of the data that’s being generated. The machine learning itself allows you to optimize that data generation. The insights that you’re now providing are just as valuable as the instrument that’s being produced on. Your Porsche is only so great as the driver behind it, otherwise it’s just a car that takes you from point A to point B. So, we’re positioned really uniquely to take advantage of single cell data that’s being generated in high volumes.

What we’re talking about here is at that protein level. We know that we are still developing therapies that target proteins, the FDA recognizes that it’s the proteomic data that’s the most valuable. You don’t necessarily submit transcript or you don’t make data for the FDA to approve, and a lot of the instruments that have really catalyzed the science, everything from genomics and transcriptomics and spatial omics, still are really early R&D discovery instruments, and [00:12:00] they will continue to increase in throughput. We’re seeing this, and that’s why the platform that we’re developing has a multi omics approach, but our primary focus has really been at the single cell proteomics level to really resolve each individual cell type and building these corpuses of data in order to be able to drive.

The one last part to not discredit is that, the instruments that measure the single cell proteome plays a role in every single part of the drug discovery pipeline from discovering and R&D through early and late phase clinical trials, all the way post FDA approval. These instruments have been around for the last 3-4 decades. So we really are primed to be in a place where there’s an accepted methodology and instrumentation for generating data, for us to be able to take advantage. There’s so much information and data for us to utilize and build upon that. We’re really primed uniquely right now [00:13:00] for this.

[00:13:03] Chris Picardo: One way, now that you mentioned, that I like to think about how to frame our areas of interest when we invest in intersections of innovation, is to think about sort of two broad buckets. One is, companies that have a method to generate totally novel data. A way that you wouldn’t have been able to see this before and then be able to apply machine learning or some sort of software to that.

The second is companies that are saying like, “hey, there is an explosion of data, but the tools and the ways that we’ve been looking at the data is not keeping up with the volume and where it’s going, and that we actually have to have a lot of insight generation mechanism to take advantage of what’s going on there”.

I think in some ways, those that sit in both of those buckets, but certainly there’s such an interesting thing to do in the second bucket where, like you said, there’s so much of this data and the lens has been manual, and now we’re switching it to machine [00:14:00] learning and insight generation.

So, given all of that, I thought it would be interesting to talk a little bit about the founding of Ozette. I think one thing that, that you guys did that’s fascinating and I just love your learnings on is, this company was formed in a trifecta process where Rafael, Evan, and Greg had been building some of the core software that underlies Ozette, at the Hutch for years. You were at AI to, trying to understand where are the interesting places that I can engage in this intersection and you guys came together and you built a company that has really deep academic roots.

I’d like to just have you add some color on how you think about building a company and bridging it out of the academic world and having to bring it into the more commercial use case and pharma or [00:15:00] customer facing world.

[00:15:01] Ali Ansary: I love that you asked that question, because in the life sciences, that academic affiliation, that academic validation is absolutely important. It’s a field where you cannot just sell vapeware, that your science has to be validated by your peers. You have to be able to replicate it and over validate it, based on publications in the science itself.

So to have an academic foundation has been crucial to what we’re doing. In fact, I think it has given us a strong platform to build, so we already had, I think, the back of the envelope was nearly $6 to $8 million in grant funding to be able to build the tooling that’s necessary. That gave us significant advantage versus anyone else who’s trying to build any kind [00:16:00] of competing platform to what we have.

It also allows us to actually be more resourceful too, because we know that with grant funding, academic institutions, you have to be nimble, you have to be fast, you have to be resourceful, because you only have only a finite amount of time and money to be able to build a technology.

The academic spin-outs have been advantageous to us. It allowed us to partner very quickly because of the reputation that Rafael, Greg, and Evan had built over the course of a decade. It allowed us to take advantage of an open source community that we’ve been continuing to support, and building that reputation saying, “hey, we’ll continue to support the open source, which is very critical to part of our mission [00:17:00] and business, but at the same time, we can build a significantly better version and automated version of what our open source tooling provides”.

We were positioned very uniquely, but I think in the life sciences as a whole, that academic affiliation is really important. It allows you to have a place of creativity, a place of research, a place of being able to build out, iterate quickly, experiment, and then bring alive. So, for us again like I had said earlier, I think it really positioned us in a unique place. I think in the field of life sciences you do need that those academic partners. Many of our early studies that we’ve been partnering on are through academic cancer centers, some are industry sponsored, some are not, but it allows people to become more aware of what you’re working on.

[00:17:54] Chris Picardo: How do you think about the team building when it comes to that? You’ve got a couple of core [00:18:00] team members who are at the company and you have a couple of core team members who will stay in academia and so how does that, as CEO, inform how you think about building a team around that kind of core academic group who really got the core product where it is today?

[00:18:23] Ali Ansary: Chris, I love that you asked that question. What we’ve been able to do at Ozette is position ourselves, not just as a life science company, but as a company that is bringing core values and missions that I think resonate really well with traditional engineers that have been at companies that are just making more money off advertisements and clicks. What you’re seeing is that engineers are tired of this and want to be able to have an opportunity to contribute [00:19:00] to something to a vision that’s beyond them.

At Ozette, it’s really creating an ecosystem and a dynamic where you have engineers, not necessarily executing a scientist’s idea or vision, rather creating an environment where the two can learn from each other. So you have these “aha” moments and you have this true curiosity and collaboration to be able to push a vision even forward. We’re lucky again, there’s a foundation technology that we’ve developed, but that’s version one. We’re planning for version two, version three, but the version 100 is going to come from these moments where you have talented engineers working across disciplines. This is where we have a lot of different opportunities to be able to educate whether it’s active learning or passive learning.

[00:19:49] Chris Picardo: I think that’s awesome. One thing I’m curious about is Ozette’s in a pretty specific subsection of life science, [00:20:00] right? Single cell data is its own world and field of study and we’ve seen that in a lot of ways. We’re bringing engineers with no background into something that’s really deep.

Just talk a little bit about the interaction between the engineers that you have on the team and the scientists and how they work with each other and what you sense is going on there.

[00:20:28] Ali Ansary: The interaction is something I have witnessed only a few times. What it is, is creating an environment of free flow of thoughts and questioning. There’s this culture of authenticity that we’ve been able to create at Ozette. I have no idea how it came about, but it’s been very unique in the sense that there is no such thing as a silly question.

It’s an [00:21:00] opportunity to truly bring in world’s experts who have developed everything from a front end to a backend with computational biologists to ask questions. As long as we’re asking questions, we start focusing on what are the right questions we need to ask and having that opportunity to have candor and challenge, and then come to a resolution quickly and then going and execute an idea. If it fails, you come back and iterate, understand why you failed in order to build forward.

Every component of any startup is risk and how do we mitigate risks? How do we create alignment? Being aligned that it’s okay to fail and coming back again to iterate on those processes. What we’ve also done is making sure we’re aligned on our vision and our vision is very much finding the right treatment for the right patient.

We’re in such a unique place to be able to help catalyze, [00:22:00] and it sounds scary, but the cure to cancer. It’s really a unique opportunity for someone to join and say, “yeah. I can get with that”. It sounds surreal for me to even say that, but the partners we’re working on are developing some of the most cutting edge therapies. so much talent that we’ve been able to bring together that it’d be a waste to not truly have a strong vision that we can try to execute here.

[00:22:31] Chris Picardo: Yeah, no, that’s awesome. I love to, that you mentioned “stupid questions”. I feel like we talk once a week and I asked you lots of stupid questions about science and it’s clarifying for me. Hopefully, sometimes it’s clarifying for you too. I do wonder that now that, teams are becoming really cross-functional in this space, especially if that’s a little bit liberating for both the engineers, the product people and the scientists where someone’s like, “hey, you spent a ton of time in [00:23:00] PhD, which is great. You know way more than anybody else, but how many people ask you the dumb question anymore?” I wonder, and this is probably more of an open question, but if we’ll see that being clarifying and freeing as you guys move down and continue to create what you’re building,

[00:23:19] Ali Ansary: I think it is, and more than ever, we have to just remain intentional about it. We have to be intentional about even a job description, so we’re not excluding a particular individual for them to say, “oh, I don’t know if that place is for me”. We have so much to grow and develop. If you were going to ask us if we needed a designer 18 months ago, I would have said, “yeah maybe”. But it was probably one of the best decisions we made because as soon as we put Calvin in the room, you have these aha moments that just come within the first 15-20 minutes, and everyone leaves aligned and [00:24:00] energized with who has been able to deliver really strong products in the past.

There’s a lot of skills and expertise that I think we tend to overlook that are not always in the life sciences. That’s, what’s been really important is how do you bring those in even more now than ever before?

