Category: Podcast Episode Transcript

In this episode, Nataraj is joined by Zach Lloyd, the founder and CEO of Warp, a company developing an intelligent terminal to modernize the command-line experience for developers. A former principal engineer at Google who worked on Sheets and Docs, Zach brings a wealth of experience to his mission of reinventing a tool that has remained largely unchanged for decades. The conversation delves into the evolution of the terminal, the profound impact of AI on software development, and Warp’s vision for a future where developers interact with their computers through natural language. Zach shares insights on moving from ‘coding by hand’ to ‘coding by prompt,’ the challenges of building a sustainable business model around LLMs, and his bottoms-up, product-led growth strategy. This discussion is a must-listen for anyone interested in the future of developer tools and the practical applications of AI in coding.

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Nataraj: Zach, welcome to the show.

Zach Lloyd: Thanks for having me. I’m excited to be here.

Nataraj: I was really excited to have you on the show because after the ChatGPT moment broke out, the LLM companies were everywhere. I think that’s the first line of value that has been captured. I was excited about the new types of applications that we will see, and the most bullish use case for me was developer productivity. The reason being, anyone who studied compilers will know that LLMs are actually looking a lot like compilers in terms of text completion and autocomplete. Then there’s this aspect of code being very deterministic. I can say something in English and it could mean different things for the same person in different contexts, but code is already logical. So if you are feeding a logical structure to the LLMs, it’s more likely that it performs better on code than on English language. That was my thesis. I think in some format, we are seeing the biggest use cases are around developing new products, especially for software developers. So I think a good place to start is if you can talk about what Warp is and how you came up with this idea of an intelligent terminal.

Zach Lloyd: Cool. So yeah, Warp is an intelligent terminal. The terminal, in case folks aren’t familiar, is one of the two most important tools that developers use every day. They use a terminal and they use a code editor. The terminal is basically the place where you tell the computer what to do. That could mean building your code, running your tests, writing internal tools, or interacting with your production system. So it’s a very ubiquitous and important tool for developers. It’s also a tool that’s kind of stuck 40 years ago from a usability perspective. It’s something that really has not evolved much from an experience point of view. When Warp started, our goal was to modernize this interface, make it more usable, and make it work more like a modern app. Even really simple things, like make the mouse work in the terminal. But as the LLMs have matured and come out, the product has become vastly different. At this point, Warp is a place for developers to talk to their computer and tell the computer what to do. Because they’re doing this through the terminal, there’s this huge array of tools that already exist in the form of these command-line apps that can take what a developer says in English and turn it into a series of app calls that do what the developer wants. That could mean setting up a new project, debugging something in production, or increasingly just writing code, which is obviously the biggest developer activity. So that’s where we’re at today. We think Warp and the terminal are an amazing interface for a developer to tell AI what they want to do and essentially have it done.

Nataraj: Developers are really unique; everyone is picky about their stack of tools. They have their own slightly different version of terminals or command lines they use. How does a developer use Warp now? How does the existing behavior of the terminal change by installing Warp?

Zach Lloyd: Great question. If you’re a developer, you can just go to warp.dev, download Warp—it’s a native app. If you’re running on Mac, Linux, or Windows, you just open it up and use it instead of whatever terminal you were using. Whether it was iTerm, the stock terminal app, or the VS Code terminal, you just use Warp. Despite being an AI-native experience, Warp is backwards-compatible with your existing stack. The way this works, really big picture, is a terminal is the app you run, and then within the terminal, you run a shell. Think of the shell as a text interpreter, so when you type a command, it’s the shell that figures out what program to run. Warp works with all the existing shells. A big product emphasis for us is to meet developers where they are and not make them take a step backwards in order to get all the extra benefit of doing this incredible stuff with AI.

Nataraj: So basically, you allow developers to bring in their existing nuances into Warp.

Zach Lloyd: That all basically works. For 98% of the stuff that developers have set up in iTerm or wherever, you can just open up Warp and it should just work the same, but also be better. At least that’s the goal.

Nataraj: A terminal is generally a little restrictive. Usually, they’re not intelligent in the sense that while some terminals let you easily reuse a previous command, you have to know the exact command. This becomes really hard when a developer is in the early stages of their career because you have to remember all those commands, or you’re constantly going to ‘help.’ If you’re using Git and trying to commit or do different things, you’re struggling to find the right command to do the right thing. What intelligence is Warp adding?

Zach Lloyd: Yeah, you’re absolutely right. One thing that’s really frustrating for beginners and experts is you open up the terminal, and it’s just a blank screen. If you want to get something done, you better remember what the command is. And these commands can become quite complicated. Let’s say you want to set up a brand new Python project. You have to install the Python toolchain, and then you might have to clone some Git repo. When you go to clone the Git repo, you might find that you don’t have SSH keys, and then you’re going to start Googling or go to Stack Overflow to figure out how to recreate your SSH keys to authenticate to GitHub. That’s annoying. That’s not what developers want to do. Developers want to build things; they don’t want to deal with all this incidental complexity. So what Warp does is you don’t have to remember the commands at all. You just need to know what you want to accomplish and you tell the computer to do it literally in English. So instead of typing a command in Warp, you would type ‘help me set up a new Python tool chain, clone this repo, make a new branch for me, make sure it all compiles and runs,’ and that’s it. You would hit enter. And then what the LLM does is it tries to figure out its context. The LLM might run ‘ls,’ it might run ‘git status,’ it will try to run ‘git clone.’ When it hits that SSH error, it’ll say, ‘We had an SSH error, do you want me to generate these SSH keys for you?’ As a user, you’ll say yes, and then it will remember the command to generate the SSH keys. It will basically do this with you until you get to the spot that you want to be at. That’s a way better workflow than switching context out of the terminal and looking this up on Google every time you hit some error.

Nataraj: There’s also been this huge integration between IDEs and terminals. Does that change how you think about Warp? Does Warp have to also now work on the IDE?

Zach Lloyd: Great question. A lot of people use the terminal in the IDE, and there are definite benefits to that. What’s interesting that’s happening in the world of AI-based development is that I think neither the IDE nor the terminal actually makes sense as the primary tool for the future of code. What makes the most sense is some sort of workbench where you as a developer just tell the computer what you want to do. The standard workflow for someone using an IDE today is you’ll open up all the files that might be relevant to building a feature, and then you’ll start writing a function or a class definition. You’re basically doing what I call ‘coding by hand.’ The world that we’re moving towards is one where, rather than doing anything by hand from the outset, you’re going to work by prompt. You’re going to describe the feature that you want to build in English, and the AI, with increasing autonomy, is going to solicit whatever information it needs from you and your environment, and then it’s going to go do that task. My hypothesis is that the IDE is not actually the right place to do that. It’s much more of a place for having a bunch of files open and doing hand editing. What you see in all of the AI-based IDEs, like Cursor, is that they are guiding users over to a chat panel where the user can, through conversation or prompting, build their feature. That chat panel is starting to look more and more like a terminal in its interactions. Warp’s approach is not to build an IDE, but to build something where a developer can ask for anything they want done and build the interface around showing the work that’s being done directly in that linear fashion. My vision is that these traditional IDE and terminal boundaries are going to blend into something oriented around what the best workflow for development should be in the future.

Nataraj: Historically, we’ve moved up the level of abstraction in development. We used to write HTML, then we came up with WordPress. For e-commerce, we went to Shopify. We’ve moved to a layer where we no longer use HTML directly. The end output is the same, but what you’re doing to get it has changed.

Zach Lloyd: Totally. Another good analogy is that back in the day, developers used to work in assembler language, which was very low-level. Then you moved up to a language like C, where you still have to know how memory works but it enabled faster productivity improvements. Then you moved up to a language like Python or JavaScript where you don’t have to worry about so much of the underlying system architecture. This is a bigger step because you can basically do it through English, but you’re lessening the barrier to working with code. I do think, for now and for the next couple of years, you’re going to need that programming expertise to build things of high complexity. It becomes more important that you know what’s going on because a lot of times, with this method of developing by prompt, the AI will do 80% of something and then get stuck or have bugs it can’t resolve. If you don’t know what’s going on, you’re going to be stuck with it. But the level of abstraction is definitely changing for developing software.

Nataraj: How has the feedback been from developers? And how is adoption coming? Are developers discovering it and then forcing engineering managers to buy your product, or is it coming from the top down?

Zach Lloyd: We’re mostly building for developers, so our go-to-market motion is bottoms-up, product-led growth. It’s going really well from a user adoption standpoint. We’re well into the multiple hundreds of thousands of developers actively using Warp, and that’s growing really fast. We have some people who are using it because they want a better terminal UX, and some are using it because they’re AI early adopters. Our strategy is to get a lot of developers using it, spread it wide, and get them paying for it. When we have enough concentration at a company, we end up having conversations with engineering leaders. We do have enterprise contracts with pretty good companies, but the primary motion is bottoms-up product growth. What gets people to pay us is getting them to an ‘aha’ moment in the app where the AI did something that blew their mind. It could be something as simple as fixing all of their dependency issues. A big part of what’s helped us grow is inserting ourselves into developers’ existing workflows in ways that are low friction but surface the value of AI with them doing almost no work.

Nataraj: What are some examples of workflows you’ve inserted yourselves into?

Zach Lloyd: A prime example is you try to build your code, you get a compiler error, and Warp just pops up a fix for it. As a developer, all I need to do is accept this fix. That’s very different from expecting the developer to know to type in, ‘Hey, please fix my compiler error.’ To the extent that we can hook into someone’s workflow, guess what they’re trying to do, and surface the AI as a fix, that’s the best way to get an ‘aha’ moment. I think that’s one of the reasons the first modality that really caught on is autocomplete—it’s just there, it’s no work, and it’s really low cost if it’s wrong.

Nataraj: Are you creating your own model or leveraging other LLM models? Which models are doing the best job for your use cases?

Zach Lloyd: The best model for developers right now is Claude 3.5 Sonnet. We offer it in Warp. We’re also offering for more complex tasks, users have the option to do a two-step execution where first they use one of the reasoning models to come up with a plan, and then we switch them to a standard LLM to actually execute the plan.

Nataraj: How do you think this will evolve in the next two to three years in terms of development? There’s this new phenomenon we’re calling ‘agents,’ where we are using high-reasoning models with traditional LLMs.

Zach Lloyd: The way I look at it, there are three main modalities that are important for developers right now. One is completions. The second is chat, where you’re pairing with an agent in an interactive mode. The third is a true agent with real autonomy. I think this is coming. In this world, you have to change the user experience to be based around higher latency interactions. What does that mean? It means if I’m asking an agent to build a feature for me, I don’t want to sit there and watch it do it. It might take five minutes to get a plan and another 10 to execute and test. That points towards a different interaction modality, essentially some sort of workflow management software, kind of like GitHub Actions. You start a job, it tells you when it finishes or if it hits an error, and you can have multiple running at once. I think another really important property is that when the agent fails, it’s not a pain for the developer to hop in and work with it to fix the issue.

Nataraj: Can you talk a little bit about cost? LLMs are costly, and the per-query price is not yet cheap enough to make a sustainable business. How are you seeing that play out?

Zach Lloyd: It’s a great question. Our pricing is based on a couple of plans for individuals and small teams at the $15 and $40 price points, differing mainly around AI requests. It’s a hard thing to price because the underlying price of these models is based on tokens, but pricing by tokens is too close to the metal and too far from the value to a developer. For all of our paid users, we have a pretty healthy positive margin, around 30 to 60%. However, it’s hard because the underlying models change both their costs and how much context they want to gather. We give all of our free users some amount of AI because we want them to understand the value and get to a moment where they want to pay us. I definitely think there’s a path to a sustainable business here, but it’s a bit of an open question exactly what will happen with model costs.

Nataraj: I always thought this dependency on LLMs could change completely if you adopt an open-source model and host it in your own cloud, then start to fine-tune your own models.

Zach Lloyd: Totally. If we were to take DeepSeek or Llama and host it, it’s a totally different level of control over the costs. You’re not paying a model provider. If you look at who’s making money on AI, it’s the chip makers, then the hyperscalers, then the model providers. There are a lot of people taking margin before you get to the app layer. We don’t do that right now because the quality difference of the models is such that our number one concern is getting users to realize the power of this stuff and convert them to paying customers. From a unit economic standpoint, we’re trying to stay breakeven and see what the right way to optimize costs is.

Nataraj: Is there any metric that you really focus on for your product? For example, how much time does it take for a new customer to decide to pay?

Zach Lloyd: One really interesting metric we’ve just started looking at is what percentage of things done in Warp are either done by AI or being asked of AI. In a normal terminal, it’s 0%. For Warp, it’s around 10% of things happening in the terminal right now are either the user asking in English or the AI doing something. AI engagement is the leading indicator for monetization for us. It would be a cool spot for us to get to where more than half of the interactions in Warp are happening in English or autonomously because of the AI. We’re trying to flip our users’ perception of this being a terminal that has AI to an AI interface where you can fall back to using the terminal if you want.

Nataraj: Can you talk about your go-to-market motion? Marketing for developers is a particularly interesting problem.

Zach Lloyd: About 80% of it is organic. We spend some money on sponsorships at GitHub repos and a little on Google ads, but the primary thing is organic. The biggest driver by far is developers telling each other about it. We’ve experimented with viral loops, like a referral program, and the ability to share cool things you do in Warp via a link. A really big thing is social media. The best thing for us is when someone does something super cool with our product and shows it to the world on Twitter or YouTube. For a product like Warp, you have to see it to get it.

Nataraj: How are you using AI, and did it change the way you are building your own startup?

Zach Lloyd: It’s an interesting question. We’re building an AI product, we’re all developers, and we all use our own product every day. There is a virtuous cycle: as the AI gets better in Warp, we do more of our coding, debugging, and DevOps tasks just by talking to our own product. Outside of our own product, there are a few AI tools I use. For example, I use a tool I really like called Granola, which is an AI meeting note-taker, and I just don’t take notes in meetings anymore. That’s cool, but it’s not like some of the stories you hear. I saw a tweet from the president of YC that in the latest cohort, for 25% of the companies, 95% of the code was written by LLMs. That’s not how it’s been with Warp. But we are adopting AI tools, and the primary one we adopt is the one we’re building.

Nataraj: Do you think we have hit a productivity level where we need fewer developers versus more?

Zach Lloyd: Not at all. We’re trying as hard as we can to hire developers. I think there’s probably a class of relatively simple front-end apps where you can maybe start to not hire developers. But for professional software development at a tech company, the impact of these AI tools is that it makes your existing developers more productive. The other thing is there’s basically infinite demand for software. Developing software is becoming more efficient, and there are benefits to that. Every company I know is trying as hard as they can to hire awesome software developers right now. I haven’t seen a negative impact at all in the type of development we do.

Nataraj: I actually think AI is at a stage where it’s sort of ‘draft AI.’ It gets you to 80-90%, but not 100%. That’s where the narrative versus reality is. You still need a developer to do that last 15-20%.

Zach Lloyd: I agree. I think it’s a mistake to think of it only as a function of the progress in the models. The models are only as good as the context that’s provided. Getting all the right context and knowledge into these things is a challenge. And then, the likelihood of succeeding at a task depends on the ability to specify it correctly. English is ambiguous, and people assume a lot of context that the LLM does not know. The fallibility of humans and how they communicate is still going to create work around this.

Nataraj: We’re almost at the end. What are you consuming right now? Books, podcasts, Netflix?

Zach Lloyd: I’m reading a totally different non-tech book called ‘Traveler’s Guide to the Middle Ages.’ It’s like, imagine you were traveling in the Middle Ages, what would that experience be like? It’s about people going on religious pilgrimages or traveling to the Far East. I like it because it’s an interesting reminder of how different an individual’s experience of the world was not that long ago. It’s history based on how people lived, not major historical events.