[00:24:20] Chris Picardo: That Yeah, that brings me to my next question. We’ve got all these cross-functional team members. It’s been awesome and we’re building, what’s largely a software company, or at least on the UX side looks like a software company to a world that hadn’t had a lot of software companies that operate like this.

What are you finding challenging or liberating, or what are you learning about trying to build a software product with this type of data, in this world where the end user is at the end of the day, aren’t often people who have been sold or used 50 software [00:25:00] products every week?

[00:25:01] Ali Ansary: This is a good question. The reason it’s a good question is that what we’re learning is the end user and the decision maker about adopting a technology, are often different people. Sometimes you’ll have a scientist who will climb the ranks because they’re on maybe a scientist management track and they’ll grow into a director, senior director or VP, but when you become a senior executive at a big biopharmaceutical company, you want to know whether or not your billion dollar investment in a therapy is going to be successful in successfully to be able to treat patients with a disease. You don’t want to see that therapy fail because [00:26:00] it’s a heavy investment, but the steps needed to bring that therapy to market, the early R&D and discovery, and every component of those clinical early and late clinical trials have different users involved with that.

I think one of the biggest challenges is your end user is not oftentimes the person who you’re selling to. You have to find your internal champions who have these aha moments. We’ve had a handful of different times where we’re presenting to a team of 40 or 50 scientists in a room and it’s one person who says, “oh, I get this. This is incredible. This is so far ahead of where we’re at”, and I’ll get an email right after saying, “this is incredible”. I’ll say, “yeah, absolutely! This is why we all left our full-time jobs to do this”. end user is not always going to be that champion.

[00:27:00] Navigating industry is really important. Industry is siloed. There’s a lot of turnover. There’s a lot of old data that’s sitting on the table. There’s a lot of different competing priorities. And only now we’re beginning to see a lot of this data becoming digitized and that allows us to have a lot of freedom to explore through different avenues.

[00:27:26] Chris Picardo: I’m lucky. I get to spend a lot of time with Ozette every week so I’m very close to the product roadmap and what we’re thinking about on a daily basis, but I am curious when you think about it from a user facing perspective. You’re building software for, at the end of the day, for scientists and drug development and discovery teams who are trying to find new therapies or understand how patients respond to different treatments.

That’s a lot different than building software for managing your workflow or optimizing your ad spending or any of these other things. [00:28:00] So I wonder, when you think about, what are the implications for design and visualization facing them? What have you had to rethink, or is it really just a blank slate where you were saying, “hey, there’s a lot of stuff we can do here and our partners are so eager to work with this software that we can experiment and some new modalities”?

[00:28:21] Ali Ansary: I think that we’ve struggled a little bit about this. We’ve been building out this partner advisory committee where we have scientists helping to shape and give us feedback. I will say that the talent on our computational biology team or data science team has allowed us to really say, we’re actually building this for ourselves, which is a pretty high standard. As long as we know that we’re building a product that we want to use, we will see it widely adopted. There are different components that a scientist will want to see or do because scientists are creatures of [00:29:00] habit and they want to still be able to maybe export the data and interacted on a legacy system, which is great and we’ll create that for them. But at the end of the day, scientists want to be able to see their data, interact with it and the first thing, anytime a publication is going to be a RIN, is the visualizations. You have to have the graphs that are available to be able to then write the story around it.

That’s really what we want to be able to deliver, is that ability to understand that complex data. I think it alleviates a lot of the time that the scientists are spending to do the analysis of data. We go straight to insight generation and these insights help drive really important decisions that again, determines whether or not a therapy will come to market or not, because we can help find the right patient for the right treatment.

[00:29:54] Chris Picardo: I think it’s so cool when you think about the visualization side. [00:30:00] One way to talk about what Ozette has already achieved is moving from looking at graphs and drawing circles by hand on a piece of paper to generate an insight because you’re using machine learning to identify factors and dimensions that you physically could not see.

So you couldn’t have drawn a circle around it anyways, because you didn’t know it was there. I think it’s interesting. I think this optionality and the ways that that will end up being translated through software, it will be an interesting paradigm for us to help create.

I’ve got a couple of last questions to wrap this back to the beginning. I’ve talked in the beginning about the power of what you can do with single cell data and Ozette is really facilitating, generating tons of new insights out of that. If you think about, call it the short to midterm, not the super long-term, but the next three to five years, where do you see [00:31:00] this world of single cell analysis and immune profile, and is this powered by Ozette, going and what are the interesting things that you are super excited to see happen?

[00:31:12] Ali Ansary: Another way to probably ask me that same question, Chris is what keeps me up at night? In the short term, we make it very clear that we’re here for long-term partnerships. We’re here to help uncover the large amount of data that has been otherwise left on the table and to provide novel insights that we actually don’t even know how to value because you’re getting so much information.

In the next half decade we’re going to be at a place where we’re actively monitoring every individual on clinical trials with high dimensional data and that data is not only helping [00:32:00] with pharmacodynamics, pharmical kinetic information, it’s determining response rate. It’s ensuring that the right treatment is getting to the right patients and Ozette will be the default platform all the way through for any single cell data. We’ll continue to build in our transcript omics and in spatial omics because we know this is the way the field is moving towards. What makes our platform and machine learning very unique is that, it’s unsupervised and it allows us to continue to be agnostic of instrumentation.

As a physician, my biggest frustration has been looking at a complete blood count or a complete metabolic panel, spend only a couple of seconds looking at it, and then I look at my patient and say, “all right, they’re healthy enough to get treatment or not”. We’re going to fundamentally change that because the insights generated from someone’s immune system is going to allow us to [00:33:00] determine that response rate in real time. We won’t need to wait six to eight weeks any longer to determine if you need a pet CT scan, to determine response rate. We won’t need to go back and rebiopsy a solid tumor because we have these immune markers that we’re able to extract. That’s in the short term and I know the short term is right around the corner, but in five years, we’ll have a lot of opportunity to mature with a lot of therapies in the field of immuno oncology.

[00:33:34] Chris Picardo: That’s a good vision. I think that if we accomplish that in this short term, that would be pretty incredible and not just for Ozette, but for patients and I think that’s, at the end of the day, what this is all about. That feels like a really good place to end because I’m not sure you could say it any better and so Ali I want to thank you a ton for coming on the podcast.

[00:33:55] Ali Ansary: you, Chris. I appreciate it. I always have fun doing these.

[00:33:57] Chris Picardo: We Yeah, do this and we [00:34:00] just don’t record it on a weekly basis so it’s fun to put it down and make something for other people to listen to, but really appreciate you taking the time Ali, and thanks for joining us.

Thanks for joining us for founded and funded. I’m Erika Shaffer from madrona venture group and i’ll be talking to you next time

Are you a founder or would-be founder? Madrona Investor, Ishani Ummat, sits down with Shirish Nadkarni, serial entrepreneur, now angel investor and author of FROM STARTUP TO EXIT, released by from Harper Collins in August of 2021. Ishani and Shirish talk about starting a company, finding your co-founder, product market fit and how to choose your investors.

Transcript (this is machine driven transcription so expect some typos)

Erika Shaffer:Welcome to founded and funded. I’m Erika Shaffer from Madrona venture group. Today, we hear from two new voices. Ishani Ummat, an investor at Madrona who came to us in early 2020, from Bain & Company and who has worked on numerous investments and initiatives at Madrona since. In conversation with Shirish Nadkarni.

Shirish is the author of the newly released From Startup to Exit book. Shirish has a special relationship to Madrona, which backed his first startup called TeamOn in 1999.

In this conversation. Ishani and Shirish talk about his road to entrepreneurship from Microsoft, how to choose an investor, and his 40, 20 10 rule. From Startup to Exit is on sale now, which is August, 2021. And it is a great how to guide for first time entrepreneurs. Listen on.

Ishani Ummat: Shirish, thank you so much for coming in today, it’s so nice to be with you in person.

Shirish Nadkarni: Hi Ishani, nice to be here.

Ishani Ummat: Congratulations on your book. So exciting to see you publish a book from this sort of illustrious career that you’ve had, it’s called [From] Startup to Exit. Is that right?

Shirish Nadkarni: That’s correct, yes. [From] Startup to Exit an insider’s guide to launching and scaling your business.

Ishani Ummat: That’s so awesome. I’m excited to get into some of the journey that you’ve had some of the anecdotes around that today. First of all, though, where can, when and where can we find your book?

Shirish Nadkarni: So we launch on August 24th you can buy it from Amazon, Barnes & Noble or really any bookstore. If you’re here based in Seattle, we have a great bookstore called Elliot Bay bookstores that you can purchase it from as well.