Nataraj: Are there any mentors in your career that helped you?

Zach Lloyd: I’ll call out a guy who’s kind of legendary in the tech industry, he’s now the CTO of Notion. His name is Fuzzy. He was my manager at Google on Google Docs, and he was one of the creators of Google Sheets. Most of what I learned about how to create incentives for engineers, give feedback, and get a team functioning at a high level, I learned from him.

Nataraj: What do you know about starting a company now that you wish you knew before?

Zach Lloyd: I’m on my second company, and I can tell you things I learned from the first to the second. The first one I failed at, but learned a lot. Really focus on team. Really try to hire great people, even if it makes you go a little slower, and hold that high bar at the beginning. Also, really try to work on as big of a problem as you can, which is counterintuitive to a lot of startup founders. Counterintuitively, the bigger swing you’re taking, the easier it is to get people to fund you and attract awesome people to work with you. People want to work on something really meaningful.

Nataraj: That’s a good note to end the conversation. Zach, thanks for coming on the show and sharing all about Warp.

Zach Lloyd: Cool, thank you so much for having me.

Zach Lloyd’s insights provide a compelling look into how AI is not just enhancing but fundamentally reshaping developer tools. The conversation highlights the shift towards more intuitive, AI-driven workflows and the exciting future for software creation.

→ If you enjoyed this conversation with Zach Lloyd, listen to the full episode here on Spotify, or Apple.

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Karthee Madasamy, a seasoned investor in the deep tech space, joins the Startup Project to discuss what he calls the “golden age” of foundational technology. As the founder of MFV Partners and the former Managing Director at Qualcomm Ventures, where he led investments in groundbreaking companies like Waze and MapmyIndia, Karthee brings a unique perspective shaped by decades of experience. In this conversation with host Nataraj, Karthee shares his unconventional journey from engineer to venture capitalist, the critical differences between corporate and financial VC incentives, and the challenges of launching his own fund. He provides a masterclass on evaluating deep tech opportunities, explaining why the sector is moving beyond selling technology to tech companies and is now being embraced by traditional industries, unlocking massive new markets in robotics, AI, and quantum computing.

→ Enjoy this conversation with Karthee Madasamy, on Spotify or Apple.
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Nataraj: How did you come into venture investing as a career?

Karthee Madasamy: It wasn’t planned at all. In fact, people who knew me from a very young age would have been surprised that I’m an investor or even a business person. When I was younger, the plan was to do a PhD and then go develop new technologies. That’s what I pursued for the first 10 years of my career: building new things in semiconductors and wireless communication.

I think it was circumstances where I was getting pulled up, going in front of customers, and leading people. I basically learned that maybe more than my technical capability to build things, I have other skills, which is what led me to do an MBA. I had a very clear thought that I wanted to come back to technology, but maybe more as a business person.

I spent a summer doing venture capital. Until then, I was a startup guy, just doing startup stuff, and then suddenly I’m evaluating startups. That was a lot more interesting because I could look at several different startups. Even then, I just jumped in, thinking maybe I’ll try this for a couple of years. There wasn’t any planned path to get into venture capital. If I had to rewind, would I just go to venture capital? I don’t know. I might have just done product management and been an operator.

Nataraj: What was your first job in venture?

Karthee Madasamy: My first job in venture was at JK&B Capital in Chicago, where I was doing my business school. In venture, unlike other areas, you have to basically go fight for your job. I reached out to them saying, “Look, I’ve done a lot of stuff in semiconductors and wireless communication, and it seems like you guys are starting to look at that. I can add value.” I told them about reconfigurable semiconductors, new architectures, and so on. They liked that because it was an area they were spending time on but didn’t have deep expertise in. So I joined to look at new electronics, microelectronics, and semiconductors. I was basically doing sector analysis and reviewing companies in those areas.

The one key thing in venture capital is that you have to define a job opportunity and a job description, telling them, “You need this, and this is what I can come and help you with”—even as an associate, an entry-level person. In venture, it’s not just about saying, “I’m a smart person who can do software.” You have to create an opportunity and then say, “I can go fill that opportunity.”

Nataraj: Once you joined the firm and started understanding venture capital, what were some of the early deals that you worked on?

Karthee Madasamy: One of the early ones was using wireless communication for tracking things. This was in 2005, 20 years ago now. They were creating a proprietary wireless communication stack for tracking objects or assets across the country. This was in the early days of 3G, so most data communication was pretty low-key. Think of it like an early incarnation of Apple’s AirTags, but for big assets. It was interesting because I had a wireless and microelectronics background. We didn’t end up investing, but it was interesting to understand how to solve business problems using technology.

The key learning there was that you always try to solve a business problem with underlying technology, but you have to be aware of how quickly that technology gets commoditized. One of the early companies I evaluated at Qualcomm was a navigation app. This was 20 years ago, before Google Maps. You paid $10 a month for an app which gave you phone-based turn-by-turn navigation. It was a business need because you were driving and didn’t want to buy a separate navigation device. It was a good business opportunity, and some companies were doing good revenues.

But the underlying technology was getting commoditized. MapQuest was saying, “I can do it for $4 a month.” And then Google said, “It’s free.” Suddenly, these companies’ business models just went away in one day. So it was good to understand both the business problem and the underlying technologies. That’s the thing about deep tech, or new technologies—they get commoditized very quickly as well. Whatever I built 25 years ago as a startup is now a five-cent chip. It’s a commodity. Understanding the technology curve is extremely important to figure out which is going to last longer and which is going to just go up in flames.

Nataraj: Is there any pattern you’ve identified to figure out if a new technology is getting commoditized and whether to invest or not?

Karthee Madasamy: It’s a lot of heuristics. You try to see the path of commoditization and who could still retain value. In the turn-by-turn navigation stack, the navigation part went from $10 to zero when Google came along. But we felt the underlying map data—the actual data of where all the points of interest are—is not easy for anybody to just go build. At that time, NAVTEQ and Tele Atlas were spending $50 to $100 million every year to make sure they had updated data. I never felt that was going to get commoditized down to zero based on technology alone.

That’s what led to two investments: one in the US called Waze, and the other in India called MapmyIndia. You have to figure out what could get commoditized and what could not. For example, would Nvidia’s GPU get commoditized down to nothing? There are a lot more barriers there. First of all, to get to that level of performance, but more importantly, they have built the stack on top—the middleware, the software, the application layer. They have created a moat around everybody using CUDA and their software middleware to build applications. So they’ll be able to preserve quite a bit of that. You look at all possibilities to see if they have any other protection or if they are just at the whim of the technology curve.

Nataraj: What was your lens behind investing in MapmyIndia?

Karthee Madasamy: We looked at the whole stack of location-based services and felt that the biggest value was in the underlying map data and points of interest data, which is not easy to get. Waze was doing it in a crowd-sourced way. MapmyIndia was more traditional, but they were going after a market which is very, very unstructured. In the US and most Western markets, addresses were standardized in the mid-1900s. India is still completely unstructured.

To give context, when a parcel of land is assigned, there’s a plot number. Then there’s a numbering system, maybe a road, and finally an official street name. You have at least three different versions of an address, but most of the time, there are five or six. Different people will use different ones. Mapping this data and routing it is very unstructured. Navigation in India is more about, “You’ll find this particular place, turn left on that.” It’s never about turning left on a specific street; it’s turning left at a point of interest, which itself will have six different names. It’s a much harder data problem, which is why we felt that data would be very valuable. We invested in them in 2009. They went public two or three years ago, and even today, nobody can match the quality of data they have built.

Nataraj: Talk about the differences in incentives. When you work at an early-stage fund, you get carry and salary. In a corporate venture firm, it’s a salary plus some equity component. For people early in their careers who want to get into venture, what should they maximize for?

Karthee Madasamy: Early on, there’s not as much difference. You’re learning to build your network of entrepreneurs, build relationships, and figure out which are good, investable startups. You’re curating deals and developing your own framework for what makes a good investment. When you start in venture capital, those are the first things you’re focusing on. Frankly, there’s not as much difference between a corporate venture and a financial venture because, in the early years, you’re learning the craft.

Some of the bigger financial VC firms have a brand that attracts entrepreneurs. Corporates also have that. For anything related to semiconductors or wireless communication, Qualcomm is a well-known name. To have someone from Qualcomm validate your technology or company is very interesting for a startup. At Qualcomm Ventures, we were given reasonable autonomy to chase investments. If we made an investment, we would be on the board and responsible for it.

On the compensation side, again, early on, it doesn’t matter as much. In a financial VC firm, you get some carried interest plus bonuses and salary. In a corporate firm, some are now instituting carry, but even if you didn’t have it, you probably had bonuses, stocks from the corporate parent, and a salary. It was almost the same.

The difference comes in the later years. Once you’ve made these investments and one has a good outcome, if it had been in a financial VC firm, the compensation would have been different. It starts to matter once you are five or six years in because an investment takes six or seven years to exit. With corporate VC, your downside is protected, but your upside is capped. You live within a band, which is okay in the early part of your career but not later. If you believe you’re a very good VC making very good investments, that’s when you start to feel the difference.

Nataraj: So you made a couple of interesting bets, like Waze and MapmyIndia, and then decided this wasn’t enough and started your own firm. What was that journey like, and how challenging was it to raise your first fund?

Karthee Madasamy: It wasn’t the compensation alone. I became a corporate VP and felt that I was hitting the roof, both in terms of learning and other things. And also, if I’m making good bets, I should be compensated accordingly. The transition to starting a firm was probably one of the hardest experiences of my career.

Raising money from LPs is very different from raising money as a startup. The main reason I did this was that in 2017-2018, software was ruling the roost. Software was eating the world. We had the cleantech bust in 2010-2011, so nobody wanted to touch anything that was remotely hard technology. Most of the big VC firms were retiring their hardware VCs. It was clear that if you talked to entrepreneurs in core technology, they had very few VCs to go to, even in Silicon Valley. We felt there was a missing gap, and that was my DNA in terms of evaluating new technologies. So we felt there was a gap we could fill.

The biggest thing was fundraising. As a corporate VC, I didn’t have to fundraise; we invested off the balance sheet. Investing as an LP is a trust-based thing. People invest based on trust, which means you can really only raise money from people that know you or at least know of you. It’s much harder to go beyond those circles. Coming from a corporate background, I had to learn that from scratch, build those relationships, and build that network. It was much slower and harder, but it’s not a short-term thing. We felt there was a need to do this for the very long term, so we were able to go through all the ups and downs. Now we’re investing out of our fund two. It’s much better than how it was when we started.

Nataraj: Based on your experience raising two funds, what are two quick lessons you can share?

Karthee Madasamy: There’s a statement that everybody has a plan until you get knocked in the face. I don’t think I could have done any more analysis. The only thing I would have said is that there were so many people I felt could have invested in the fund who didn’t. Separating people from their capital, even as an investment, is the hardest thing to do. We started off thinking we were going to raise a bigger fund; maybe we should have started by thinking we would raise a very small fund. Assume that everyone you think could invest is not going to, and then maybe start that way. But I don’t think the end game would have been any different. Maybe we would have had fewer disappointments.

Nataraj: Let’s talk about deep tech. The term has become pretty common now. VCs used to fund hard problems, but then we went a bit haywire. You probably found the right time when everyone was focused on software. Where do you think deep tech is right now, and which areas are you interested in?

Karthee Madasamy: You’re right, VCs used to fund hard problems. Not necessarily R&D science research, but when something was proven out and ready to be built, even though it was still hard. Then the internet started, then mobile, then elastic compute and cloud. All three came together. The concept of deep tech or core infrastructure has been there for the last 50-60 years of our technology evolution. You come up with a microprocessor, which starts the personal computing era, then you get a bunch of applications. You start with internet infrastructure, and you build on top of that. In that cycle, nothing has changed. The next one was robotics, automation, and AI.

What happened was the internet, mobile, and cloud provided this era of cloud, internet, and mobile applications. It coincided with the hard landing of cleantech and the emergence of China as a semiconductor hub. A lot of the slightly easier semiconductor work moved to China. You couldn’t compete. So, people investing in hard technologies found that the opportunity threshold was much, much higher. The institutional knowledge was completely gone. The new VCs hired into firms were all doing software.

But I’m very bullish because technology used to be bought by technology companies; now other verticals are buying technology and getting disrupted. We are in a golden age of this core deep tech. We’re seeing things around robotics and automation, synthetic biology, a new generation of computing like quantum computing, and core AI solving classification and generation problems. We are in the golden age of new technology solving problems. I’m sure once this infrastructure gets built, you’re going to see a variety of application layer companies.

Nataraj: I want to talk about one of your portfolio companies, PsiQuantum. You invested before Quantum was really in the narrative. What was your bet on PsiQuantum, and what is the company really doing?

Karthee Madasamy: We are hitting the limits of computing. We’ve gone to one-nanometer, two-nanometer semiconductor chips. There’s no more room to pack things in, but our computing needs are not going away. We need a different form of computing architecture, and quantum provides the best alternative. Today, if you want to push the edge of computing beyond what we can do with our current technologies, the best option is quantum.

The basics of quantum draw from quantum mechanics, where anything can be in multiple states at one time. Current digital computing is either a zero or a one. With quantum, a bit can take multiple states. That has exponential qualities. If you have eight bits, it can stay in 2^8 states at one time. If you can use that to do arithmetic, you can solve complex exponential problems much harder to solve with conventional computing.

The first applications are all things that require this. Think about drug discovery. We can’t simulate the full interactions in your body on a computer because it becomes an exponential problem. In a quantum computer, we could get most of that simulation done. This means we could get a drug to market much faster. The pharma and computational biology applications are big. Same for computational chemistry. Those are all going to be the first applications, and they have huge impacts on business, industries, and humanity. It may take a while before you have a quantum computer in your laptop, but solving these big problems for industries is going to happen much sooner than people realize. We are a few years away from significant breakthroughs using quantum computers.

Nataraj: What do you know about investing that you wish you knew when you started your career?

Karthee Madasamy: It is not a monolith. Investing in the stock market is very different from investing in a Series Seed company versus a seed company versus a pre-seed company spinning out from a lab. They are all different, and they require different levels of gut instinct versus being data-driven. I’ve come to the conclusion in the last 10 years that I’m more comfortable in the early stage because it involves intuition and gut as well. When you’re starting your career, you want to figure out what you are more comfortable with. Are you comfortable with data, with processes, or with technology and instinct? Depending on that, you probably belong in different parts of the spectrum.

Nataraj: That’s a good note to end the conversation. Thanks for coming on the show and sharing all the insights about what you’re investing in deep tech.

Karthee Madasamy: I enjoyed the conversation. You asked a lot of interesting questions that I typically don’t get. It was fun.

Karthee Madasamy’s insights reveal a pivotal moment for deep tech, where foundational technologies are not just advancing but creating entirely new industries. His journey underscores the long-term vision and conviction required to invest in companies that are solving the world’s hardest problems.

→ If you enjoyed this conversation with Karthee Madasamy, listen to the full episode here on Spotify or Apple.
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The landscape of startup investing has dramatically shifted, with companies staying private longer than ever before. This extension of the private lifecycle has created a significant challenge: a lack of liquidity for early employees, founders, and investors who have poured years of effort and capital into building these businesses. How can they access the value they’ve created without waiting for a distant IPO or acquisition? Atish Davda, founder and CEO of EquityZen, created a solution. In this conversation with Nataraj, Atish breaks down the world of secondary markets. He shares the personal story that led him to start EquityZen, explains how the platform standardizes and simplifies private share transactions, and details the company-friendly approach that has earned them the trust of major late-stage startups. He also dives into different investor strategies, the outlook for the IPO market, and why building a trusted brand is the ultimate long-term play in this evolving space.

→ Enjoy this conversation with Atish Davda, on Spotify, Apple.

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Nataraj: So let’s start. A good place to start would be, for a lot of folks who don’t know about EquityZen, what is EquityZen and how did it get started?

Atish: EquityZen is a marketplace for private company shares. We have been around for about 13 years and our mission is to build private markets for the public. This is what we do. We work with founders, employees, and early investors of late-stage private companies—large companies that 20 years ago would have been public but are still private today. We help them get some liquidity, meaning they can sell their shares, and we match them up with investors on the other side that want to invest in these companies but can’t find them on their Fidelity account or their Vanguard account because they’re not a publicly traded firm yet. So EquityZen works with the company to get their shareholders cash and to get new investors access before the company actually goes public. And we’ve been around, like I said, since 2013. How the company got started? Well, this is in some ways a very personal story for me and not unsurprising for many folks. I had a personal need. I’ll just give you my quick background. I started my career at a quant hedge fund. I studied computer engineering and mathematics. Basically, if anything had to do with numbers, it made sense to me. I was fortunate. I worked at a quant hedge fund called AQR Capital. My work there was excellent, and it was a multi-billion dollar hedge fund where a lot of the entrepreneurship occurred maybe 10 years before I had joined. And so I wanted to be an entrepreneur, so I joined a startup as its first employee to learn. My equity in that company and a few other companies I had just been consulting for ended up being worth a little bit of money. And because I wasn’t getting paid the startup share, the hedge fund money anymore, I wanted to liquidate some of my private company stock. Well, because I wanted to liquidate $25,000 worth of stock or $50,000 worth of stock and not $25 million worth of stock, I was effectively out of options. I didn’t really have any brokers I could go to, didn’t really have any bankers I could go to. And so that was really the genesis behind what has now become EquityZen. We serve these private company shareholders that are big believers, supporters that have been there for the value creation, supporting the private companies. It’s just that if you work at Google, you can just sell your Google stock and pay for the house, or in my case, an engagement ring, which is what I wanted to sell my stock for. And if you’re a private company, you can go to EquityZen and allow your shareholders to do that in a regulatory sound manner and with the company’s blessing.

Nataraj: Before EquityZen existed, how did people find liquidity in the market? Startups existed forever, for the last 30-35 years. Was there no market at all? Or was it more like happenstance that you knew someone who was looking to buy these shares? I was working at early Yahoo, and I know some investor who is looking to buy. He probably doesn’t have a venture fund, but he’s trying to find late-stage company shares. Is that how it was working back then?

Atish: That’s a great question. Look, there’s been about three stages of evolution in the private market. Stage number one, companies used to go public when they were three, four, five years old. Amazon went public famously as a four-year-old company. Today, most companies that go public in the tech sector are teenagers, especially if you think about over the last three years, how closed the IPO window has been. Basically, if you’re an 11-year-old company and you wanted to go public in 2022 and you missed that window, you’re now a 14-year-old company and probably you’re not going to go public for another six to 12 months. And so before you know it, your shareholders have had to wait 15 years, your investors have had to wait 15 years to get liquidity. What used to happen before in phase one is effectively companies would just go public. And then you saw what happened in the dot-com boom. A lot of companies went public. Most of them didn’t survive. Some of them have survived since then. And it was the public investors that effectively took on the risk of providing liquidity. Phase two of the market is when there were basically six or seven companies. You have Facebook, LinkedIn, Groupon, Pandora, Pinterest. I mean, these small number of companies had grown to be multi-billion dollars but they were still private. So larger, sell-side capital markets desks were trading their stock. Goldman Sachs very famously conducted a lot of secondary transactions for Facebook, but it wasn’t $25,000 shareholders or $30,000 investors. It was $25 million worth of blocks, and hedge funds and family offices invested.

Nataraj: In a lot of ways, it’s like a version of selling your IPO stock because that’s sort of what happens when a company is going public, right? You have a roster of your clients who want to invest and then you allocate shares to that roster of clients, and pretty much very high net worth.

Atish: Yeah, it’s totally a heavily negotiated and heavily brokered transaction. That’s what phase two was about. And Facebook got arm-twisted into going public actually because there were too many secondary transactions the way Goldman was doing them, Goldman and other firms. And what ultimately ended up happening was that Facebook was forced to go public. That kind of put a chill on the venture secondaries market until EquityZen came along. And what EquityZen has done is effectively done two things. One, we have standardized the process of conducting these transactions. Look, when you’re transacting $50 million worth of shares, it makes sense to heavily negotiate each contract. Those economics don’t work if you want to trade $50,000 worth of stock. And so what we’ve done is the traditional technology company thing, which is build up the infrastructure and then amortize the paperwork and the cost over thousands of transactions. And by doing that, we can reduce the artificial minimum of conducting these transactions. Now, you don’t need $10 million to transact in private company stock. You can do it for $10,000, thanks to EquityZen. So that’s one thing we did was standardize the process. And the other thing we did was by making it available to accredited investors via our website, via technology. And this was right around the time that AngelList was coming up and crowdfunding was becoming more popular and people were getting comfortable actually deploying capital into an investment online. And while AngelList focused on the early stage of venture and Schwab continued to service the public companies, EquityZen kind of filled that hole in between. If you’re a series C but not yet a public company, you can now invest via EquityZen. So those are the two things that we kind of, I would say, reignited the secondaries market back in 2012, 2013.

Nataraj: EquityZen and AngelList have a lot of similarities from what I can see as a pure consumer or someone who has seen EquityZen and participated in one deal on EquityZen and plenty on the early-stage side on AngelList. And AngelList, I think, has a different set of products. It has sort of an early-stage fundraising product, which is slightly different than what EquityZen does, although there are some secondary transactions that happen on AngelList as well. Can you quickly talk about what type of standardization you brought? Like what are the couple of important terms that investors or even early employees who are selling the stock are looking at? Like I know for early stage the stage counts, if it’s a convertible or direct equity, when it matures, what is the discount? Is it a SAFE or a non-SAFE? Those are the terms that I’m usually familiar with, but for EquityZen, what are the two or three terms that are actually making or breaking the deal?

Atish: Yeah, great question. Before I say that, let me just draw a quick parallel to early-stage investing, which I think a lot of folks are generally familiar with. In early-stage investing or crowdfunding or the things AngelList became really popular doing initially, it’s the actual company that’s raising money. We call that in our parlance a primary transaction. So this is a transaction where the company is issuing new stock, whether it’s in the form of a note or SAFE or new common stock or preferred stock, they’re issuing stock. The company experiences dilution and all the money that’s raised goes to the company in order to fund operations, pay salary, rent office space and what have you. What the secondary market does, which is what EquityZen does is again, conduct secondary transactions. In this situation, when we conduct a transaction in some company, Instacart, it’s a public company now and so I can talk about it. When we conducted transactions in Instacart, Instacart wouldn’t actually get any money. Let’s say we do anywhere from $10 million or $100 million of transactions in Instacart. Instacart itself doesn’t actually get operating capital from them. It’s the shareholders who already own a piece of Instacart. They sell their shares, get money back, and new investors now get to basically own equity in Instacart. So that’s just one key difference between early-stage and late-stage. And because of this, there’s a difference in asset class returns. Early-stage investments are very famously power-law investments. You’re going to make 30 investments. You’re going to lose your money on 15 of them. You’re going to return your money on 10 of them. And if you’re lucky, five of them will earn you back all the money that you’ve basically invested and lost. Late-stage investments are very different. These are doubles and triples. You’re not just swinging for the fences for the home run. And you’re getting a lot more established businesses. And so now to answer your question, what are the things that matter? What do people look for when they’re thinking about investing in this asset class? Well, first of all, you should look at your whole portfolio and you say, I have a certain amount of money in public stocks, a certain amount of money in bonds, a certain amount of money in early-stage venture maybe. Do I have anything in between where on a risk-adjusted basis it’s a more established company, but there’s still a lot of value to be created? So you should think about allocation of how much of your portfolio you want to put in. Then you should think about what your sophistication level is. Do you want to invest in one of EquityZen’s multi-company offerings? Meaning I write one check, I’m going to write a $50,000 check or $10,000 check, and I’m going to get access to 20 companies. Or do I want to invest in individual companies? I’m going to write 10 $10,000 checks or $10,000, $50,000 checks and make my own portfolio. So I think that’s kind of the next level of making a decision of do I want to buy an ETF, if you will, or do I want to pick a single stock? Then the next level of deal evaluation is what series of stock am I buying? Am I buying preferred stock? Am I buying common stock? What is the discount to the last round of capital or premium to the last round of capital? And of course, because these are more established businesses, you can do a little bit of research on what the revenue stream looks like, what the management team looks like, who the other investors are. So Sequoia just puts money into this company. Sequoia has, first of all, a fantastic track record, but also way more resources than the average individual investor does. And so Sequoia and Andreessen Horowitz, Benchmark, you kind of have your top list of investors. If they have recently put money in, they’ve kind of done their work and established a price point. Well, now it’s a lot easier for you to all of a sudden say, well, it’s a private company. I don’t have public stock information. How do I get comfortable with it? And in this way, it is similar to earlier stage investments, where usually in early-stage investments, there’s a VC that puts money in, does all the diligence. And then you have a bunch of angel investors who are basically tagging on and saying, yes, I will also put money in. So in an essence, you’re kind of borrowing from the diligence that institutional investors have done and knowing which institutional investors’ investments fit your return profile. That’s probably where a lot of investors ought to spend a bit of time understanding like, yes, I understand Benchmark’s portfolios, they invest in marketplaces, they’re excellent at it. This company is a marketplace. Maybe this is a good opportunity for me, or maybe this is not a good opportunity.

Nataraj: Talking about the multiple products, in terms of your business, which is the more successful product for you? Is the portfolio offering a bigger business or are individual transactions a bigger business for EquityZen?

Atish: Yeah, for us as a business, certainly the single-company transactions, that’s what we’re known for. That’s a larger business. I think if you’re an investor learning about EquityZen for the first time, the real question I would ask is, what is your goal? Is your goal that you want to build your own portfolio? You’re familiar enough with the technology industry, you do your own research. I’ll give you an example. If you’re a security engineer that works at a marketing firm, you’re probably a pretty great person to be able to determine the difference between cybersecurity company A and cybersecurity company B. If you’re a marketing executive at an engineering company, maybe you’re great at determining which new marketing tech company is better than the other. So within certain sectors, people are going to get more value out of establishing their own portfolios by choosing single names. And in other sectors, they may say, you know what? I don’t know anything about artificial intelligence. I can’t tell. I can’t keep up with which company’s beating which other company. I just want to invest in the sector. Fine. So maybe you can make a thematic investment. So it’s more a matter of what makes more sense for the user. From EquityZen’s perspective, certainly the bulk of our volume happens on the single-company side. And I think that’s more a function of where the market is right now. We are still very much in the early days of this market forming. So if you take a look at the typical customer lifecycle, we’re in the early adopter phase. The folks that use the beta version of a product, not wait until the final version is released. And so even though we’ve been in business for 12 years, 13 years, and even though we have this fantastic track record, I would say we’re still probably in decade one of three before this entire cycle continues to grow. And the next 10 years are actually going to bring that next segment, the folks that really say, I don’t know this company from that company, but I know I need an allocation here. And so I think for the last 10 years, brokerage of individual companies has been the bigger segment. And over the next 10 years, if I were to fast forward, no doubt that more structured products will be the larger business segment.

Nataraj: The way I always thought of secondary transactions is like betting on your unique knowledge in a lot of ways, where it is less risky than early stage, because even if you have a lot of knowledge in a specific sector, it’s a very hard bet in early stage. Like the security engineer example, you cannot really identify a Wiz or something like that when the team is three people. But when the team is 100 people, when a couple of well-known VCs have invested, you can probably convince a Wiz employee to sell some of the equity to you. So I always felt like secondary transactions are for these sophisticated investors or sophisticated individuals who want to acquire equities in companies they are super confident about. That’s how I always saw secondary transactions.

Atish: But first of all, let me just say you’re spot on. And if you look at history, typically you have sophisticated folks doing something, and then people realize that’s where the sophisticated money is going. So then people come up with products that are versions of the sophisticated strategy, more for the less sophisticated investors in the space. This is exactly what happened in the liquid alt movement. You had institutional investors… one of my first projects at the hedge fund, a strategy that $250 million check writers get access to, was to convert this into a mutual fund that my mom with $2,500 in a Vanguard account can access. So I think in that way, you’re spot on, and that’s candidly what we’re doing. Institutional investors have invested in late-stage venture for 20 years, 30 years. What EquityZen is doing is bringing that access, making it available to smaller check writers first, and then eventually the folks that don’t even need to be in the ins and outs of technology every day. Their financial advisor will actually just find our ETF equivalent or mutual fund equivalent for them and say, we’re going to put 1% of your portfolio in this growth bucket, next.

Nataraj: Yeah. So companies in the sector usually, at least on the early stage, where they’re doing primary transactions, they’re always taking some amount of carry in their compensation or in their business model. They have a standard, like an X amount of cost structure plus an equity component of it. Is EquityZen also taking some equity component of it to have a stake on the upside or is it just purely per-transaction capital cost?

Atish: Yeah, so I mentioned we have two products. Product one, we operate exactly like a marketplace. We do not take carry on top. Frankly, I think that would dissuade a lot of people from putting money in. And therefore, what we do is we effectively only charge a commission to the buyers and sellers. In this product line, we do take carry. This is more of a traditional kind of managed fund product. And so people put money in, we charge a small management fee, and we charge a carry. And all of this is less than the two and 20 kind of products. However, there are two different product suites designed for two different use cases. And so in one case, what we’ve learned is a lot of clients don’t really want to pay carry on individual names. Frankly, AngelList convinced people to do that, and that’s a phenomenal trick that they pulled and it’s fantastic for them as a business model because even if you build a portfolio of 10, if one of them ends up doing well, the carry pays off. Later-stage investors, a little more sophisticated, don’t really want to do that. But on this side, they’re only portfolio-based kind of carry calculation.

Nataraj: I also think carry works when they have a syndicate-like product where you are basically incentivizing a lead to bring a good deal. And like, why should he offer his work to you? It’s that sort of alliance. I think that’s why it still works. Even though a lot of competing products are trying to reduce the carry component, and I think we’re trending down towards zero eventually. But at least that’s the reason it worked in my view.

Atish: I’m sure that’s a big part of it. And look, in any market, as the level of familiarity grows, the animal spirits tell us that people will just arbitrage away inefficiency.

Nataraj: So today, what is the state of business? Give us a sense of how many transactions happen on EquityZen, how many assets are under management.

Atish: Yeah, so we’ve conducted almost 50,000 private placement transactions. We’ve conducted transactions in 450, close to 500 of these large private companies. About a third of these companies have already gone public or gotten acquired in M&A, and therefore we’ve returned capital to investors. And a bunch of capital that we’ve returned just gets recycled. The other thing I’d like to point out is we have around 700,000 households on our platform. But it’s heavily skewed to the investor side, right? The majority of the users on our platform are investors, meaning they’re actually trying to access these investments for the first time. It kind of makes sense. Most people don’t work in technology, and most people don’t invest in early-stage venture so that they become late-stage. And so a smaller segment of our user base is shareholders. But when shareholders get liquidity, usually it’s their first or at most second time coming into money. At least a portion of those actually end up becoming investors too, just because they say, again, like the examples we talked about, I know the difference between this tech company and that tech company, I’d like to participate. A couple of other stats that might be relevant, just to give a size idea. We manage over 2,000 special purpose vehicles right now. So it’s not just one-to-one transactions we conduct. We also spin up SPVs, people invest in SPVs, the SPVs sit on the cap table of all these companies. And we have between one and a half and two billion of active investments, not counting all the stuff that we’ve already processed. And of course, for the last few years, we haven’t seen that many exits, but again, in like 2020, 2021 and prior, there were a lot of exits that we processed, so all those returns are not counted in the one and a half to two billion estimate.