Ishani Ummat: We’re big advocates of our local bookstores, so certainly make sure to check that out for all of our listeners. Let’s start with back to the beginning. Like so many others here in Seattle, you started your career at Microsoft and, perhaps fewer of those people who started have ended up on this journey through many different companies, starting many ones and ending up as this, an angel investor, and then publishing a book about it.

I’d love to just go back to those original days. Microsoft is such an interesting and dynamic place. We’ve come to know and love the company here in Seattle. But making the transition from a big tech company into entrepreneurship and starting your own business can be pretty daunting for folks today.

What about working at Microsoft made you want to be an entrepreneur? Was there a moment where that catalyzed this; hey, I want to have this entrepreneurial startup experience rather than staying at a bigger company?

Shirish Nadkarni: Yeah, first of all, I was very fortunate to have joined Microsoft in it’s very early days. This was in 1987, when people were actually using MS-DOS. I don’t know how many people know about MS-DOS versus windows. Microsoft was really a startup a t that point. So I got great kind of experience working at Microsoft, launching email software on the PC and the Macintosh. And then I got to work on MSN.

I drove the strategy for msn.com and one of the things that we felt was really important for us to have was a web-based email offering. And at that time, I noticed that Hotmail which was founded a few years ago at that point was really successful and gaining a lot of traction.

And so I met with Sabeer Bhatia the founder of Hotmail and then quickly decided that we needed to acquire the company. But really what inspired me to become an entrepreneur was the fact that here what you know, two young adults 26 years of age who had built this amazing piece of web-based email, that you could access your email from any location. And that was really inspiring for me.

And I realized that the internet really had changed the model for startups. In the old days you had to not only develop your software, but you had to then, publish it on floppy disks and find distribution from egghead and so forth. It was not really easy for a startup to get going.

Whereas the internet really changed all of that and made it possible for a young entrepreneurs to build a piece of, SAS software and make it available through the cloud on the internet. So it was a lot easier to get started. And so that inspired me to, Dig that vision and really see if I could, provide a business email solution that would provide enterprise grade email and calendaring functionality for small to medium businesses. And that was the Genesis of TeamOn.

Ishani Ummat: Yeah, that, so precious, right? The vision for being able to access your email anywhere, anytime. But at the enterprise level, right?

Pretty different from the Hotmail product in its end user. But actually the underpinnings of that are quite similar. At Madrona and many of the other, large VC firms we think about these technological shifts, these major technological shifts, a step function changes, right?

What underpins what these technologies create, can be the underpinnings of massive new businesses and a pretty significant rise in startups. And okay, you have this passion for email, right? You work on the Hotmail acquisition. You take a little sabbatical, take some time off, reflect on things and come back energized and see an opening in the market, for sort of enterprise email. And the product, really great. We’ve talked about in early days, I can totally imagine who would use email every day. And who would think about using email even multiple times a day? Seems like it could have been, that could have been dissonance around; okay is this a weekly product? Is it a monthly product? But everyone was on the phone. People would re record rerecord voicemails. Finally get it right. And leave a voicemail. But no one was really using email all that often. So of course, we’re looking around that corner to the next thing you came up with this idea, I saw a market opening, built a great product and raised some VC funding and including from Madrona. ‘

Shirish Nadkarni: That’s right. This was in the heavy days of the internet.-boom, the .com-boom. I raised $15 million , a number of VCs, including [00:06:00] Madrona ventures here locally. And did that, with just a beta product. It was quite amazing. And I was lucky to have raised lot of funding at that time.

Ishani Ummat: Yeah and even in today’s world of massive rounds, $15 million is a pretty hefty amount. And thinking back to, that era of the .com-boom, you, must’ve done such a great job of conveying the vision for the company and Hotmail paving the way in terms of understanding the product at a conceptual level.

But I’d love to talk a little bit about some of the lessons you would share and you learned from that experience. We live in a world of product led growth now. And there’s these big terms, “product market fit”, “customer validation” they’re tossed around quite a bit. And there’s a lot of lengthy theories out there on what exactly it means to have “product market fit”. How do you measure that? What markers suggest that you might have it? Folks might be familiar with Rahul Vohra’s Superhuman’s Playbook, that’s really gotten a lot of traction lately, which is just around this idea of how would you feel if you could no longer use the product. And when customers say that they’re very disappointed or disappointed, maybe you have something that people might be interested in and would be upset if they couldn’t use.

So there’s a host of other ideologies that become popular in the product market fit front. And how to think about and measure it. But thinking back to those early TeamOn days, what do you wish on this front measuring product market fit, thinking about it that you had done differently?

Shirish Nadkarni: Yeah. When I, you know, thought of the idea of TeamOn and the notion of web-based enterprise grade email. I was convinced that this is going to change the world. And so I did really no virtually no market research. And in a sense, I was taking a bet that as you said, the technology shift.

That’s really what enables new startups to come out and change the world. And so I was making a similar bet that email would become prevalent in a kind of cloud-based environment. But I wish I had conducted, customer interviews to find out if the market was ready for our product. And it took a long time for cloud-based offerings to really gain acceptance because companies were not really willing to keep that data in the cloud. They were, they had concerns about security cloud based offerings. And I think that’s what ended up for us making it difficult for us to be successful with the original vision for TeamOn was that email is really sensitive data. You have sensitive communication, sensitive documents being shared across, individuals in a company. And I think at the end of the day, at that point the industry had not really migrated to a point where they felt comfortable with, cloud based storage of sensitive information.

And so we had to pivot and ultimately we pivoted to a mobile version of a TeamOn the idea was that you could access your email, your existing email from any internet enabled phone.

Ishani Ummat: Which is such an important part of the startup journey, but, hearkening back to the original vision, you were just too early. And I think sometimes when we are on the cutting edge of what’s going on and looking at these broad technological shifts and specific applications, sometimes we forget that we have to bring the rest of the market along with us. So what a good journey and what a good learning set of learnings for you in in the startup journey and how to, respond to a market need, but then also where exactly it’s taking you and how exactly it’s playing out, maybe a little different than you would have anticipated early on. It’s a good learning that most of our founders go through at many given points in time.

Before we talk about the next journey that you had, I wanted to talk about briefly, early in your book, you mentioned that recruiting your technical co-founder took you several months. It’s one of the biggest challenges. LinkedIn didn’t exist back then, there was no teal fellowship, no on-deck fellowship, none of these Twitter, different types of ways to build relationships and find people that might be interested in building the same products or same types of technology that you are.

Given all those things exist today, it’s still a big topic and it’s still a massive challenge. I talk to founders about all the time. How talk us through how you found a co-founder, how did you approach the process and what parts are still relevant for entrepreneurs today?

Shirish Nadkarni: A tough time to recruit people, even though, as I said, the.com- boom was happening and a lot of people were leaving established companies to join startups or start companies. I first obviously went after people I knew at Microsoft and many of them were excited about what I was applying to build. But they just couldn’t get themselves ready to leave Microsoft, where they were getting a nice comfortable, you know, paycheck and healthcare and all that. In my case, finally, what happened was I was introduced to my co-founder Shaibal Roy through a common acquaintance. He had a lot of expertise around email but unfortunately he was based out of the bay area and he was working at Netscape at that point and still was also hesitant to leave the company.

So we arrived at the arrangement where I would work with an outsourcing company to get the software developed and he would work part-time in the bay area and guide the outsource development shop in developing software. And that he joined the company. Once we raised the Series A and that’s what happened we raised $15 million and obviously that made him comfortable enough to move from the bay area and come get to Seattle.

Ishani Ummat: That’s great. Fortunately for a lot of folks today, we live in a world where remote work is possible. Folks are building remote first companies and instead of having off-sites, having on-sites for the first time. But I think that problem and challenge of leaving a comfortable job in a position, whether it’s at a big tech company or even a later stage startup to go start your own venture can still be so daunting and still be a big decision for folks to make. So I would say that’s part of, one of the challenges that still remains for a lot of entrepreneurs looking for co-founders to come and join them.

Shirish Nadkarni: Yeah, and it’s difficult these days because especially here in Seattle where you have all the big companies, whether it’s Microsoft, Amazon, Facebook, Google. And the amount of compensation that they’re providing is amazing. So you really have to, one of the things I emphasize in my book is the fact that the founder has to be really a visionary and a great sales person, not in a traditional sales person sense, but somebody who can really excite people about their vision. I think that’s an essential skill that a founder has to have to successfully recruit folks to join the company.

Ishani Ummat: Absolutely! And I think that’s part of the skill set of pitching to investors too, is having the conviction and then being able to convey that conviction to a broader group of folks, whether that’s someone who’s going to join your team and having that recruiting capability is so important. Backing that recruiting capability is the venture funding. And so that’s something, absolutely, we all look for and hope to see in many of the entrepreneurs coming out of Microsoft, Facebook, Google, etc.