Nataraj: What are some of the interesting stories or examples of some of those exits that happened in 2021, which you can probably talk about?

Atish: Yeah, well, I guess one thing that’s worth saying out loud, maybe this is more of a nuance of the secondary market compared to the primary market, is EquityZen operates as a broker, right? We’re a matchmaker between buyers and sellers. But unlike most marketplaces, we operate a three-sided marketplace. So we have a seller of stock, we have a buyer of stock, which is what most marketplaces have. But then we have the issuer, which is the company in which the stock is. And EquityZen is really the only platform in our industry that very much gives the issuers, the companies, a seat at the table. Issuers, we don’t charge them anything. We’re not beholden to them about anything. But we have taken the approach that because it’s their company’s stock, they should have visibility into who’s buying, who’s selling, and to actually get permission to be able to say yes, I approve this transfer restriction, or I waive my right of first refusal. Maybe it sounds obvious, but that’s not always the case. We’re the only ones that very much put companies at the top in terms of the decision-making tree. And what that allows us to do is really establish a relationship with the company. So for example, sometimes we will have companies say, hey, EquityZen, we’re in the middle of raising financing. We don’t want a secondary transaction to be price-setting right now, even though people are willing to pay a crazy amount of money. It actually hurts our negotiations with VCs or with private equity firms. So we’re going to put a one-month block on these transactions. And so that’s the kind of dialogue that we establish with these companies. So they kind of tell us, Hey, look, there’s a blackout window coming. We’re pursuing an IPO. Those are the types of dynamics that exist because we’ve taken a very company-friendly approach. And that’s just one example of how this is different from the rest of the peer group, perhaps.

Nataraj: But what if the company… so you mentioned right of first refusal, often referred to as ROFR, which means that a company can deny a secondary transaction because they have the first right to purchase that stock at that price, right? So if an early employee wants to sell a stock and the company doesn’t have a ROFR, EquityZen would still block the transaction? And wouldn’t that drive away certain business to your competitor, and they might execute that transaction elsewhere because technically the company can’t stop it if they don’t have ROFR rights?

Atish: Let me clarify a couple of things you mentioned. First, I have not come across a company that does not have a right of first refusal in the 13 years I’ve done this. And as a private company owner myself, I want a right of first refusal on my stock. And there are very legitimate and sensible reasons for that. However, a right of first refusal is not the same as a blocking right. So a right of first refusal is effectively the company saying, I don’t want that investor on my cap table. That investor is actually funded by my competitor. I don’t want that person on my cap table. Or that investor is from a different geography and for regulatory reasons, I’m not allowed to have that investor in my cap table. So what I will do, shareholder, is I will buy your shares. Effectively, it’s a matching right. It’s a right that says, shareholder, you will still get your liquidity, but that investor is not allowed to come in at this price. That’s separate from the blocking rights that I think you’re describing. And so you’re absolutely right. What some of my competitors do that we will not do is they will effectively conduct a transaction without actual share certificates changing hands. They will conduct what are called forward contracts, which are effectively IOUs. If you were a shareholder and I was an investor, and I was using some other company because EquityZen does not do this, one thing that could happen is you could say, okay, yes, I agree to sell you 100 shares at $100 a piece. Cool, no problem. I give you the money. In theory, I have the equity exposure. But if I’ve entered into this forward contract with this funky SPV with multiple other SPVs or whatever, and then the company actually ends up being Uber, and you regret selling your stock. In 2025, you took my money. And in 2028, you might have $10 million from your 100 shares because the company just blew up in a great way. And you might say, you know what? I don’t want to sell all 100 of my shares. In that scenario, what I have done is not only illegal from the standpoint of I violated the company’s restriction. What you’ve done is illegal because the company has changed restrictions for a good reason. But now I have no recourse to this. Like if you move to Singapore and basically change your phone number, I’m not saying you would ever do that. But of course there are people who would do that. As an investor, I’m completely exposed. And from a company standpoint, they don’t like that. There are companies today that are dealing with this and they’re going out of their way to educate their shareholders and they’re saying, hey, there are brokers out there that are claiming to sell you shares and claiming to trade your stock. Let me be very clear. We only work with a small number of preferred partners like EquityZen, and outside of those partners, you should be careful about what it is that you think you’re buying or you think you’re selling because we are not endorsing that. And that nuance is just something I want to bring up because it’s not a real concern when the counterparty is an early-stage company.

Nataraj: I think there is one company whose secondary shares keep trading higher and higher and are traded everywhere. I think I know which company this might be. This is SpaceX. I’ve been seeing this company’s secondary offers everywhere from every Indian WhatsApp group to every online portal. Someone is offering a SpaceX secondary offering. How many of these are legit versus how many of these are like the second category of IOUs that you’re talking about?

Atish: I certainly cannot speak to generalities on that front, certainly not for a specific issuer. What I can say very clearly is, EquityZen conducts transactions with the issuer’s knowledge and with the understanding that we give the issuer basically the visibility, hey look, here are the shares, here are the investors, we want to trade, are you okay with this or not? And time and time again, we have walked away from revenue that we could have just kind of skirted, but that’s not how EquityZen operates. It’s not how we want to operate unless the broker that you’re using can say that, unless the fund manager that you’re using can say that. I always try to caution people about what it is they’re buying. Cause at the end of the day, you are the one parting with your money. So it’s your responsibility to make sure that you understand what it is that you’re buying and whether or not there’s a trusted platform. There’s a reason in the 13 years that we’ve been in business, we’ve seen, I don’t know, half a dozen to a dozen platforms come and go. Some of them because the government told them to stop and some of them because they made so much money by doing some of these things that they didn’t need to work anymore. And our approach the entire time has been, we want our name to be synonymous with trust. And that means we’re going to have to say no to a lot of things. And in the long run, it’s going to pay off and we’re seeing the effects of it now. EquityZen is a referred platform for many companies who say no to most other brokers out there. In fact, we sometimes get assigned a right of first refusal. A company says, Hey, I received this transfer notice from this other broker. I don’t want that broker or their client on my cap table, but we don’t want to execute a right of first refusal at this price. So if you can do this, we have an assignment right. We will assign a right of first refusal to you to do this. EquityZen will then get tagged in, in order to be the broker of choice. And candidly, that doesn’t just happen. That happens because of years and years of basically being a trusted partner with a lot of issuers and effectively sometimes gritting our teeth and doing the thing we don’t want to do, which is to say no to revenue at the end of the day. But again, long-term perspective, it’s a no-brainer decision.

Nataraj: You also have some interesting data I feel because you also gauge demand or interest in different companies when you go to your platform. How do you use that data either to create new products or do you use that data to approach companies and say hey there’s a lot of demand for transactions, how are you thinking about secondary transactions and providing liquidity? How do you leverage that data?

Atish: Yes to all of the above. The only way we don’t leverage the data is we don’t actively sell or license the data like many of our peers do. And our view on that candidly is there’s no philosophical reason why. It’s pure and simple. The market’s early. So anyone—I’m a former quant, so data is very pure to me when it comes to utilizing data in a statistically significant way. Not everyone does that, that’s okay. And so our view on it is the market is still nascent. It does not make a ton of sense to use the data unless it’s a tiny portion of a larger model. Using private company transaction data should be one factor out of many factors in your investment decision. And unfortunately, a lot of companies out there are trying to sell their data and pretend like this is equivalent to public market data. Public market transactions are orders of magnitude more often than private market transactions. Private market transactions are actually more similar in terms of frequency to house sales compared to public company stock sales. And many of our peers are not drawing the distinction and papering over it. And so the only ones I think using data well, maybe as intended, let’s say, are institutional investors and sophisticated individuals who are saying data is one of my inputs. It really informs on the margin. It’s going to inform whether I’m going to pay 12 bucks or 13 bucks. It’s not a yes or no decision for me on data. And I think I would draw a parallel to the crypto world where you have a lot of supporters of various cryptocurrencies who are effectively acting like day traders. The data says the stock is going up, so I’ll invest or it’s going down, so I’ll sell. And we just are not that place where people would make purely speculative bets. This is more of a buy and hold investment in your portfolio from an allocation perspective. Again, the very first thing I told you when you asked me is, the very first decision to make is, what is my allocation to the space? Then determine all the other things. And so how do we use our data? We use it to talk to issuers. We use it to inform investors. We use it to inform shareholders. We publish cap tables. We give our users a range in which transactions are happening. And all of this we’re happy to provide to the issuer because ultimately we want the issuer to be a partner with us and that’s true. What we don’t do is use our data to kind of reel in investors who don’t really know what they want to do. We want people who know what they’re buying basically, if they’re going to buy.

Nataraj: And I don’t know what the regulation allows you or doesn’t allow you, because any company has to market itself. So how does EquityZen market itself to a future employee or early investor who wants to sell or a future investor who’s thinking about maybe expanding or diversifying their portfolio? How do you market EquityZen? Because it’s a very regulated industry, right? And these are very niche transactions for a lot of individuals. So how does marketing for EquityZen work?

Atish: Heavily regulated with good reason, I would argue. How does EquityZen market itself? We stay away from individual company marketing. So we will not market a specific offering. That’s just not our world. What we want to do is we want to educate. And then we want investors to self-select in. We want to put forth a knowledge base that we provide, one of the more detailed FAQs I’ve seen that we provide. We want people to read, spend the time to read, and not just make TikTok videos and kind of help people very quickly get brought in. Our view on this is, this is a serious thing you’re doing. Your money is an important asset. You should be careful with it. And so we almost build in a little bit of friction into this process. And I think my product and my marketing team are not always happy with me about that. But the way we do this candidly is we say, look, we’re in this for the long term. Let’s focus on educating people. Let’s help them make a decision about whether or not they want to invest. Then if they decide they want to invest, then they can go through and ask us, what do you recommend? And at that point, we said, we will not recommend individual companies or investments. But we will make the data available to you for you to make your own decision. So we always go out of our way to only educate people that this option exists and here are the benefits and risks of this option. And then sometimes clients will say, hey, I read all this stuff, but I still don’t know whether to invest in company A or company B. And so what we will do is we will say, look, we are not going to give you a recommendation. But we have a financial advisor that if you don’t have one, we’ll refer you to one. And because their buyer base has to be accredited, there’s a wealthy household that’s a typical investor. A lot of times, the vast majority of our users don’t actually have a financial advisor. So we’ll actually connect the dots and say, you should talk to someone who can give you more holistic advice. That’s not something we’re going to do. And so it’s very much about content-driven, education-driven, mission-oriented stuff as opposed to individual deal and transaction oriented.

Nataraj: So for both early-stage and secondary markets, the exit is IPOs. Obviously, the next secondary transaction might be another exit, but IPOs are measured at the exit points. Are there any exit differentiations when it comes to traditional IPOs versus direct listings? Is there any difference that the stakeholders see in terms of an exit perspective?

Atish: Yes, and let me add, if you invest through one of EquityZen’s SPVs, chances are good that you’re actually going to be eligible to sell your holding before the underlying company goes public. And we’ve seen this in the last three years. As an example, for the last three years, the IPO window has been pretty tight. So very few exits have taken place. However, if you bought five years ago or eight years ago and your goal was to hold for five to 10 years, you’d just have to wait until the IPO happens, right? Unless you bought it through us, in which case, chances are good that what you may be eligible to do is actually say, you know what? I hit my return target and I hit my holding period. If there’s a buyer for this, I’m willing to list it. And investors can go and kind of seek liquidity for their own holdings. So that is an exit avenue for the individual investor that is decoupled from the actual company going public. Your question was about a direct listing versus an initial public offering. There’s just the concept of a lockup. Typically in an initial public offering, what ends up happening is, as we talked about earlier, you have insiders who list, existing shareholders who list, and they get some liquidity maybe. Usually, the vast majority of liquidity they get is after the lockup window. And the only people that really get to buy and sell are the newcomers. This is pretty typical in a share registration. It’s in there for a reason. It’s there to prevent fraud and all sorts of other investor protection reasons. In a typical IPO, most of the stock is restricted. It’s locked up until usually a six-month window. It’s different for every listing. And so if you invest in something, and the company goes public using an IPO, usually you’re not allowed to sell until after the IPO lockup expires. And so you’re taking six months of additional public market risk. Now for a lot of EquityZen’s clients, it’s irrelevant because they’re long-term holders. And I think the way a lot of them look at it is, well, this is going to be in my portfolio for 10 years. What’s the difference whether it’s nine and a half years or 10 years or 10 and a half years? And so from that standpoint, there’s a lot of a buy-and-hold perspective. There are some folks who have more of a ‘buy today and sell in two years’ mindset. And they might care more about direct listing versus IPO. It’s not something you can influence, but if the company chooses a direct listing, then the shareholders typically can sell right after the lockup window, which is actually very short or non-existent. And so the next day, or the same day, you can actually start to sell. That is a key difference between an IPO versus a direct listing. And again, depending on the product that you invested in with EquityZen, you might actually have the ability to get liquidity separately from whether the company goes public. We’ve seen a lot of that over the last few years. Candidly, I think we’ll continue to see a lot more of that over the next couple of years as well until the IPO window fully opens and the business cycle hits that stride.

Nataraj: You mentioned the IPO market being frozen for the last couple of years, and 2019 to ’21 was when everything was hyped up. I think that was also the peak for secondary market sales if I remember. How do you see the next couple of years? That’s when I did my first EquityZen deal. It didn’t work out that well.

Atish: Yeah, it was just peak venture in every way. There you go. Then you should do another one now while the market’s come down quite a bit to dollar-cost average.

Nataraj: Yeah, I was keenly looking at the platform over the last year. But what is the outlook for the next couple of years looking like? Are the animal spirits coming back? It feels like it, that we can expect some IPOs to come back. What are your thoughts?

Atish: I absolutely believe there’s going to be more IPO activity. I think there’s actually going to be a lot more M&A activity, which is fine. Company liquidity is liquidity. This is the thing that, when you just read TechCrunch, it’s easy to forget that at the end of the day, an IPO, whether it’s M&A or IPO, anything worth buying should have a long-lasting impact. And so whether it’s a financing round, whether it’s an IPO event, whether it’s an M&A, it’s just one more milestone in the journey. It’s like you graduate high school, you graduate college, you rent your first apartment, maybe get married, maybe have a kid, maybe buy a house. It’s just one more event. I think when you actually look at it from a zoomed-out perspective, what I think is going to happen is there’s going to be a lot more liquidity that’s been built up, and the pressure valve will be released. A lot of this pressure comes not only from VC funds that have been able to make money with continuation funds but private equity sponsors. You have traditional hedge funds and private equity sponsors that put a lot of money in over the last six or seven years in the zero-interest-rate environment. There’s a lot of pressure for them and they actually control the businesses so they can maneuver the businesses to either sell or get sold to a corporate or to another sponsor. So I think that activity is going to help a lot. Anytime there’s that kind of activity, even without the cost of capital coming down, even without interest rates coming down, you’re going to see external prints. As soon as you see external prints, secondary transaction activity goes up. Because again, like I said, whether it’s Sequoia, which is the example I used earlier, or Francisco Partners, like a sophisticated investor that’s conducting diligence and setting a price, boom, now you have a benchmark off of which to go. And so whenever that activity goes up, secondary transaction volume will go up. And I think further what’s likely to happen is because there is, whether it’s in the next 12 months or certainly by 18 or 24 months, interest rates are expected to come down a little bit further. As soon as the cost of capital comes down, venture activity can really start to take off and private equity investment can start to take off. So not only are you going to have M&A, you’re also going to have IPOs and you’re also going to have financings and no matter what type of deal event takes place, it’s generally a positive sign for venture secondary transactions. And so from EquityZen’s standpoint, we’re really excited. We’re not really trying to figure out whether it’s this month or last month, or this quarter or last quarter. From a zoomed-out perspective, we think we’re kind of finding the bottom and we can’t wait for the growth that’s ahead of us. And at EquityZen in particular, we’ve actually been unique in our peer group; we’ve raised almost no outside capital. The last time we raised capital was eight, almost nine years ago. And so from that standpoint, the last few years that have been a little more lean, that’s what we were built for. And so we’re actually really excited and ready to go and not feeling beaten down about where the next few years are going to be. Unlike some of our peers that have raised a ton of money and are trying to figure out what they are going to do because venture activity is not yet at those crazy levels. And so from our standpoint, we’re just really pumped about where the market opportunities are going to be for the next really two and a half, three years at a minimum.