Okay. You start TeamOn, you have a great exit there from the email company, and then you go on to start a new company, right?

So this started your serial entrepreneur journey, a company called Livemocha, both inspired by and then acquired by. So you mentioned that, a year and a half into Livemocha Series A, one of your VCs instructed you to work with an investment bank and sell the company actually at a valuation of $100 million, even though you had a little proof of monetization and your acquire, wasn’t interested in paying that price. That’s the canonical example of don’t work with venture capitalists. Right, like, that’s what everyone’s terrified of. Then they weren’t happy with the proposed price and then to me, that seems so absurd, you know, coming from an objective point of view, but it’s true that I talk often with entrepreneurs who are nervous about giving up control of the company for fear of this type of situation playing out.

Inherently, and always there are going to be some bad actors out there, and so that’s a nature of the deal. Largely, in my perception of the world this often comes down to misalignment. A fundamental misalignment between an investor and an entrepreneur, or the, a mismatch, if you will.

How would you advise founders that, you work with now on the angel side of things to avoid this conflict with their own VCs or folks that they might be thinking about taking money from?

Shirish Nadkarni: So that’s one of the things that I really talk about. My book is you have to be really careful about who you pick as your partner in terms of the VC firm. So not only do you need to do due diligence about the VC firm that you want to partner with, but specifically who is going to join your board.

Unfortunately in my case while the individuals who joined my board were really smart individuals, they were fairly inexperienced as venture capitalists and they didn’t really have good, they had good operational experience, not really in the startup world.

And I didn’t really get good guidance, good advice from my board members. So it’s really important for you to, have a discussion with your VC firm, understand who is joining your board, do the due diligence, just as much as they are doing due diligence on you to really make sure that there’s a good fit and they have the world of experience that you can count on to make important strategic decisions in the future.

And then if you receive acquisition interest you really have to, as a board figure out, you know, how you want to respond to that interest. How’s the company doing? Is the company really doing well? In which case you may not want to sell the company or sell the company only at an astronomical price that makes it compelling for you to consider.

It’s very important that you don’t waste, the time, the precious time, each founder has, can only focus on a few things and, we want to make sure that as a board, that the founders are really focused on making the company successful and that you don’t waste their time on unnecessary pursuits that may end up not being very successful.

Ishani Ummat: Yeah, it’s a really good point that M & A is a whole separate topic that we could talk for hours about as well and that process gets really complicated quickly and we’re seeing more of that with the rise of SPACs and that whole advent, but coming back to this mismatch point and being, having alignment on your board.

Such a critical part of building a company is prioritizing the right things collectively. And I think first time founders, serial entrepreneurs in general have so much to learn from, about creating a board and their board members and putting the right people in that room together to help drive the business forward, create alignment, and make collective decisions. But it’s hard. It’s a really hard process to understand who the right partner is for the long journey are going to be.

One of the things I’ve seen more recently, is founders actually, while they’re doing the fundraising process. And in those sort of third or fourth conversation with investors actually hold a mock board meeting. And I really liked that because it you’re right. It is such a two-way street where you have to figure out, hey, is this the right fit for the investor? And is the investor the right fit for the entrepreneur? And the mock board meeting is such a good way to test that because saying, hey Shirish, how are you going to be, if you’re on my board, what is the type of interaction? What are the questions you’re going to ask me? What rapport can we establish? What are the directions you’re going to push on? Where might there be tension? Can be sussed out so nicely in a board meeting or in a mock board meeting versus just a formal one-on-one pitch, right?

Shirish Nadkarni: Yeah. I think that’s a great idea to test out if there’s compatibility between you and the board members. The other thing that I would emphasize is that really the board meetings while, there’ll obviously be discussion around operations, situations and how you making progress and all of that, most of the board discussions should really focus on strategy.

What are the strategic decisions, important, strategic decisions that the company is making and are they making the right decisions and investments? And you’ve got to do that on a quarterly basis so that you make sure that you’re all in. But your board and you making the right decisions moving forward, that’s really the level at which the VC should really be or the board members should really be operating, not getting into the nitty gritty details of the operational performance of the company.

Ishani Ummat: Yeah, totally. And I think, there’s certainly both sides of that argument. I, 100% having strategic alignment in the board meetings themselves and with the board members and when you have to have those quarterly meetings that making sure you’re focused on the strategic aspects of the goal.

As a junior investor, we also try to spend a lot of time in those details, those operational details outside of the context of a board meeting. And I think that’s also where folks maybe don’t quite utilize their investors, as much as they could. Having a board observer or someone who has been in those meetings, but also can get into the details with you and say, hey, let’s test this operating model, or what might pricing look like and how can we go figure out a bunch of different pricing options? And what have I learned from pattern recognition around seeing the companies that I work with and how can I bring that to you? Is another really good way to take advantage of the fact that, hey, you have this group of people that are eager and willing to help beyond just writing a check.

Shirish Nadkarni: And I was fortunate that at least one of my company that I had the opportunity to work with other members of the VC firm who are willing to roll up their sleeves and really get into some operational issues and provide their expertise.

That was a really valuable resource. So you should, as a founder, really understand. What resources is the VC firm providing to help you with operational issues, with recruiting, with business partnerships and leverage the hell out of that relationship for your business.

Ishani Ummat: Totally! And it’s something that we at Madrona and many of our peers always try to make really clear when we work with companies where we start the journey together is that it’s more than capital.

Shirish Nadkarni: Yes, I remember actually, when TeamOn working with Matt McIlwain when he was, an early partner at Madrona back in 2000, it was, we had some pricing discussions and I remember, to this day he offered some really good advice to help me think through my pricing challenges.

Ishani Ummat: That’s so great to hear, and I’m sure that advice has been amplified by many more years of experience since then. So for folks that you know, are looking for, to work with hands-on investors, that is an awesome way to be able to utilize them. So let’s talk about what happened after Livemocha.

Shirish Nadkarni: So after my mocha I launched a third company called Zoomingo, this was in the mobile shop space and the idea was to take all the information that you would typically find on your Sunday flyers. Of course these days nobody gets a newspaper, but in the old days, people would get the Sunday newspaper just so that they could get all the flyers from your, Macy’s or Nordstrom’s telling you about all the great deals that are happening.

What we did was built a mobile solution, which allowed you to access all the great deal information by zip code. So based on where you’re located, tell you, Pierce, Bellevue square mall next to you and hear all the great deals being offered by Macy’s or Nordstrom’s around you.

We did pretty well initially. We got to number 15 in the shopping category as an app, we had over two half million downloads but the space got super competitive with big, much bigger players entering the market with coupons.com and others. And so our growth flattened out and that’s the death nail for any startup it’s you have to show hockey stick growth otherwise it’s very difficult to raise funding. So unfortunately that was one where we didn’t really have a successful outcome.

Ishani Ummat: Yeah, but so much learning along the way. And again, this kind of precious product motion where you identify, you have a life experience that informs you starting a company because it’s such a big pinpoint, where’s there going to be a sale? Why do I always get this paper in the mail? And then turning that into a new technological shift has created an opportunity for us to build a company around it. So again, those, thematic learnings really shining through and every time I’m sure you got so much better, learned so much from the last process.

Shirish Nadkarni: Yeah, absolutely. One of the things that we were highly focused on with Zoomingo was in terms of achieving product market fit was really tracking our retention. And the way I talk about it in my book is to crack cohorts of users and track the usage from day zero to day 30 and beyond.

And there is a magic rule that I talk about in my book, the 40, 20 10 rule. So you want to see 40% coming back on day one, 20% on day seven and 10% on day 30. And if you achieve that level of retention, then you can get to becoming a top 5,000 app. We got very close to it, but we didn’t quite hit that mark and then that’s one of the reasons why we didn’t see the hockey stick growth that we wanted to see.

Ishani Ummat: It’s such a good early building early hygiene around being able to collect, track, and then report those metrics is such an important part of company building that I think people sometimes under appreciate that, oh, in this era, of product lift growth, then you have to understand how that product is interacting in the ecosystem. And so that’s such a well-taken and a good point. And obviously from the investor side of things, I’m always looking at metrics. And that level of hockey stick growth. And obviously there are deviations to that model and to that narrative of continually growing so fast and outsize growth, but I think it’s this responding to what you’re seeing in the market, being able to track those things, lets you say, hey, let’s make this adjustment and then you get back on track.