Nataraj: I think the reality of this industry, whether it’s early-stage or secondary-stage, is that you have to build long-term trust. And I think AngelList has done that in the early-stage space. When I looked at the secondary transaction, I saw a bunch of companies, but I can’t remember any other name other than EquityZen. I think that’s sort of a testament to the trust that you’ve built in the ecosystem.

Atish: I really appreciate you saying that. I think you and my mom are the two people that have told me that before, so I really appreciate that.

Nataraj: I think that’s a good note to end the conversation on. I know I want to be respectful of your time. Atish, thanks for coming on the show.

Atish: Hey, this was a fantastic conversation. Thanks for shedding a light on an area that obviously I’m really pumped about. And I think everyone who’s an investor should at least evaluate. So thanks again.

Atish Davda’s insights provide a clear roadmap for understanding the secondary market’s crucial role in the modern startup ecosystem. This conversation is a must-listen for anyone interested in pre-IPO investing, startup equity, or the future of private market liquidity.

→ If you enjoyed this conversation with Atish Davda, listen to the full episode here on Spotify, Apple.

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In this episode of the Startup Project, host Nataraj sits down with Aviel Ginzburg, a central figure in the Pacific Northwest’s tech scene. Aviel’s journey is deeply intertwined with Seattle’s startup evolution, from founding Simply Measured (acquired by Sprout Social) to his roles as Managing Director at Amazon’s Alexa Accelerator and now General Partner at Founders Co-op. He offers a candid look into the world of early-stage investing, sharing how his perspective has shifted from focusing on product to understanding the founder’s core motivations—often finding success in those who are ‘irreparably broken’ and driven by an innate need to build. Aviel also discusses the recent volatility in the venture market and introduces Foundations, his new community-focused initiative designed to be an anchor for Seattle’s startup ecosystem, aiming to foster the collaboration and serendipity needed for the next wave of innovation.

→ Enjoy this conversation with Aviel Ginzburg, on Spotify or Apple.
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Nataraj: Hello everyone, welcome to Startup Project. I am your host Natraj. Today my guest is Aviel Ginzburg, founder of Simply Measured, which was acquired by Sprout Social. He was managing director at Amazon’s Alexa Accelerator, he’s also a general partner at Founders Co-op, and he’s now co-founder of Foundations, which is a shared workspace and accelerator, an anchor to Seattle’s VC ecosystem, or trying to be.

Aviel Ginzburg: Exactly. The way that you’re answering it shows the work that we need to do. We’re defining it right now as an invite-only community of founders in the startup ecosystem. It has one part that looks like an accelerator and one part that looks like a co-working space, and we’re going to do a better job of explaining what it is as we figure it out ourselves in 2025.

Nataraj: We’ll get to Seattle Foundations and everything about it. A good place to start this conversation would be with Chris DeVore, your partner from Founders Co-op. He was on one of the best episodes of Startup Project. We had a really great conversation, and I’ve been following Founders Co-op’s work and Chris DeVore for a while. How did you get to start working with him?

Aviel Ginzburg: For better or worse, my entire career has been wrapped around Founders Co-op and has involved Chris. I graduated college in ’07, at the beginning of the Great Recession. I knew I wanted to do something in tech, maybe tech and finance. I was from the East Coast, and the plan was to go to New York. Then everything just went to shit. All of my peers who were graduating were having their jobs pulled. So I had been building small website businesses to pay my bills in college, and I just said, okay, let’s go all in and do this.

So a buddy and I decided to found a company. Before we closed on the friends and family money, I realized very quickly that we were about to lose all of it because we had no idea how to actually start a startup. We were reading TechCrunch and thinking, let’s do that, but neither of us had worked at one. We hadn’t even really talked to someone who had been there and done that. So I said, I have to go West and see what this is like. I didn’t know anyone in SF, but I had one good high school friend at Microsoft, so I wound up in Seattle not knowing anyone.

Less than a week after I started, there was a startup weekend. Back then, everybody would get in a room and build together. There were 150 people from early Amazon, Microsoft, and the budding Seattle startup ecosystem. It was like, okay, let’s pick an idea, form divisions, and all build together. It’s insane to get 150 people to work on the same thing at once. It’s a complete shit show. But I raised my hand and said, I’m a designer, I’ll lead the design department. Was I a designer? I don’t know, but I was more confident than everyone else who said they were.

So I found myself rubbing shoulders with what eventually became the who’s who of the Seattle tech community. Out of that, I landed a job at a company called Aperture, which was funded by Founders Co-op and Madrona. Within two weeks of arriving in Seattle, I was right in the middle of that community, so I got to know Chris. He knew my plan was always to start a company. I was clear with the founders that this was for me to learn and there was nothing they could do to keep me.

I was lucky enough to watch that business work. I think so many people start their career at a startup that goes nowhere or at a big company where you’re stuck in a tiny hole. I was able to write code, design products, talk to customers, and act as a product manager. When I felt I had enough confidence, paired with the fact that I think what makes founders founders is that they just can’t not start something, I started working on nights and weekends with my best friend, hacking together anything we could with Twitter data and Facebook data. So I said, it’s time to go off and start a company, but I don’t know exactly what it’s going to be. Chris and his then partner, Andy, said, we like you, you should do it, we’ll just write you a check. We incorporated as Untitled Startup, which was the precursor to Simply Measured. Chris made me put together a pitch deck that he ripped to shreds and made me feel like he wasn’t going to invest, but he did anyway.

So I transitioned from an early employee to founding CEO, which then transitioned into head of product and engineering. But I was finding that I was much more interested in the zero-to-one of things—going from idea to MVP to customer traction. So I was naturally spending more time with Chris and Founders Co-op. I found myself wrapped up as a pseudo-venture partner, which turned formally into a venture partner in 2014. Then, when we sold Simply Measured, I transitioned into a GP role. It has been 17 years of working every possible seat inside of the Founders Co-op portfolio. Now, it’s just Chris and I working together and investing in new companies.

Nataraj: So talk to me a little bit about what Founders Co-op is doing right now. Are you actively investing? At what stage and what type of checks are you writing?

Aviel Ginzburg: We are at the tail end of our fifth fund, which is a $50 million fund. The average check size is about a million to a million and a half, investing in pre-seeds and seeds in the Pacific Northwest mostly. COVID sort of screws up what geography really means, but we find that we gravitate towards founders who are culturally Seattle. That means you learned how to build at an Amazon or a Microsoft and you gravitate more towards unsexy business workflow problems rather than flashy consumer products. We’ll be doing the first close of our next fund within the next month and are actively deploying. The thing about us is neither of us are finance people. We’re both founders ourselves. We never worked at a larger venture firm. We have no associates. We act very much like a startup itself. Our process feels more like interacting with a former founder who’s deploying his own capital into really early-stage things that they find interesting.

Nataraj: One thing you mentioned on a podcast was that you did these things overlapping—you were an investor while you were a founder. I can relate to doing multiple things. I invest, I work at a big company, and I do a podcast. Talk to me about how your thesis of investing and finding companies evolved.

Aviel Ginzburg: When I was starting to make investment decisions as part of Founders Co-op, I was still actively operating. I was anchoring too much on product and on what I would do if I was running the company. I was thinking way too much about the product, the customers, and the opportunity rather than the founder. That was a hard lesson to learn because I invested in a couple of companies and watched as their direct competitor became a monster. I knew that was going to be a thing, but what I really messed up is that the only thing that really matters is the people. I just did not yet have the pattern matching to know what behaviors and motivations make a great founder. So much of success is about luck and upcoming challenges that you aren’t expecting. I was bringing my perspective of, I know what good product looks like, I know how to take things to market. Frankly, that initially made me a bad investor.

Nataraj: Right now in AI, you see certain types of companies will succeed, but now you have five competitors in the area. Who are you going to invest in?

Aviel Ginzburg: As a fund, I think you can run a strategy if you are a thematic fund with enough dollars and access. You can see everything in a space and pick the winner. It’s hard to do that at the pre-seed and seed stage. Ultimately, as a seed-stage investor, your job is to get really good at identifying a very specific type of founder and be good at knowing how to help them. Focus on those folks. Don’t feel FOMO about missing out on other things.

It’s embarrassing to look at what a lot of folks do. They’ll put out a whole thesis on AR/VR, then they’re a crypto fund, then an AI fund. Then you learn pretty quickly that a company did a 180-degree pivot after they invested, so the whole reason why it was in the fund is completely wrong. Ultimately, early-stage investing is like casino-level risk in people. The reason why it works is that you make enough investments that something does work and takes care of the rest. How you become good at it is through having enough experience with enough founders and seeing the movie play out enough times. I was part of the selection committee for Techstars Seattle from 2010 through 2020 as well, so I have seen thousands of companies from pitch to exit. Ultimately, when I look at a founder, I look at how they’re tackling an opportunity, the shape of the market, and the market opportunity. I can see all the different directions this can go. What you are underwriting is really just the human and the market they’re going after. That’s it.

Nataraj: You mentioned pattern matching. Are there any specific things that are deal-makers or breakers when you look at certain types of founders?

Aviel Ginzburg: Motivation matters a lot to me. Why are you doing this and where does your energy come from? A lot of times, the folks that have that infinite, renewable energy resource are those who are building something because there’s something broken in them. They’re just filling a leaky bucket for the rest of their life with creating something new. They find happiness and satisfaction in the work, in building, not in a specific technology or product. They just have to be putting something into the world or they’re falling apart. You work with crazy people, and I love that.

Mental health is a big factor. Depression is real, I’ve lived this as a founder—high highs, low lows. But your job is to ride that wave. You don’t want to find someone who gets one-shotted by finding peace and happiness and is no longer motivated. I’ve seen it happen where someone says, ‘I discovered the love of skiing, and now I have a family and I ski, and I’ve found balance in life and I no longer care if my company succeeds or not.’ You want to find founders who are irreparably broken, so they’re just going to keep charging forward and build. My bond with them is that I’m the same way. I’m not here giving you money trying to take advantage of what’s broken about you. I’m saying, I’m broken too, and living this path fulfills me. It can fulfill you too. Let’s go on it together.

Nataraj: That’s a pretty good way to put it. I grew up in India, and when I came to the US, I noticed a similar dynamic. Entrepreneurship in the US is so de-risked in a lot of ways. The only risk you’re taking is mostly on time. If you’re a developer at a big tech company, you should technically be doing a startup because it is de-risked. You will find some seed money eventually. The Indians who come here are a bit more broken by their childhood. They have more motivation. If you have a really stable childhood, that motivation doesn’t exist. They’re happy doing what they’re doing.

Some funds invested in narrow categories like AR/VR during the 2020-2022 period. It was a sign of so much capital that there were funds with inexperienced fund managers being created left and right. We created a lot more new funds which will never be successful.

Aviel Ginzburg: Money became functionally free. So you’re looking at, if money is free, where do I find alpha? When you run out of ideas, you say the best place to put that money is in the unknowable, in things that don’t exist yet. That led to an outrageous amount of first-time funds. A first-time VC is bringing their network with them. They haven’t yet saturated it. It’s all these amazing, smart people I know from my operating days, now let’s give them capital. Somebody can get $20 million and immediately deploy it into all these awesome-looking companies because they know the right people. An outsider looks and thinks, this person is a great investor. But you realize this isn’t really a venture capitalist; this is just someone with a great network who now has capital and just deployed it right into their network. They were not being thoughtful about if there is a real business. All that was also masked by markups.

The fun part is the excitement you get around a new idea. Then you invest, and it’s all downhill from there. Nothing ruins a good story like data. In the beginning, you’re going to the moon. Then you learn, this business is terrible, what was I thinking? You have this high, and then it goes to shit. That first investment meeting, you’re just wondering, what is this? You come into that first meeting thinking, how bad is it going to be? Then you build yourself out of the hole into a great company. That’s where the real work is. A lot of folks will not raise future funds. They’ve realized this isn’t that fun or enjoyable. The side effect is there are a lot of companies that raised money that shouldn’t have, and we’re still going through that pain.

Nataraj: I think the biggest distortion was the opportunity size. Every idea was exaggerated to be a billion-dollar opportunity.

Aviel Ginzburg: I would take that even further. People were saying there are $10 billion opportunities because unicorns went to decacorns. That started to make the model work. But if the company can only be worth $1 billion and you started at a $50 million pre-seed valuation, your fund is fucked at inception.

Nataraj: There’s also this winner’s bias. The winners became the Mag 7 and these trillion-dollar companies. So now everyone will say ‘trillion,’ and then you can justify a seed round of a billion dollars, which is happening with AI companies.

Aviel Ginzburg: There are some areas where there could be winner-take-all market opportunities. But I’ve also come to see over time this illusion that great companies have an arc that’s constantly up and to the right. Things move so fast these days that there are amazing companies where their enterprise value is high and then it goes to zero because the world moves. Part of your job is to invest in the company and know when to get out.

For example, we invested in a seed round of this company called Ally, which ended up selling to Microsoft. It was OKR software. We invested right before OKRs took off and before COVID, so there was this insane accelerant. We got approached by Microsoft for an acquisition. At the same time, we had a term sheet from a major fund offering $100 million at a billion-dollar valuation, even though we had single-digit ARR. We had many conversations with the founder about what’s the right way to go. We ended up selling to Microsoft.

Now, fast forward two and a half years. Microsoft acquired the product, put it into Microsoft Viva, and made it Viva Goals. Then they announced they’re just shutting it down because their strategy has shifted to co-pilots. They just don’t care anymore. Those two other competitors are functionally screwed. So, was that a bad investment? I underwrote a category that never came to exist. But one investment returned nearly a billion dollars and another similar one will return zero. Trying to reconcile that is crazy. You have to think about that sometimes, even in a great business, the local maximum may be the global maximum.

Nataraj: Let me ask you this, was that acquisition sort of a fund returner for your fund? So it was an easier decision for you from the perspective of the fund?

Aviel Ginzburg: As a seed investor, I was very aligned with the founder. It was a meaningful return rather than just another turn on capital.

Nataraj: This reminds me of Clubhouse, which got an acquisition offer of $4 billion from Twitter. They went and raised a similar amount from A16Z at a similar valuation. When COVID dropped, the hype for audio products dropped, and everyone featurized Clubhouse. At that time, the rational choice, even if you’ve only spent two years on the company, is to sell.

Aviel Ginzburg: I think it is. That’s the point I’m making. Just because Clubhouse got featurized and there was no long-term residual enterprise value does not mean it should be viewed as a failure. You created something of value that there were buyers for. Something does not have to exist on its own in perpetuity to be successful. We sort of lost sight of that over the past decade. It almost became a bad thing to sell your company, like you sold out. Instead, the chip on your shoulder was to build a unicorn. Now we have hundreds of unicorns that are going to go to zero.

Nataraj: One more point and we’ll shift to Foundations. This was also the time where secondaries were huge. Founders who were shrewd enough to make the rational choice of taking more secondaries were also winners.

Aviel Ginzburg: You need to be able to keep founders properly incented, so I expect some semblance of secondaries to continue. But it got nutty.

Nataraj: Moving to Foundations, I was a Techstars mentor for the last two batches before it got shut down in Seattle. I saw this story closely and can relate to how important that space was. It was one of the anchor points for the Seattle startup community. It got shut down, and I felt that Seattle is probably second or third after SF in terms of talent, but we are all somehow not living up to that potential. Talk to me about why you started Foundations, what it is going to be, and what its goal is.

Aviel Ginzburg: The general thesis is that Seattle should be a much better place to be a founder than it is. Coming out of COVID with the rise of large language models, it was embarrassing to watch the phoenix of SF proper with YC leading the charge. The difference is insulting. I went on a listening tour with founders in the area and found this desire to work and build around others, but also a desire to leave Seattle, which was not a good thing for our ecosystem.

I went back in reflection to why Techstars came to Seattle in the first place back in 2010. At that time, it was the rise of cloud and the SaaS business model. There was this new wave of founders excited to build things they couldn’t before. But there were no best practices. The magic came from people working in real-time around each other and sharing knowledge. That rhymes exactly with what we’re experiencing with large language models right now.

Every startup ecosystem needs an anchor point plus rhythms that allow the earliest stage folks, those who are actively building, and those who have been there and done that to get into the same place at the same time. The idea for Foundations was, can we do that and kickstart a flywheel? We need to anchor this around a physical space because that’s something all three of those categories need right now. We created all these different rhythms anchored by events and an entrepreneur-in-residence program to get people together. Our goal is to help people quickly on their way. Success is having a founder who went down and did YC, while others who were thinking about leaving Seattle have instead found a home and a community here. So far, it’s been a great success. Our mission is to serve the founder community in Seattle and make this a much better place to start a company.

Nataraj: So you’re doing Foundations, but have you thought about what other things should exist in Seattle to live up to its potential?

Aviel Ginzburg: There is a very big need for everything from founder matching to the incubation required to get people out from big tech companies. It’s weird about Seattle that we have more venture studios than venture funds. I think that’s because for a lot of people who have been at big companies, it’s a more comfortable path. But we should have another product here. Going to AI tinker events, you see all these people who are not quite founders, but the rise of large language models has been enough of a catalyst for them to say, I want to go out and start my own thing. There’s room for something more structured that could look like an accelerator.

Nataraj: One thing I also think is missing is that we don’t have enough pre-seed funds that write quick, small checks, considering how much talent we have. We have more studio models where it takes longer to get that first check.

Aviel Ginzburg: It’s not that hard to raise that money from the Bay. What we don’t have, and this will take time, is tons of folks in the Bay Area who made their money on startups and write 50k, 100k checks to people who remind them of themselves. The people who made money in Seattle made it by never leaving Microsoft or Amazon. They buy boats and houses on lakes. Their hobby is not investing in startups. We are starting to see those exits and people have that money, but we don’t have one-hundredth of what there is in the Bay Area. We just need to keep investing in our startup community and building things. Five to 10 years from now, there will be a lot more folks who have had those exits and can write those really quick, easy checks where they’re not asking for a business model. They’re just looking at the human and saying, I’ve been where you are, I want to be part of your journey.

Nataraj: What are you consuming right now—books, podcasts, Netflix—that is influencing your thinking?

Aviel Ginzburg: As someone who has multiple jobs and an eight-year-old, you would be surprised at how much I can consume. For podcasts, I listen to All-In, Rogan, and Jordan Peterson, and then I just pick up random other things. I love sci-fi, so I pretty much watch every sci-fi show that is out there. It’s been a year since I’ve sat down with a good book, but I was reminded to reread ‘The Courage to Be Disliked.’ I would highly recommend that book to anyone who’s ambitious.

Nataraj: What do you know about investing that you wish you knew when you first started out?

Aviel Ginzburg: The feedback loops on investing are really long. I am a builder; I started my career as a software engineer. As an investor, if you try to do more than you should, you mess things up because you are not the co-founder. If you are the type of person who really needs the dopamine hit of having an impact, you need to find other places in your life to place that energy, hopefully in ways that are accretive to your work as a VC. And that doesn’t look like just shit-posting on Twitter, because that’s what I see a lot of people do with that energy.

Nataraj: I think that’s a good note to end the conversation. Thanks for coming on the show and sharing your thoughts. I hope Foundations will become an anchor for the Seattle ecosystem.

Aviel Ginzburg’s insights offer a valuable look into the mind of an experienced founder and investor. His focus on founder psychology and his mission-driven approach to rebuilding Seattle’s tech community provide a compelling roadmap for the future of the ecosystem.

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In this conversation, Nataraj sits down with Jacob Bank, the founder and CEO of Relay, a startup building AI agents to revolutionize how we work. With a rich background in AI and productivity from his time at Google and as the founder of Timeful (acquired by Google), Jacob offers a unique perspective on the intersection of automation and artificial intelligence. He shares the winding journey of Relay, from its initial concept as a cross-product collaboration tool to its current form as a powerful AI agent platform. Jacob dives deep into the challenges of building in a rapidly evolving market, the importance of robust integrations, and the product-led growth strategies—particularly his success on LinkedIn—that have propelled Relay to early product-market fit. This discussion is a masterclass in modern company-building, navigating the AI landscape, and understanding the future of automated workflows.

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Nataraj: What is Relay and how did it get started?

Jacob Bank: Relay.app is a platform to build AI agents. The journey has been a bit winding to get here. I started the company in 2021. My background is in academic research in AI and then building productivity tools. When I started the company in 2021, we had two founding premises. The first was that we all use a lot of tools to get our work done. The builders of those individual tools spend a lot of time figuring out how to make experiences within those tools better, but probably not enough time figuring out how those tools interact with the others in your ecosystem. For example, I used to be the product lead for Gmail and we would agonize about every single pixel when you were archiving, replying to, or starting an email. But if you said, ‘Hey, I really need to get data out of Gmail into Notion and then also Salesforce and then send a Slack message,’ we’d say, ‘Sorry, good luck. Use the API.’ When we looked at what knowledge workers are actually doing, a lot of what we do is take stuff from one tool, do some stuff with it, and then stick it in another tool. We thought there was an opportunity where people were underestimating the importance of cross-tool coordination. And second, it sounds so silly to say this now, but it was not obvious in the summer of 2021 that AI was going to be important in doing this. The original name of the company was Collab AI, and we didn’t know exactly what product we wanted to build, just that it was going to help with cross-product workflows and that it was going to use AI somehow to do that.

For the first year and a half of the company, we wandered in the desert, as they say. We built eight or nine different product prototypes that all fit that theme, but none were quite right. We built an automated to-do list, a contextual knowledge base, a stand-up tool, and an employee onboarding tool. Eventually, we landed on a workflow tool. A workflow tool that captured repeated tasks that had an element that can be automated and an element that required human judgment. That’s why we named the company Relay, because we were thinking so many things we do should be a relay race where the computer does some stuff and the user does some stuff. We announced our beta at the end of 2022 and ran it in 2023. By the end of the beta, we realized that maybe there was a category to be created there, but it wasn’t us who was going to create it. It just wasn’t right. When you’re an entrepreneur and you’re just muscling something through that’s fundamentally not right, there’s too much friction.

So in the summer of 2023, we decided we were going to build an automation tool. We would focus on the market that Zapier is the leader in: cross-product horizontal workflow automation for a non-technical audience. But we were going to try to build the modern version of it. What makes it modern is that it’s way easier to use for non-technical people, it has AI better integrated into the workflows, and it has human-in-the-loop capabilities so you can correct your AI when it gets stuff wrong. In 2024, we were an AI-powered automation product, positioning ourselves as the modern alternative to Zapier. We got to initial traction and then early product-market fit. But we realized that by positioning ourselves as an automation product, there were two major limitations. One, you limit the audience of people that think you’re the tool for them. We want to tackle the much bigger opportunity of helping every business get more work done with AI. And second, we didn’t want to be perceived as a duct tape product that only exists to temporarily glue two products together. We want to be a transformative tool. So the evolution we’re making now is transitioning from an AI automation platform for no-code workflow builders into an AI agent building platform for everyone.

Nataraj: When I see a product similar to yours, the problem is we are using so many tools and so much data is spread across different things. How are you prioritizing which tools to bring into the platform?

Jacob Bank: Right now we have about 120 native integrations. The way we think about it is that there are about 12 categories of tools that pretty much every business needs. Every business has an email client, a calendar client, a messaging tool, a CRM, an email marketing tool, an e-signature tool. There are these 12 to 15 categories that are quite ubiquitous. In each category, there are three to 20 players that have material market share. We’ve basically just tried to work our way down that list for our target audience, which skews towards small and medium-sized businesses. If you’re a regular SMB using modern tools, you’ll probably find everything you need with Relay. Zapier has 7,000 integrations; I don’t think you need 7,000. I think that’s a vanity metric. The number we need to get to is probably somewhere between 300 and 500 for the product to really feel complete. I believe integrations are skilled labor. I don’t think this is something you can just outsource. Building a really good Salesforce integration is really hard software engineering. Second, I believe agents will only be as useful as the robustness of their ability to interact with the tools you use. There are two big schools of thought: do everything in the browser or build on top of APIs. I think every serious player will need to do both, but if an API is available, that’s almost certainly a more efficient and robust way for the AI to interact with the product. We have focused entirely on robust API-based integrations.

Nataraj: What has the traction been like? Give us a little bit of insight in terms of the scale of the company right now.

Jacob Bank: We’re now at 440 paying customers. We have about 1,200 weekly active teams. That’s up from essentially zero when we launched at the very end of 2023. I’d call it early product-market fit. My personal definition of product-market fit for a product-led self-serve business is: could I go on vacation for a week and come back with more users, more customers, and more revenue? That is now true of our business. With 440 paying customers, there’s enough there to say that you’re not just a bespoke consulting shop for one or two companies.

Nataraj: What are you doing to drive this adoption further? I think you’ve done very well in terms of product-led content growth, especially on LinkedIn.

Jacob Bank: That’s super recent; we only figured that out in the past month. We’ve been building from the back of the funnel to the front of the funnel. Meaning we started with retention and depth of engagement, then moved to activation, and now have moved to working on top of funnel. In my first company, Timeful, we got 300,000 downloads the first weekend and retained none of them. I was scarred by that experience. So for this company, I would rather have 10 rock-solid, retained customers and then figure out how to bring more in. The strategy that makes sense for our kind of product has to be facilitated word of mouth, facilitated by content, community, and partnerships. I spend a lot of my time on content creation. One type is LinkedIn posts, which are teasers that illuminate a use case for an AI agent. I’ll post something like, ‘I just built a cool AI agent to synthesize insights from my customer calls.’ I’ll make a six-second GIF about it and pair that with long-form YouTube tutorials that show you how to actually build it. On LinkedIn, I now have 15,000 followers, and I’m getting about 150,000 impressions a month. Our YouTube channel will cross 10,000 views for the first time this month. It’s an order of magnitude fewer views, but super high intent. About 25% of our paying customers come from YouTube. Now that we have a robust community, many of them are writing LinkedIn posts or building templates, which helps solve the problem of people figuring out what to use a horizontal product for.

Nataraj: How come there’s no LinkedIn integration when you post so much on LinkedIn?

Jacob Bank: We’re actually in the review process from LinkedIn right now. We’re waiting for them to flip the bit to accept us, but it’s coming very soon.

Nataraj: What integrations are coming in the next couple of months?

Jacob Bank: We have a public roadmap. LinkedIn is at the top. WhatsApp is coming—that’s a really highly requested one. Xero, the accounting provider, is another. We have a few more social media integrations to build, like deepening our YouTube integration and building an Instagram integration. We need to deepen our integrations with website builders like WordPress, Squarespace, or Wix. We just have Webflow at the moment. The drumbeat of integrations will go on forever, but we really want to cluster around the use cases where we’re seeing the most traction: content creation and marketing, research use cases in sales, and general back-office operations.

Nataraj: There’s a lot of overlap with Make.com and Zapier. Do you see them as competition, and how are you differentiating?

Jacob Bank: When people are deciding between Relay and other products, they typically consider two categories. One is the traditional automation players: Zapier, Make.com, N8n. The other is the new AI agent builders: Lindy, Gumloop, Relevance. With respect to Zapier, our main differentiations are a way easier product experience for non-technical users, AI is integrated much more natively, and we have human-in-the-loop support. For the AI agent builders, they typically have good AI primitives because they’re AI-first, but they don’t typically have the depth and robustness of integrations or perfect usability. We all have our strengths and flaws, but we’re all kind of circling around the same opportunity.

Nataraj: This is your second company, and you sold the first one to Google. What didn’t work in that company, and what are you trying to avoid doing in this company?

Jacob Bank: Two big lessons from that company. The first is that we let ourselves be a little seduced by top-of-funnel numbers when we should have focused on having 10 super high-value retained users. The second was we just didn’t understand business. It was like, oh, we’ll just build a mobile app like Instagram and eventually get bought for a billion dollars or monetize it with ads. It turned out there was this other business model of subscription B2B SaaS, which totally existed in 2014, but it wasn’t in our DNA. So for this company, I wanted to make sure it provided rock-solid value, high engagement, and high retention to a small set of customers before we expanded. And second, that from the very beginning, the business model made sense.

Nataraj: You are at the edge where you might be called automation, but if you push, you’ll be called agents. How do you think these will look in two years?

Jacob Bank: I think there are three principles that are going to be really important in agent building. One, agents will need a robust and reliable mechanism to interact with all your tools, likely through APIs in the next two years. Two, agents will need to give you some sort of intermediate representation of what they plan to do before they do it and give you the ability to give feedback. And third, you need a great human-in-the-loop mechanism to correct things and help the agent learn. I think we will primarily use natural language to instruct an agent, then iterate on its plan, and then work with it to get the final output. This pre-compiled version of the flow chart is more understandable to users and will run more reliably and faster in practice.

Nataraj: What’s next in terms of scaling? Are you planning to fundraise?

Jacob Bank: We don’t feel any need to fundraise at the moment. We have plenty of runway, and our revenue is growing quite quickly. It looks like we’d be able to make it to profitability if we had to. That said, we will likely want to raise additional capital because it’s such a big opportunity. But my philosophy on company building has changed. It used to be you raise a round and triple the company size. For the kind of business we’re building—we have nine people right now—I can see us needing 12 or 15, maybe 20, but I don’t see a near-term future where we need 200. Modern company building is going to look very different.

Nataraj: This was an amazing chat. Thanks for coming on the show and sharing all your insights.

Jacob Bank: Thanks so much, it was a blast.

This conversation with Jacob Bank highlights the incredible potential of AI agents to transform business operations. His journey with Relay provides a clear roadmap for building a modern, lean, and highly effective company in the age of AI, focusing on real customer value over vanity metrics.