So now fast forward you are, you’ve had this sort of incredible foundational learning and career at Microsoft. Now started three companies and had various outcomes and exits from them. But again, so much learning along that journey. And today you sit as an angel investor through one of the local organizations, TiE. You’re giving back to that community and those, the serial, and set of entrepreneurs that are in their local here in the Pacific Northwest, which we love with our sort of vision of giving back and building the Pacific Northwest tech ecosystem.

We’ve also done a lot of work in build and helping build that angel community through meetups over the years, which I’m sure you’ve attended. And our pioneer fund most recently, we ran a survey for an angel investors locally in Seattle. And then in your book, you did talk about this idea of these technological shifts and whether that is from the entrepreneur or investor side, I think an incredibly important component of what you have to believe for starting or investing in a company.

Shirish Nadkarni: Absolutely. I’m a big believer in the opportunity that technology shifts or platform shifts enable and how you can use that, disrupt existing incumbents as well as build totally new solutions that can leapfrog what incumbents are providing in the marketplace. So that’s where I look for at now as an investor is, are you taking advantage of some technological shift that you are the first to really adopt and use to disrupt the existing players in the market?

Ishani Ummat: Tell us a little bit more about that, what are the technological shifts that you’re excited about? Who are the types of entrepreneurs and what are they taking advantage of in Seattle today that you are getting most excited about and seeing a lot of energy around?

Shirish Nadkarni: Yeah. So I invested in a number of companies here locally that I’m really excited about. There’s a company that I was an early investor in called Ally which is it also received funding from Madrona ventures. And they are a SAS solution to manage OKRs or Objectives and Key Results, the company’s doing phenomenally well. And I see them applying AIML to provide more insights and actionable actions. Individuals and so forth.

There’s another company called Bloomz which is an educational space. It’s a communication platform for teachers to communicate with parents. They are in over 25,000 schools across the US. They recently won an RFP for the state of Texas to be the sole communication platform for schools in the state of Texas. So I’m really excited about them.

Then I was excited to see I was an early investor in Safari, they announced the acquisition by Microsoft. And again, they’re applying AIML, which is again, the technology that I’m a big believer in to provide actionable insights on spend data within corporations.

Essentially I’m looking for companies that are either taking advantage of AIML or moving legacy software to the cloud. Those are some of the types of technology platform shifts I’m looking for.

Ishani Ummat: So nicely dovetails with many of our investment themes here at Madrona. We’ve focused so much on infrastructure, intelligent applications, cloud, native applications, and now this sort of next generation of artificial intelligence machine learning (AIML), natural language processing, unlocking new use cases in different verticals that we may not have thought of before. One, we’ve spent a lot of time on recently is in the life sciences, for example there are countless examples that we could go on and highlight.

It’s been so nice to hear your story Shirish and congratulations again on launching your book.

And we’re so excited for it to come out in a more public way.

Shirish Nadkarni: Thank you very much. Great to be here.

Erika Shaffer: Thanks for joining us for Founded and Funded. If you’re interested in checking out Shirish’s book From Startup to Exit, you can look in the show notes and there will be a link to the Amazon page.

Till next time.

Starting a company is a lonely business. Finding co-founders can be the solution to this – but what if you don’t know anyone who fits the bill? Linda Lian of Common Room set out to build a company and recruited her co-founders one by one. Hear her story and theirs in the latest Founded and Funded podcast. Linda sat down with Madrona’s Shannon Anderson and then we checked in with co-founders Viraj Mody and Francis Luu.

Madrona works with founders from the earliest stages and has helped founders identify possible co-founders and those crucial early employees. Listen to this conversation to hear Linda’s approach and how the future co-founders at first ignored Linda and then dove in to the challenge due to her persistence and vision.

Transcript

Erika: Welcome to Founded and Funded, I’m Erika Shaffer from Madrona Venture Group. Today on the podcast, we talked to Linda Lian, Co-Founder and CEO of Common Room, a company that as Linda mentions in here, Madrona has been working with in funding since the negative day one. Common Room is working to build a platform that enables brands to more easily connect with their users. The company came out of Stealth in the spring of 2021 with $52 million in funding from Greylock Index, Madrona and others.

We have a deep relationship with Linda in part because she used to work at Madrona. She was an associate working with entrepreneurs on new investments and our existing portfolio companies. From there, she went to Amazon’s AWS group and then she left to build Common Room. In this conversation, Shannon Anderson, our Director of Talent, talks to Linda about one of the most important elements of building a company, finding the right co-founders. Linda went about this in a slightly different way than we see with most startups. We also talked to two of those co-founders about how Linda approached them and their first responses, which was to ignore her for various reasons, and their decision to join her in founding Common Room. The conversation with Shannon and Linda is interspersed with Shannon’s conversations with Francis Luu and Viraj Mody, two of the co-founders that Linda recruited.

There’s a little bit of musical interlude to indicate when we are making a switch, we’re going to start off here with Shannon and Linda speaking. Enjoy!

Shannon: I am so glad you are here. We’re having so much fun working with you. I want to start off here with you. I just want to get a baseline for who you are and understand your journey. My question is, what is your why? In other words, Linda what kind of problems do you tend to find yourself solving? Another way to think about that it is, what are you known for?

Linda: Hey Shannon. It’s really awesome to be here with you today, talking about the Common Room journey which, Soma and Madrona has been part of since day negative one. But Shannon, to answer your question, I wish I knew myself better. It’s a big question, but I think that what really drives me, and it has from an early age, is to build something of value to prove that I can do it. I think that a lot of entrepreneurs might have a certain chip on their shoulder where the more that someone tells them that something can’t become a reality, the more you want to make it real. So I would say it’s been a combination of, just wanting to build something of value and the desire to prove anyone wrong who says that, that can’t happen.

Shannon: Yeah, I get it. Wanting to prove yourself is such a motivator. It’s an intrinsic motivator, right? It’s not, it’s a little bit external, but it’s really inside of you proving to yourself and to others that you can do it. What I’d love to understand is how your career has reflected these motivations, right? So, as you think about, why you chose the school you chose and the program that you chose, how you ended up from, job A to B, you ended up at Madrona, as an investor, and then you went to Amazon to be a product manager, and now you’re founding your company. I’m curious what, in your mind, as you look back, are those common threads.

Linda: So I think for me, I’ve always had this like insatiable appetite to look at things from a 360 perspective. By that I mean, I’ve had a nontraditional career in that, I have done a lot of different things. Sometimes I call myself like a ‘jack of all trades’ master of probably nothing.

But as you mentioned, I started my career in investment banking doing really traditional mergers and acquisitions and really large, cross border multi-billion dollar deals in very stable industries. And having had that experience, I think it was incredibly valuable to be able to strategically understand the value of a company from simply looking at its financials.

But what it made me realize was, I had this hunger to see the other end of the spectrum, which was how can I work my way from like this late stage, massive corporate clashing up against each other kind of world to go upstream continually to where, the source of where ideas become real.

I’ve mostly spent my whole career I think, working backwards and trying to get to that source going earlier, earlier stage, after my time at Morgan Stanley and investment banking, I went to a late-stage startup called Lookout Mobile Security. and still at that point, the company was a couple of hundred people.

I felt like that was still feeling like a company that had already figured out a lot of things. And of course, we now know that companies are never fully figured out, but I think at that time I just had another sort of push and urgency to go earlier and I never really tried to stay in the same role.

I think I always tried to maximize for learning and to me after a time in finance, I felt like I didn’t necessarily have the skillset or the experiences that I wanted more on the outward facing thought leadership, business development, content marketing side of things.

I felt like that was just an area where I was intrinsically uncomfortable and I think early-stage investing enabled me to leverage my sort of finance assets and experiences, but also couple that with, the day-to-day work of being an investor, which I don’t know if many people know this, but is incredibly, outward facing.

It has a lot of like mappings to what I would consider in a more traditional company to be almost like business development or, more external facing type functions. And then again, it’s after a couple of years working with Soma and the rest of the Madrona team I just felt like I wanted to get back into being where the action was, rolling up my sleeves, building within the context of a company. So when AWS offered me the opportunity to join them and lead product marketing for Serverless, which was at that time growing extremely quickly and was in this completely new category that was still being created, I jumped at the chance to do that. I think it’s really that that ability to take a risk and not worry about having this traditional more linear career path that I think has enabled me to be a better founder and to be a more empathetic leader and I’m still figuring out all those things. I think having that diverse background and perspective has been really helpful.

Shannon: Yeah, that makes a ton of sense to me as you walked through it and this whole working backwards concept of trying to get closer and closer to the source of where our company originates, or at least where our product originates.

So, at AWS you’re building the VM1 and now you’re at Common Room and you couldn’t get any closer to the metal than Common Room, because that was an idea that you had and nothing more at the time.

Linda: Yeah, exactly.

Shannon: Yeah. So that’s great. So, let’s talk about Common Room.

When you started Common Room and you had decided that you discovered a problem that you were passionate about solving in terms of a customer focus, did you start off thinking that you were going to be a solo entrepreneur founder, or did you have other ideas for what your early team might look like?

Linda: Yeah so I think despite having been an early stage investor and having seen this from the other side of the table, it’s never as real as when you’re trying to get something off the ground and you’re asking yourself, I have a problem that I want to solve. I understand and have empathy for a specific customer set, but I may not have the necessary skills to make this a reality or if I were to try, it would be a sub-optimal experience because I am not an engineer, I’m not a product designer, and I think it’s hard to believe that anyone wants to start a company as a solo founder.

Starting a company is a scary experience. It’s a leap into the unknown. It always feels better to do it with somebody at your side, but oftentimes, for one reason or another, you do end up being alone at various stages in the early company building journey.

I think for me there’s two paths that every founder or founding team can take, they can choose philosophically to build everything themselves and do what it takes to, learn new skills. And like the example here would be, I would design the product using pen and paper, even though I’m not a product designer or they can philosophically decide I’m going to identify what I’m good at.

I’m going to spend time doing what I’m good at on behalf of the company. Because I believe that if I can leverage my super power for the company, that’s going to be best for the company. And I’m really going to take a lot of time and effort to build a team around the things that I don’t have as much strengths and capabilities in.

I was philosophically very much in the latter camp and I think one of the first things that I did after we closed our C round was I set out to find the right co-founders on and I decided early on that the first co-founder I needed was in product design. I think this isn’t obvious, but with our product, Common Room, which is a new customer journey platform for community in order to enable companies to build and nurture and engage their thriving communities of end users, it was very important that we had not only at delightful product experience, but one that required a rich set of workflows and interactions and a highly social kind of way to represent community because community is all about people, content, and communication. And so with that in mind I set out to find my design co-founder, which it took months, and it took a lot of work and it took networking and pounding the pavement and cold outreaches and having lots of conversations that went nowhere.

But when I found Francis who is my Design, Co-Founder it almost was like an instant fit in terms of our working styles, the thought partnership that we had and his experience and background having been at Facebook for over a decade recently, leading design for groups and communities and also yeah, chill out there.

Shannon: That’s amazing. Like when the first time, the most recent time I spoke with you about your team and I had seen how much progress you made. The first question I had was so you’ve got three co-founders at this point, you’ve got Francis, who’s your designer co-founder, you’ve got Viraj Mody, who’s your Engineering Leader and Tom Kleinpeter, he’s also Engineering. And so you’ve got like a very, like an all-star team with incredible pedigrees. And if I remember correctly, you did not know any of these folks until you reached out to them? All three of them, if I remember correctly, were cold calls, can you talk about, let’s start with Francis. How did you know what you were looking for so that when you met him, you knew he was it? And then how did you do it? How did you go about it? Like literally, like how many emails?

Linda: I think that I knew I wanted to work with somebody who had a, like an intuitive understanding of community. That was the thing that I felt was the irreplicable or incredibly special quality that, like you could go one of two ways with product design for Common Room. You could think about it okay, we’re building an enterprise SAS product and platform that is meant to cater to companies and organizations.

And so I’m going to, bias towards finding someone with that type of background, or you could say, because we’re building a community platform that is meant to enable other organizations and enterprises to better engage and nurture their communities. I’m going to be biased towards, someone who understands community.

And so for me, it was a no brainer in that. I believe that there are many people who understand the B2B SAS motion, but there are very few who have a deep empathy and appreciation for community, which is an incredibly amorphous and highly fuzzy word, but it combines things like social communication, content consumption, content exploration this concept of knowing who people are, hearing what people say enabling everybody to feel supported and heard and connected.

And that, that to me was like a special skillset that was really hard to find. And so I tried to find people that, might have that. And it was really hard. I don’t think I found really anybody except for when I met Francis. So the process by which, I was able to team up with Francis was I messaged him on LinkedIn in a cold outreach message and he didn’t respond. And I continued to make progress on my own. And a couple of months later, circling back, I messaged him again and I said, “Hey I messaged you a couple months ago. I’m reaching out again, would really love to chat more about this if you’re interested”. And to his credit, he just had his first child, Ben with his wife, Lisa. And so it wasn’t that he was ignoring me, he was just doing a much more important thing of being a father.

But he eventually did pick up my call. We went and grabbed coffee, I think, the week before the pandemic happened. So I did get to meet Francis in person, which I think, we just started jamming and the thought partnership was super natural. And he instantly got what we were trying to do, and it just worked out and it was always very frictionless, and I think we align on values.

We talked about what it meant to build the business, all the downside and upside scenarios. And that’s one of the things that I always value with all of my co-founders of frankly, our entire team is that we can speak very transparently about all the things, and I think that level of trust is just super important.

Shannon: I’m really curious to understand the experience that Francis Luu had, not only being recruited by Linda, but some of the reasons that he found this opportunity so compelling. Francis is the Co-Founder and Designer at Common Room and he was the first person that joined the team.

Francis, welcome to our podcast. How are you?

Francis Luu: I’m doing well. How are you?

Shannon: I’m Great. I really wanted to ask you about your recruitment journey coming to common room. It’s actually pretty unusual. And what I’d love to do is ask you about your first interaction with Linda, that, this story goes both you and Viraj have the same story. She reached out to you and initially I think you, you did not speak with her, but at some point you finally, somehow she converted you into a conversation, a coffee chat, and then, and then the rest is history. So I’m curious, what changed your mind to talk to her? And what were your first impressions once you finally did make that step?

Francis Luu: Yeah, absolutely. And just to, as a bit of context I think this will definitely shed some light on Linda’s claim of basically us ghosting her. So yeah, let’s take it back a little bit. So June of 2019 my wife and I actually had our first kid and I promptly went on parental leave and around that time, I’d already then wondering if I was ready to take the next step. So I wanted to really, in a way, live that, and I think the parental leave and the very gracious benefits allowed me to really just live that without making a big leap or guessing.

So I did the stay at home dad thing for a bit ended up actually officially leaving Facebook in November and then, just continued on and I’m like, this is great. This feels like a next, a good sort of way to evaluate next steps for myself. And yeah, it was having a good time learning how to be a dad and. Understanding that it definitely isn’t a break at all. It’s a ton of work and a ton of different work. I’m just so grateful for my parents. I unfortunately have to go through it myself in order to learn these sorts of things, but better late than never.

So I think it was around February that’s I just randomly decided to log back into LinkedIn. I haven’t really checked in on anyone, when it came when it came to work and I saw it obviously a million messages I think people had seen that I’d left and we’re curious to reach out and everything. And right near the top of the inbox list was someone named Linda that had reached out and that hadn’t just reached out, this was her second time reaching out. And I actually completely missed her first message.

That was, I think back in November, December, she had mentioned that she was going to be leaving AWS, had an idea and really wanted to get some of my thoughts around it, given that the last two or three years for me at Facebook was actually working on the grips of Kennedy’s product. And I’m like, “Oh My God, I’m so sorry. I totally ignored your first message. I wasn’t aware of it. My deepest apologies”.

What was actually funny is that you can tell there’s a difference between message number one and message number two. Message number one was like, I think I’m going to leave. I have this idea. And then the most recent message right around the February timeframe was like, I started a company. I’d love your feedback on what we’re working on right now. So there was clearly this sense of progression and I’m like, oh, okay. If she just wants some feedback and some ideas more than happy to help out, I guess it’d be nice to use my brain again for a little bit and not just be completely to a completely in the dad thing, even though that was, that’s been a lot of fun up to that point.

So yeah, I, I reached out, reached back out, apologized profusely and we figured out a time and a place to meet, and it really was as simple as that. And then we saw each other in person and shared a coffee for about, I think it was a good hour and a half, two hours that first time.

Shannon: Francis it’s interesting. Linda used the ‘I’d love your feedback’ tactic. So tell me about that tactic versus maybe another tactic she could have used, which is, I want to recruit you. Would you have responded differently?

Francis Luu: I think so, especially at that point, I had been tinkering around with the idea of perhaps going back to work, but I wasn’t ready because I was really enjoying just staying at home, being with the kid. And I think the barrier to entry, hearing something like, oh, ‘just wanted to get your thoughts on something I’m working on’, I think made it quite a bit easier to say yes. Yeah, of course, ideas and feedback can be a very casual thing. When it comes to recruiting, that could be a bit more of a commitment even just saying yes to a conversation.