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With a career spanning over three decades, David Blumberg of Blumberg Capital is a veteran of the venture capital world. His journey began in the early days of tech, long before the dot-com bubble, shaping his perspective on what truly drives innovation and success. David was one of the first American VCs to recognize the potential of Israel’s tech ecosystem, contributing to its rise as a global ‘Startup Nation.’ In this conversation, David shares his wealth of experience, from his first investments at T. Rowe Price to founding his own firm. He delves into the key principles that have guided his investments through multiple economic cycles, the unchanging truths of human nature in a tech-driven world, and the importance of backing serial entrepreneurs. He also provides a look into his current investment thesis, focusing on data-intensive companies and the transformative power of AI.

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Nataraj: How did you get into investing in early-stage tech companies? At what point did you decide that you should start investing in tech companies?

David Blumberg: I’ll go all the way back to my high school days because I’m from that generation that came of age after the Watergate scandals of the 1970s. That was an era when a lot of people were depressed about the future of America, about the future of government, and about the ability to solve big problems. I was idealistic. I wanted to solve problems, so I thought I should go into government. I was lucky enough to go to Harvard College, where I started to study international relations in the government department and economics. I loved the courses and was soaking it up like a sponge. I worked in Washington for three summers and after those three summers, I realized that Washington was a place that causes a lot of the problems, it doesn’t solve them. They try, but they have this problem called unintended consequences, which often happens in a non-linear fashion, and a lot of their projections are made in linear models.

At the same time, I had three big influences that moved me toward business. One, I was a middle-class kid, so I needed to work. I started a business at Harvard called Harvard Distribution Services. That company still is going today. It’s part of Harvard Student Agencies. I employed 100 kids doing distribution and courier service. It wasn’t a tech business by any means, but it was so much fun to serve customers, hire my friends, get paid for it, get feedback, and build new ideas for what we could offer them in the future.

Then I had this negative experience in Washington where it was very sexy. I was close to power, at the foot of a senator learning about all these policies, but there was just this level of bureaucratic slowness and lethargy. Nobody cared that the taxpayer was always on the hook, and there was no accountability. I didn’t like that.

Then there was the other interesting thing. I did a thesis on African-Israeli relations between 1973 and 1981. A relatively obscure topic. In 1973, there was an oil embargo after the Yom Kippur War. The Arab countries mostly forced the African countries to break diplomatic ties. But in those same years, trade went up 800% between those same countries that had just broken off diplomatic ties. I thought this was unusual. What I found out by doing a lot of research is that it was the business people, the military people, and the ministers and priests who would bring their flocks to the Holy Land that kept going despite the political rhetoric. They had real interests—economic, military, and religious—and those persevered over the political noise at the UN.

Here’s my conclusion. I decided that I want to help impact the world while I’m alive. I’ve benefited from the history of all the progress of Western civilization, and I want to increase goodness for the world and help everybody thrive. My watchword is human flourishing. To me, the most high-impact way to achieve human flourishing is a combination of capitalism and science. The vehicles, the prophets that drive that forward are entrepreneurs. So I am all about entrepreneurs. I love entrepreneurs. I am an entrepreneur, but mainly I back them now as a venture capitalist. That’s my role in the world, and I feel blessed and grateful that I get to do this every day.

Nataraj: When did you first start investing in a tech company, and if you can remember, what was the first tech company you invested in?

David Blumberg: It was as a public investor. After Harvard, I went to T. Rowe Price, as you mentioned. At T. Rowe Price, I was on the technology team as an assistant securities analyst. My job there was to meet companies that were often about to go public, so they were private and about to do an IPO. I would form an opinion on their financial progress, their future, and their marketing relative to their peers. We would come up with a thesis about which of the IPOs in a new industry we would want to invest in. I started investing that way by making recommendations to the portfolio managers. One of the ones I remember investing in was a company called Scitex. You mentioned that I also invested in Israeli companies for a long time.

That was interesting because T. Rowe Price had never invested in a public Israeli company at that point. Their theory at the time was, ‘Israel’s a very socialist country. It has a very high inflation rate, and there are these periodic wars and terrorism. It’s probably a dangerous place. We shouldn’t invest there.’ My counterargument was that’s already priced into the stocks. Their price-to-earnings ratio was lower than a comparable company in the US or London. They bought my argument, and we started to look at Israeli companies and start to buy them. Scitex was one of the first that helped get into the T. Rowe Price portfolio.

Nataraj: So this is an Israeli company that was going public, or already public, and Israel was considered a socialist country at that point in time.

David Blumberg: At the time in the 1970s and 80s, yes.

Nataraj: I remember India was mostly considered socialist until 1990 when the economy opened up. That makes sense.

David Blumberg: India and Israel share a lot in common. They both had the experience of British colonialism. The British did some good things, and some bad things. One of the bad things was that there was a very powerful group of economists from the London School of Economics that believed in import substitution as an economic model. Israel was told to do that, and India was told to do that. It was completely the wrong idea and really messed a lot of things up. For example, when I first went to Israel, they had a very strong tariff on personal computers. I said to some of the government folks, ‘If you’re trying to build a software industry, it doesn’t make sense to have high tariffs on the tools you need to write software.’

Over a period of time, not because of me, they started to reduce tariffs and regularize taxation of venture capital funds. But in the early 80s, there really wasn’t any venture capital in Israel. There was onerous taxation and not the kind of stock option permissibilities that we take for granted in the US. Silicon Valley was novel. Some lawyers tell me that I was the first person that brought a standard Silicon Valley term sheet from Wilson Sonsini over to use on a deal in Israel in the early 80s.

Nataraj: There’s this amazing book called Startup Nation about Israel. Silicon Valley is obviously the gold standard for tech innovation, and Israel probably comes second or third internationally.

David Blumberg: Certainly in density per capita, it might even be higher in terms of entrepreneurs per capita. But Silicon Valley is the center, no doubt.

Nataraj: There’s an interesting comparison of countries which got independence around the same time as Israel. For example, South Korea and Israel. But Israel was able to develop a tech sector that is as innovative as Silicon Valley. One of the projects that helped them was Yozma, where the government allocated funds and made it lucrative for venture funds to come into Israel. Were you exposed to or part of Yozma at that time?

David Blumberg: Yes, I was very involved. I even helped contribute to some of their ideas, in a very small role. But most of the credit goes to other people. Here’s what I want to push back on: the notion that government leads on these things. I don’t really believe that. I was invited by TIE, The Indus Entrepreneurs, to come to India on a delegation in 1999 to talk to the leaders of India. We met with the finance minister, the military folks, all kinds of leaders of the economy. They said, ‘We want you to tell the story of Israel because Israel had the same British colonial history. They were also a people full of mathematicians and scientists like India, and yet both of those countries lagged until they had a takeoff.’

These Indian folks said, ‘We were village boys in India. We came to a good university, then we went to America and became super successful entrepreneurs because of the American system of the government getting out of the way.’ Whereas in India, Israel, and most developing countries, there’s so much bureaucracy and red tape, which allows bureaucrats to get rich through corruption. It really impairs and depresses entrepreneurial energy. The most important thing for governments to do is just get out of the way and let the entrepreneurs do their thing. We have too much permitting, too much regulation, too much red tape. It’s very hard to do things now in the United States and in most Western democracies. We get sclerotic. What India needed to do was get out of the way of its own people. Israel had to do the same thing. Israel had, since 1948, the most advanced technological workforce in the world per capita, but they were not that successful in tech until the government got out of the way. They had economic reforms and allowed stock options and equity structures. I’ll remind you that in the late 80s, the Israeli economy crashed entirely. The banks failed, the government nationalized all the major banks. It was a complete disaster. It was only with the help of Chicago-style and MIT economists who basically said you have to allow the free market to work its magic. The same thing is what we told India in the 90s, and you’ve seen the power and growth that India has enjoyed too. It’s not that government leads so much as it just needs to get out of the way.

Nataraj: I think I agree with you. The way I understood Yozma was they sort of aligned the incentives and got out of the way.

David Blumberg: Let’s go specifically to Yozma. Most governments are driven by political goals. In Yozma, certain constituents wanted private sector institutional funding. That became the Yozma program. There was another fund to get the retail investor interested. Yozma did a program where if I raised a fund of $100 million, Yozma would put in another $100 million. At the end of the fund’s life, if the fund was a success, we, the investors, could buy out the government at cost—a great deal. The other program, which did not work very well, was an insurance policy attached to publicly traded venture capital funds. It did not work. Again, it’s government trying to be too smart and do too much. The main thing government had to do was get out of the way. I will applaud Yozma because they insisted on one good thing, which was cross-collaboration between experienced international venture capitalists from the US and Europe and Israeli local investors who were doing this for the first time. That was positive because there was a flow of information and a transfer of knowledge.

Nataraj: Another interesting fact about the Israel ecosystem is Warren Buffett’s first investment outside the US was an Israeli company. Intel’s first office outside the US was in Israel.

David Blumberg: Yes, Iscar.

Nataraj: The founders they come up with are usually very exceptional and one of the highest quality of founders that I’ve ever seen in any other ecosystem.

David Blumberg: That did not exist before. Israel did not have MBA programs or a culture of appreciating entrepreneurs. In the old days, under the socialist regimes, the smart kids went into the government or the military. Then a few people became successful entrepreneurs, and they became paragons and role models for the next generation. I will credit this: the Talpiot and the 8200 programs, these special units in the military that recruit the brightest people, give them great training, put them in a small group, give them a budget and a deadline, and say, ‘Here’s your project. You must design this new kind of technology.’ They’re bonded through fire. They put people together who know electronics, physics, radar, and tell them, ‘Build this, and your grandmother’s life depends on it.’ These people are forged together, tempered like fine steel. When they come out of the military, they have been bonded and tested. When you’re finding a co-founder, if you’ve been through that experience of the military together and you’ve had each other’s back, it’s a very powerful way of determining if this person is going to be a good co-founder.

Nataraj: Before starting your own firm, you also worked at Claridge. Talk to me a little bit about that experience and how that shaped your investing later on.

David Blumberg: I’m going to go backwards a little bit because my first mentor was Fred Adler. I met him when I was at T. Rowe Price, and he was the only big, successful American investor who was also willing to invest in Israel. I was interested in that combination. I want to give him great credit because although he was a very difficult man, he was brilliant and he exposed me to venture capital. Then I was fortunate to work with Alan Patricof, another great venture capitalist. And then I worked for Charles Bronfman at Claridge, which is the family office of the Bronfmans in Montreal. I was investing in the US, Canada, and Israel. Family offices have different criteria than a traditional venture capital fund. They had certain personal issues they wanted to steer clear from and other areas they wanted to emphasize. Their background was real estate, which was a little incompatible with my background in venture capital. I had to push and pull and try to explain why we should structure deals in a certain way. For example, they were used to structuring deals with debt. I pretty clearly explained that debt in a venture capital structure in the early stages is not really worth the paper it’s written on, and we need to be equity owners and get rewarded for that equity risk.

Nataraj: So then you went on to start your own firm.

David Blumberg: That’s right. The best deal I did at the Bronfmans, which I’m kind of proud of, was a little pharmaceutical company in Israel. I looked at it as an acquisition. The Bronfmans were not willing to do it on our own. So we bought a company called ABIC and back-to-back flipped it right away into Teva Pharmaceuticals in return for a large stake. Teva at the time was only worth about a billion dollars and later rose to between 40 and 60 billion. It was a rocket ship, selling to 50-plus countries. It’s now the largest generics manufacturer in the world. It was a real testament to that Israeli innovation mindset.

Then, moving on to Blumberg Capital, I started that in the early 90s. At first, I didn’t have a fund, so our team was very small. We called it a virtual venture catalyst. We would work with investors, mostly family offices, to find deals for them. In compensation, we received a retainer, cash on the completion of a deal, and equity as a kicker. We had nine investments, and it was a 9x return on that portfolio. Four IPOs, four M&A exits, and one death. In 2001, Blumberg Capital raised its first venture capital fund. Since then, we’ve raised six funds and now have about 65 companies in the portfolio. Our offices are in Miami, New York, San Francisco, and Tel Aviv. We’re about 27 people on the team. We have two strategies: one is early stage, focusing on pre-seed, seed, and A rounds. Then we have a growth fund that starts late A, early B.

Nataraj: When you started your first fund, to now, it’s more than 20 years. Valuations have changed, things have changed drastically. What didn’t change in this business?

David Blumberg: What did not change? I love that question. I’ve got a great answer. Technology changes, human nature doesn’t. The lesson we learned from that is the context is constantly changing. Valuations are up and down. We know that there are cycles. Nothing lasts forever. The average length of duration on the Fortune 500 list used to be about a century; now I think it’s down to about 15 years. Most of the large companies of today didn’t exist 50 years ago. So the pace of change is accelerating. The lesson of life is keep running. The lesson of Silicon Valley is keep up with the change.

Human nature is going to stay the same. There are jerks, and there are great people. There are incentives that motivate people and bureaucratic constraints that slow people down. My lesson from venture capital is it’s about the network. It’s about the people. If you treat people right, as you know from the karmic principle, it will generally come around to benefit you. If you screw people up, they’re going to remember. If they screw you up, hopefully, you will be smarter the next time and not want to work with them again. So I think that technology changes and you’ve got to keep up with it, but human nature is quite stable. We have been so blessed to work with serial entrepreneurs. We’ve backed them one time and they were successful, twice and they were successful, and sometimes we’re on our third round with these entrepreneurs.

Nataraj: Who are some of those entrepreneurs that you repeatedly work with?

David Blumberg: One fellow is Oren Netzer, the founder of DoubleVerify. We invested $8 million in the seed, A, and B rounds. Ultimately, we were able to take out $578 million in profits when the company went public. He’s started a new company called DataHeroes, and we’ve invested in that. Another example is a man named Dan Sanker. Dan has been the CEO of two of our companies. One, CaseStack, in the logistics area, was sold for $255 million. The acquirer did not want a small skunkworks Dan had set up, so I said to Dan, ‘Let’s just take it and build another company.’ We built another company, and seven years later we sold that company, SupplyPike, for another $216 million. Now Dan is going to do the next company with us, so that will be the third time. Another is Benny Nachman, the founder of Credorax, an Israeli/Maltese merchant acquiring bank. That company ultimately sold for $1.1 billion to Shift4. Now he’s started a new company called Jazzypay, which we’re also invested in. These ties that bind are absolutely wonderful because I know how he thinks, he knows how I think, and we trust each other. We’ve been through hell and back together.

Nataraj: In pre-seed, there is no data. It’s all qualitative. Talk to me a little bit about your decision-making in pre-seed, especially for a new founder.

David Blumberg: At the pre-seed stage, the premium is on the team. The team is much more important because they’re going to pivot no matter what they say. Something’s going to change. A successful investor once told me, ‘No good company pivots less than twice.’ I don’t know if that’s statistically true, but the point is very few people can really predict the future. It’s opaque, it’s unknowable, it’s probably non-linear. So you’ve got to be able to react quickly and effectively. A great team is more likely to do that than a not-so-great team. We look mostly for the teams. I also look for large market potential because it’s better to hit a big target. We also favor industries where there’s not a lot of competition. My friend Peter Thiel talks about this a lot, like little monopolies. Some of the best companies, like DoubleVerify and Nutanix, really didn’t have much competition at all when they started. Or what they were doing was very distinct. We could differentiate and say, ‘They do it this way, we do it differently, here are our advantages.’ So, team first, large market, and minimal competition are three of the key factors for us.

Nataraj: I’ve come to think of two criteria in pre-seed. One is I want an absolutely insanely talented founder, and my definition is they must be writing code way better and faster than any senior team inside Microsoft or Facebook. Do you have your own definition of what talent is for you?