Shannon: The interesting thing here is every solo or, co-founding team that I’ve ever talked to says in some way, shape or form, we want to go hire the best XYZ out of you name any, big company, Google, Facebook, Amazon, Convoy and in through more local companies. And, but you did it. And it’s, I always discouraged okay, listen, it’s not about the pedigree. It’s not about the fact that they work at Facebook, that’s a safety net. It’s almost a lazy way of specking out the wall saying if they’re good enough for Google, they’re good enough for me. You have a napkin with an idea on it and a little bit change in your pocket, not to underplay that, but, what, how did you do this? What is your secret?

Linda: Yes. So, when we teamed up with Viraj, he was still at his last role. And I think with anybody that you’re trying to, attract, whether they’re, a new father or they’re in a really busy job as the technical advisor to the CEO during a pandemic. It’s all about building that relationship, aligning on values and if they’re, that person’s not ready to take the leap, then showing them continued progress over time.

So, with Viraj I reached out to him, he might have not responded, but I did reach out again and he picked up the call and we talked about the idea, and he felt like it was really interesting. I knew that he would potentially find it interesting because, he had experience as the co-founder of a startup which was built around the music community. So I knew that this was a topic that he had thought about before and had lived. And I think instantly when we were chatting about Common Room, what I recognized was that, like Francis he had an intuitive and deep and instant connection to the problem that we were solving.

Not only had he built, Audiogalaxy with Tom Kleinpeter, who is now my other Engineering Co-Founder in the kind of music community space, but like specifically Viraj and Tom had also lived the journey at Dropbox of product led growth and what a user communities could mean for a company a modern SAS company. And so again, it was where, Viraj was really interested in the idea. We had amazing thought partnership. He was bringing new ideas that I hadn’t thought of to the table and when you recognize that kind of energy in a conversation, it sticks with you because you’re pounding the pavement, as you mentioned with just a little change in your pocket and you meet a lot of people and have a lot of conversations where that energy isn’t there.

And so if you feel that spark that’s worth fighting for. And so Viraj, Francis and I were chugging along and we were making a lot of progress on our own with respect to customer discovery and really honing in on the problem. And just talking to a lot of potential customers, many of whom we’re partnering with still today. And I think with Viraj, it was just going back to him, a couple months later and saying, hey, we’d love to catch up and share our learnings because we’ve learned a lot. And I think, with a rush, I think he was positively surprised by just how much progress we made.

And it’s always that it’s the concept of hey, come on board because this bus is leaving the station and we’re going to continue to drive this forward so you can’t ever have the mindset that you need anybody or anything to move forward and continue to build. You just have to keep going. And the right people will usually end up coming along, even if you have to play the long game and we still play the long game today, right? Like we’re always playing the long game, whether it’s with team building or earning the trust of our customers.

Shannon: You hit on something earlier that I really wanted to dig in on just for a moment. The idea that I know that Viraj, in looking at his profile on paper, I know he looked like he might have some of the same interests that you’d have in community. And that’s why he just, a little plug for Madrona, I went into the things that we do for our founders and try to help you with recruiting. And so we gave you a short list of people that we thought might look a little bit like what you had described as the kind of people that could help you build this thing. So his name showed up on that list, but that’s, identifying what somebody might be interested in.

It’s different than really discovering the truth of that. And I always think of everybody, including everybody here, listening. Everybody has a career problem all the time. And the career problem is that delta between where you are right now and where you want to be like current state versus future state. And we’re always growing and we’re always trying to get to that future state. So there’s always a problem we’re trying to overcome where whatever we’re working on, we want to learn something and then move onto the next thing.

And so all of these things lining up is almost a little bit like you think of it as magic, but it’s not, you’ve got, Viraj and you’ve got Tom and other than that they both know how to solve or a lot have thought a lot about how to solve these community problems. It’s, there had to be some other things that they were hoping would be present in working with you at Common Room, that wasn’t happening for them in their current role. How did you discover that? How did that conversation happen, in real time, when you were getting to know each other?

Linda: That one’s tough. I don’t know Shannon, if I have the same, like jujitsu as you it was probably yeah, it was probably unconscious on my part. Like maybe I was listening for the desire to build or the desire to start a company or the excitement around the actual work that company building is, which is team building and customers and I don’t know that’s, when you’ll definitely have to ask them.

 

Shannon: So Viraj thank you so much for joining me. I’m excited to talk to you about this topic. We talked about it in the past, but without the recording button on. So I really wanted to get your story. I had a chance to speak with Linda about her impression of the, the recruitment process with you. Tell me about your first interaction with Linda of course, the story goes that she reached out to you, maybe you weren’t necessarily responsive and so I’d love to hear what changed your mind about talking with her and, what were those first conversations and what were your impressions?

Viraj: Yeah, for sure. She emailed me just before the world locked down. And when I first got the email, it was definitely interesting but also one of many that I usually receive. And so I was like, hey, I’m just gonna ignore this for a bit, but I did respond to her saying, hey, this sounds pretty cool, I’d love to get to know you, but also like it’s unlikely that I’m going to do anything now. And it took us a while to get it scheduled. I was dragging my feet because honestly there was no urgency on my end to do this, but also the COVID rumors had started and people were starting to see the world going to lockdown. So like work had gotten really busy, too.

It took maybe 20, 25 days since she emailed me to actually get on a call with her. I really enjoyed that conversation. I could tell pretty quickly that, she knew what she was doing. If you know, if you know, Linda, you know, all her strengths, you can pick up pretty quickly. And so I left the conversation feeling pretty impressed by Linda, but also I was like, Hey, look, this is too early. I am really not thinking about doing a startup thing just yet, because I got a day job and it gets pretty busy. So I filed it away as something that was more interesting than the average email I get which I mostly don’t even respond to. And then just, things went to 11 at work. The world’s shut down for real.

The company I was at, obviously like every other company during the time, we were trying to figure out how to cope with everything because everything was up in the air and unknown. So things got really busy. I basically ignored reaching back out to her. I would have been busy, but then a couple of months in, she emailed me with a pretty solid update on what she’s been up to. Some of the things she’s learned about the community space, some of the customers she’s been talking to. And that was the first time, and I was like, okay, look, I probably want to take this call and reconnect with her because clearly she’s going to get this done and it lined up in some ways with what I was excited about. So it wasn’t like a complete, Bitcoin or AR VR thing that may have been interesting in its own , but I had no interest into like this was definitely something I had interest and experience with. And so the, hey, look, it’s worth getting in touch with her again and then the ball started to roll pretty quickly after that.

Shannon: That’s really interesting Viraj, Linda told me the same thing. She said she, her secret sauce here was really persistence, but not an empty persistence. It was one of providing something to you in the terms of an update. How does a founder get the attention and I’m not trying to be too flattering, but you’re a force, you have a, you are an accomplished highly pedigreed guy and you’re no lightweight. And Linda is no, she’s wonderful, but she’s no more special than every other, brilliant founder. What was the transition for you from ignoring her emails to, I gotta get in on this?

Viraj: I think for me, particularly the timing lined up with what I had wanted to do eventually anyways, so I’m pretty entrepreneurial. It was mostly a question of when not if I was going to do my own next thing or, join like a really early-stage company of some sort. So, I had clearly been like in the headspace of wanting to go back into entrepreneurship and then meeting with Linda and keeping up to date with what’s going on with her helped me see that, okay, this is a person who’s similarly motivated and who’s similarly diligent.

I would do what she did. Like just because somebody says no one to blows you off once doesn’t mean they’re not interested, doesn’t mean you walk away. So I saw a lot of what I would do in what she was doing, but also very complimentary, I come from a product and engineering background, her background is very different than mine. And so the thing that connected the dots for me was, hey, look, I am in this head space where I know I want to do this eventually. And in fact, until recently I was talking to Tom, who I was almost certain I want to do something with again, and from a space perspective, from a business opportunity perspective this stuff seems pretty legit, she was able to describe what she was doing, talk precisely about the progress she had made versus, I get emails from people that are either just like name dropping, like nobody’s business or using 300 words and I still don’t know what they were trying to tell me.

Linda’s like that, it’s very precise. So yeah, it just. It was the right thing to get me to start talking to her. And then obviously once you start talking to somebody and get to know them, then the equation is completely different than now.

Shannon: Yeah. That’s great. That’s perfect. So you referenced Tom Kleinpeter, and he is, was actually your co-founder at your previous company that you did together, which was Audiogalaxy. And it’s interesting because I want to move onto another topic, but I want to ask you, did you come together? Was it a condition of you coming that Tom would come with?

Viraj: It was not a condition of any sort. It was one of those where if you can get Tom and me together, you’d be a fool to pass on that opportunity, no matter who you are. This is like plainly speaking. Both of us have very different strands. Both of us complement each other really well and you increase your odds of success exponentially by having the, both of us on the team. And from my perspective, obviously I wanted to work with Tom again.

And if I was going to do this with Linda, I would want Tom to be on that team. Cause why not? A team is successful because of the various skills that people bring to the table and the complementary skills they bring to the table, it was a no-brainer from my perspective, I remember talking to Linda instead of breaking out of character for a second, hey, I’m just going to objectively tell you that if you could get the, both of us, you’d be a fool to pass on this really is the right thing to do. And to her credit, like she got it, we chatted about it and she had some questions about how we’d work. Cause it’s scary, if, bringing in one co-founder’s scary and bringing it in two at a time is even scarier. So I could totally see her perspective, but it was such a great conversation, walking her through my thought process, having her get to meet Tom, get to know him. I think it all worked out at fabulously.

Shannon: That’s awesome. It worked out great so far, so good. And it’s interesting because Linda recruited you out of Convoy, she recruited Tom out of Dropbox. Both of you have worked in enterprise as well as startup situations. What’s the difference, like how would you compare and contrast for somebody for first time co-founder coming out of a Microsoft, maybe not having done a startup before?

Viraj: The thing that’s common is you need to know how to build. At a Microsoft, you probably can’t get by and get too successful without actually being able to deliver. And that’s the same thing with a startup. You have to ultimately deliver. Talk takes you on so far, even at Microsoft, even at a startup. But other than that, I think it’s developing completely new muscle.

So it’s I’m probably, I could probably come up with an analogy, but I think the bottom line really is. You have to be willing to understand how the rules are different or how the needs are different and be able to adapt. And if you can get your head around that, I think the context and the experience you have working at large companies can be modified and reapplied to having really strong impact at small companies where almost certainly will not work is expecting that you would work the same way you did at a large company, and then expect to have success at a startup. I’m not saying it cannot happen, but I’d be surprised if it happens.

Shannon: So Viraj also, I want to just give you a plug. You are in the co-author of a book called Technical Recruiting and Hiring. Ozzie Osman is actually like the main writer and then you are one of the co-writers and this is published by Holloway. And it is a phenomenal book. It is my Bible. I send it to every founder that we invest in and I use it as our textbook, as we walk through various things that they’re learning and you wrote the campus and university recruiting piece of it, but I know you have expertise all along the way.

So I just wanted to say I think you really know, how to put your money where your mouth is when it comes to this topic. And so finally, I want to ask you about the future of Common Room and you guys are a little over a year into it. You’ve just come out of stealth mode. You raised your B round. What keeps you coming to work every day? And what are you most excited about in terms of the mission itself?

Viraj: When I was a kid, I used to love Cadbury chocolates. They were pretty big in India. And I was so passionate about it, that I sent a letter to the MD of Cadbury, asking them to invent. It was something with sprinkles and cashews and something. I don’t know the details, but I know I distinctly remember writing to them. And what was the most amazing part of this as I got a response back from them and they invited me to their factory and I toured it and it was. It was just so phenomenal. Even today, when I walk into a store, I will instinctively just pick up a Cadbury bar. I don’t like the American version as much as I like the British or the Indian version, but still that won’t stop me from doing it.

And so that little act of kindness or customer relationship building that happened when I was a kid, left such an impression on me that I’m essentially, I feel like an extension of the company for no logical reason other than I got to visit the factory and I got a letter from somebody high up there. But if you step back and think about that motion they made a lifelong evangelist or champion for their chocolate bar through a tiny personal interaction.

How do we build software to scale this so that everybody can have their customers become an extension of their company? You call it community motion, you call it bottom-up motion, you call it product led growth, it doesn’t matter what you call it, the dynamic I cared about really is that look; treating our customers as like a revenue machine on a transactional interaction paradigm where it’s you have a problem, I haven’t answered and let’s not talk to each other ever again, like that just feels so old.

And so that’s the thing that I connect the dots with where I’m like, if I can do a little thing, everybody intellectually understands, having our customers be your champions is great. How do we actually make that happen? How do we teach the world? How do we build software? To make that happen there, wasn’t the kind of things that excite me. So from a mission perspective, obviously that’s what brings me to work every day. Part of it also is the team, when you have fun working on stuff with people, it doesn’t have to be easy. It doesn’t have to be hard. It just has to be fun.

With startups, a new curveball shows up every day, multiple times a day. That’s part of the fun for me . Look if I can deal with this with a group of people who are similarly motivated and passionate. That’s perfect. What else could I ask for?

Shannon: That’s great. We are really excited to watch you all on this journey. I have to tell you before we go, I do want to ask you, did they make the candy bar that you suggested?

Viraj: No, they did not. My ideas were not that great back then or now, but at least I had ideas.

Shannon: That’s right. I just wonder, because whenever anything with chocolate and nuts, it sounds great to me, so

Viraj: Yeah, no, pretty sure they had professionals making decisions for them, but

Shannon: Viraj, I’ll talk to you again in a year or so when you’re down the line and maybe interview some of the rock stars that you haven’t even recruited yet and find out how this is all going, but in the meantime, I wish you all the best of luck and thanks so much for your time today.

 

Linda, a couple of things that I heard here today is that, you were pretty relentless. First you identified that basically, the skills and the motivators that you needed to put on your team to either fill the gap and what you were missing or round up the team. Then you iterated on that by having conversations with people and you were not just having conversations, but you were always in recruiting mode and earlier you refer to this thing called the ‘slow poach’. And I think that’s interesting because it’s, you don’t just go into recruiting mode for when you need somebody. You always need to be recruiting. And so when did I, when I wanted to ask is if you could give our listeners, two or three or four things that you consider to be your tenants or your operating principles, as you continue to move your company forward, as you probably have 20 people that you are sending emails to and pulling along, I’d love to know like, how you think about this just in a summary?

Linda: Yeah, I think for me, it’s just about two things. Building a relationship based on transparency and trust, having plain direct conversations about what it means to join an early-stage startup and the day-to-day work, like I’m always biased towards transparency. I don’t oversell anything. In fact, I undersell things. And the, secondly, if they’re not ready to leave, then continually keeping them updated on our progress. And demonstrating that rapid clip of, that acceleration of progress day after day, week after week, month after month. And hoping that at some point, those stars will align and we’re always, you know whether or not we’re a good fit for a good person today. We’re always going to be a place that welcomes great people at any stage. And so that’s what I bias towards.

Shannon: And thanks so much for sharing your story today.

Linda: Thank you so much, Shannon.

Shannon: You’re welcome.

 

It’s so interesting to talk to Linda Lian about her experience, recruiting Francis Luu, Viraj Mody, and Tom as well. And it’s interesting that the stories actually match up quite well, but one of the things that Linda wasn’t able to give insight to is what were the things that compelled each of these people to join her team?

And she, I think she knows instinctively, but like any great founder, any great recruiter. They may know it inside, but they haven’t really bubbled it to the surface. And one of the things I noticed was a real contrast in the reasons that Viraj and Francis joined Common Room. Viraj is really motivated by making great software and creating amazing customer experience. And he told this story about Cadbury as that’s the kind of product and kind of loyalty that he wants to build and doing that through great software is his mechanism for building that. And that’s a very compelling mission and it’s just as valid for what Common Room is doing.

Francis’ motivation, which is much more about his passion around community and building communities and groups, and some of the work that he’d done at Facebook and the markers for his motivations are really easy to see on his resume or his LinkedIn profile that he’s all about creating community with the software. Just working at Facebook is the tell. And when you look at Viraj, you can see the same mark different markers that actually indicate that his motivations are all about building great software building great teams.

So, in retrospect, after having this conversation, I can see very clearly that those two areas of motivation, the problems that they were trying to solve, I guess, in their career, like, what do you want to do next? What are you running toward? They each described them differently, but those are both compelling and interesting for them at Common Room and that’s what makes a great two-way fit.

So, for those founders out there listening to this, or for those folks thinking about becoming a co-founder with someone like Linda, the path that you get there, isn’t going to be straight, but it’s all about finding that two way fit and working together to solve problems that you all care about in a way, and doing it in a way that aligns with your values and your interests.

 

 

Erika: Thanks for joining us for Founded and Funded. If you were thinking of starting a company, reach out, as you could tell from this podcast, we really work for our founders. We worked with Linda early on, helped her identify possible co-founders, and then funded her company. It doesn’t always work that way, but we are very invested in the success of the Seattle tech ecosystem and that means making a lot of connections possibly for you.

Reach out to [email protected] or to [email protected] to learn more and thanks for listening and please share this podcast and like it on all the different platforms, thank you.