David Blumberg: You remind me of my mother who used to say, ‘Before we had children, I had three theories about raising them. Then I had three children, and I no longer have any theories.’ My analogy would be Nutanix. We were the first investor. We made hundreds of millions of dollars on the exit. They came to us and described exactly what you said. Mohit Aron was one of the most technical of the three. He was considered one of the 50 best programmers in the world. He came from Google, he helped develop the Google File System. He and the other two founders said, ‘We’re going to do what Oracle does for storage. Everybody buys these old, big systems that are hardware and software. Instead, we’re going to emphasize the software and buy commodity hardware.’ We have this wonderful CIO Council. We took the Nutanix trio to them and said, ‘If they build this virtual storage idea, would anybody buy it?’ Three hands went up. Those became their initial customers. But the funny story is, you’re right, they were all really talented. Mohit was probably the most talented coder, but Dheeraj was an executive and Ajeet was the other fellow. They were all brilliant. Each of them started unicorn companies. Ajeet started ThoughtSpot, and Mohit started Cohesity. So they split up, but they were each successful in their own domain. So I think quality is recognizable. You tend to want it to be coding quality, but there are other qualities. I heard somebody recently say that every CEO needs to be the best salesperson for their company. I think that’s true. They may not be the best coder, but often the lead in the company is going to be the more business-oriented person.

Nataraj: You talked about the CIO council you have. Talk to me about that council and how it’s helping you pick winners and losers.

David Blumberg: Our innovation council consists of chief information officers, chief security officers, and chief technology officers. We get them together about four times a year. They really enjoy conversations among themselves on a topic of mutual interest, like AI in production applications given privacy constraints. We’ll have them talk about that topic, and then we present a couple of our companies, either before or just after we’ve invested, and we get feedback for the entrepreneurs from this council about how well the messaging is coming through, product-market fit, pricing, and the go-to-market plan. A lot of feedback comes, and often what comes next are design partners. It really helps because there’s credibility that we’ve built up over decades of bringing them companies like Nutanix, DoubleVerify, and Braze. When these CIOs see something from us, they know that we’ve vetted thousands of companies down to a few that we invest in every year.

Nataraj: I always like to ask investors where they’re investing their own personal capital. Can you talk a little bit about your own strategy?

David Blumberg: Sure. First of all, I’ve been very fortunate to become wealthy through the venture capital business. We’ve had a lot of successes, and the carried interest really rebounds to the benefit of the investor founders. A lot of that capital comes in the form of stock in public companies. I’ve often held those stocks. Sometimes I do what’s called an exchange fund, where I’ll take a chunk of a concentrated stock and trade it over a period of eight years tax-free into the S&P 500. So I diversify without any transaction costs.

I’ve also personally invested in real estate and particularly one non-obvious area. I really enjoy investing, and I’ve made a lot of money in oil and gas and fossil fuels. That’s very uncool, but I am what’s called an energy humanitarian. It’s fine for wealthy people to feel good about themselves by thinking about green energy, but you come from India, so you understand there are hundreds of millions of people that have zero electricity. There are 700 million people on earth with zero electricity today. Four billion people have less than four hours a day of access to electricity. The world needs a lot more power. The only possible way we can get the poorest people on earth to have enough energy is if we utilize more of the God-given resources of natural gas and coal. I’m all in favor of innovation—solar, wind, nuclear, hydro—where applicable. But the vast bulk, 80-plus percent of the world’s energy, is still coming from fossil fuels. So while everybody’s voting against it, I vote for it, and I make lots of money because when people are voting with their emotions instead of the data, they lose and I win.

Nataraj: Who are the investors you admire the most and like to learn from?

David Blumberg: Peter Thiel is a friend, and I admire him greatly for his intellect, his ambition, and his rule-breaking mindset. Joe Lonsdale is in a similar vein, and we’ve invested a lot together. I also think that Marc Andreessen and Ben Horowitz are amazing; they’ve built an incredible franchise relatively quickly. Of course, the classics, the people at Sequoia like Moritz and Leone, are tremendous. And I’m old enough to have worked with some of the great guys from the old generation. Venture capital has changed. When I was starting out, it was very much a hardware business, centered around semiconductors and test equipment. That’s why we call it Silicon Valley. Today, obviously, it’s coders that are at the top of the rank. Now we’re automating the information world, the world of knowledge workers, the world of data. That’s why we at Blumberg Capital look for data-intensive companies that can sell into one vertical or more, using intelligent algorithms to shape, refine, distill, and interpret that data. Every industry on earth can become more productive. My way of describing venture capital is we are the outsourced R&D function for large corporations.

Nataraj: What are you consuming right now—podcasts, books—that is influencing your thinking?

David Blumberg: This always shocks people. I’m a huge reader of the Bible. I think that the Bible is the greatest guide to human nature, to wisdom, and to what really matters in life. I have a specific version I like by Dennis Prager called ‘The Rational Bible.’ It doesn’t require suspension of belief or disbelief in science; it’s totally copacetic with science. But it teaches you why and should, rather than just what and how.

In other domains, I love listening to economics podcasts and edgy technology discussions about what’s going to be next in four, five, or 10 years. Also on demographics and regulatory changes. I like to read the editorial page of the Wall Street Journal. A politician who doesn’t understand economics is not going to be helpful, and an economist who doesn’t understand politics is not going to be successful. One needs to know both. I would say the most important thing is continuous learning. I’m told that an engineer today is outdated in seven years after they graduate from college because things are changing so fast. So nobody’s a genius constantly. You need to continue learning, and the best way is learning from other people.

Nataraj: Who are your mentors who helped you in your career?

David Blumberg: Fred Adler was one of my great mentors. A lady named Abby Joseph Cohen hired me at T. Rowe Price; she went on to become the ‘Queen of Wall Street’ at Goldman Sachs. Alan Patricof has always been a gentleman. Charles Bronfman is a prince of a human being, a great philanthropist. And the people I learned most from are the entrepreneurs we’ve worked with because they’re always confronting really difficult challenges. I love watching the way their minds think about how to overcome a challenge. That’s the beauty of being an entrepreneur and the privilege of being a venture capitalist.

Nataraj: One last question, what do you know about investing now that you wished you knew when starting your first fund?

David Blumberg: This is very easy. The most important thing for young people is to always get your contracts pinned down. Make sure you have a contract and it’s clear, especially if you’re doing consulting. Make sure that everything is written down and bound into a contract because after one starts a project, people’s memories change, incentives start to diverge, and you can get into a big fight. The most important thing is to get everything squared away up front. You can always adjust it later, but if you don’t get it signed, you’re at grave risk of losing what you’ve worked so hard for.

David Blumberg’s insights offer a timeless perspective on venture capital, emphasizing that while technology constantly evolves, the fundamentals of backing great people and solving real problems remain the same. His story is a masterclass in long-term vision, resilience, and the power of building lasting relationships.

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In this episode, we sit down with Court Lorenzini, the visionary co-founder behind the $16 billion e-signature giant, DocuSign. Lorenzini takes us back to the early days, revealing that the path to success was a ‘slow grind’ rather than an overnight explosion. He shares the fascinating inside story of how a presentation at Microsoft’s executive briefing center led to landing them as a pivotal first customer, providing the seal of approval that catalyzed their growth. The conversation also explores the strategic partnership with the National Association of Realtors, which embedded DocuSign into the daily workflow of millions. Beyond DocuSign, Lorenzini opens up about his subsequent entrepreneurial journey, including a spectacular failure and the invaluable lessons learned. He now channels this wealth of experience into his latest venture, Founder Nexus, a community designed to help fellow founders navigate the treacherous startup landscape and increase their odds of success.

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Nataraj: You’ve started several companies; I’ve lost count on your LinkedIn profile. Everyone knows DocuSign, which has a market cap of $16 billion today, but you’ve founded a couple of companies before and some after. Could you share a bit about your career up to now?

Court Lorenzini: Certainly. I started my career as an engineer. My undergraduate degree was in engineering, and I did three postgraduate master’s programs in different forms of engineering. But I always knew I wanted to be an entrepreneur, so for me, that was just a pathway to getting to where I am now. Early in my career, I worked for a semiconductor equipment company, ran a division for them in Europe, and then went to work for Cisco in the early days when it was on a rocket ship. During the years when Cisco was considered the fastest growing company ever, it was a fantastic place to learn leadership.

Nataraj: I’ve had several guests who were at Cisco during that rocket ship phase. It fostered a lot of successful people.

Court Lorenzini: It was a great place to learn. I moved to the Northwest in 1996 and started my first company at the dawn of the internet era, before e-commerce. I built one of the very first e-commerce engines and ended up selling that company. I tried my hand as a venture capitalist for a bit but realized I enjoyed building companies more than investing in them at that time. DocuSign was my second company, which I co-founded with a friend who had worked for me in my first company. I ran that as the founding CEO until 2008 and then left because my passion is the first phase of a company. I love what I call the ‘napkin to product-market fit’ phase, where every decision is life or death. That’s my favorite part of growing a business. In my career, I’ve structured it so that by the time I get to about year five and there’s a product-market fit signal, I tactically exit and go start another one from scratch.

Nataraj: When you were starting DocuSign, what was the original thought? Did it evolve?

Court Lorenzini: My co-founder, Tom Gonser, had the idea. He came to me after leaving my first company. His own company was in the process of selling assets from a prior venture it had acquired called DocuTouch. He called me and said we should build a company around the IP his company was trying to get rid of. In that IP package were two things of value: the trademarked name DocuSign and an issued patent for signing documents via the internet. I thought that was interesting. We extracted that, bought the IP from his company, and that’s the basis around which we founded DocuSign. He left his company, and we built it together. It was amazing.

Nataraj: Was it obvious from day one that this was going to be big, or was it a slow grind to product-market fit?

Court Lorenzini: It was a really slow grind. I remember telling the very first venture investor that it was going to be a winner-take-most proposition. They kind of scratched their head, and I said that someday, one market leader would have about 70% of the worldwide market share. There would probably be a second player with about 20% and a bunch of copycats in the last 10%. If you roll the camera forward to today, DocuSign owns about 76% of the worldwide market, Adobe has about 12%, and everybody else is in that last 10-12%. It came true exactly as I predicted over 20 years ago. It was not obvious; it was a grind. It took a lot of creativity to figure out how to get product-market fit, and it took years. We founded it in ’03 and didn’t go public until 2018, so it was 15 years to a public offering.

Nataraj: Who were the first or most impactful customers?

Court Lorenzini: The most impactful relationships were the ones that took it from ‘kind of cool’ to ‘going to be amazing.’ The first one was Microsoft. This was an interesting story. We were a very early adopter of .NET technology. It turned out that at Microsoft’s executive briefing center, the .NET team was presenting to executives. Without telling us, they used DocuSign as an example of a company using .NET in a cutting-edge, valuable way. In the audience was the chief legal counsel for Microsoft. From that meeting, I got an inbound phone call from him saying, ‘I was just at the EBC. I heard this thing is really cool. We should be using that.’ That’s how we landed Microsoft. It wasn’t me calling them; it was them calling me. Because it came from the legal team, it was blessed inside the organization from day one. At that moment, Microsoft was the biggest company in the world, so that helped a lot of other companies get comfortable. It was the seal of approval I needed. The next one by far was the National Association of Realtors (NAR). The NAR had software used by three million realtors nationwide to create home purchase and sale agreements. They liked what we had and agreed to embed our signing tool inside their software as a white-label deal. This meant every realtor in the country immediately had an opportunity to send documents to home buyers via DocuSign. That was a huge deal because it gave us volume and exposure to an incredible group of end-users who had day jobs where signing things electronically would be fascinating. We got a tremendous amount of lift from that deal.

Nataraj: It seems like a sign you’re solving a real problem when customers come to you inbound. You predicted one player would dominate 70% of the market. It’s a seemingly simple software, so why does DocuSign still hold that position against competitors in the broader document management space like Adobe, Google Docs, and Box?

Court Lorenzini: There are two core reasons. First, humans prefer consistency. If we were constantly forced to use a whole array of different signing methods, it would get confusing, and it would be hard to find your stored documents. Human characteristics were going to drive standardization on one player. It’s also a trust factor. The other main reason it remains dominant is that early on, we recognized that a key element to resolve wasn’t the signature itself but the flow of data between the universe of document creation tools upstream and the universe of document execution tools downstream. Upstream, you have Word, Adobe Acrobat, and special-purpose platforms creating documents with relevant data. Downstream, you have big software companies like Dynamics, SAP, and Salesforce that need that same data to produce, ship, support, and bill for a product. We invested very early in a set of robust APIs that could take data from upstream systems and seamlessly move it to any downstream system. We built years of expertise in data translation via APIs, creating a large constellation of tools that really cannot be replaced by a third party. Most enterprises won’t take the risk of replacing us because a competitor would have to have all the same tools working perfectly on day one. That moat has been a huge differentiated advantage for us.

Nataraj: When you left DocuSign, did you sell your equity or keep it?

Court Lorenzini: I kept it all and moved on to start several more companies. By the time the company went public years later, I still had all my equity.

Nataraj: I spoke with Martin from Insights VC, an early investor in DocuSign, who said he never sold his shares and mentioned a ridiculous multiple. What did your multiple look like?

Court Lorenzini: The shares were founder shares, so they were basically fractions of a penny, and they got to over $300 a share. It was a very healthy return, let’s just say.

Nataraj: After five years, DocuSign was successful, yet you went on to found other companies. Are you an ambitious person?

Court Lorenzini: I think people would describe me that way. I’m certainly an optimist, and I love the thrill of getting something off the ground. When you’re successful and you do it repeatedly, it means you’re in it because you love the game.

Nataraj: What was your career like after DocuSign?

Court Lorenzini: The third one was a renewable energy company. I was trying a business model that didn’t require much venture capital, just a few hundred thousand dollars in angel money. It was intended to be a cash flow business, which it turned out to be, returning cash to my investors. I wouldn’t say it was a giant hit, but it returned capital. Then I started my fourth company, a consumer data acquisition company called Metabright. That one was my most spectacular failure. It was a rocket ship with 50% month-over-month growth on a multi-million dollar run rate. Between that and absolute catastrophic failure took less than three months.

Nataraj: Wow, why did it fail so drastically?

Court Lorenzini: The technology we were building was data extraction from checkout register receipts. We built an OCR-based system that could read and translate that cryptic writing into real product data. We were licensing it to other application providers. Our biggest customer was delivering 90% of our revenue and growing like gangbusters. One day, the founder of their company was at an event and sat next to a young man who had just finished his master’s program in Croatia. He and his buddies had written a program to read receipts using a cell phone and was willing to give his code to my customer for free. Within weeks, my customer tested it and called me up to say, ‘You’re out. He’s in. Bye.’ When your 90% revenue customer walks away with no warning, you don’t survive that. I went to Croatia to try and buy the technology, but couldn’t get a deal done. I called my investors and employees and said we had to shut it down. It was very gut-wrenching.

Nataraj: How do you evaluate opportunities now and decide if they’re worth your time?

Court Lorenzini: I have a methodology I promote to early-stage founders. First, validate your product by testing if someone will pay for it before you even build a prototype. Get them to put down a down payment or something to test the concept. Second, and this is the one most people miss, actively try to kill it. I go back and find founders of companies that preceded me in the same solution space. I ask them what happened to their company and why it failed. Through that exchange, I learn all the fatal, foundational flaws I need to be aware of. It’s an incredibly eye-opening process. If you can diligently uncover and resolve all those fatal flaws with your approach, you’re probably on the right path. I tend to be pretty rigorous about both of those things before I jump into something new.

Nataraj: Let’s talk about Founder Nexus. You’re not raising outside money for this. What is it, and why are you doing it?

Court Lorenzini: Founder Nexus is my thank you note to the venture capital industry. I’m not trying to get myself or anyone else rich, but I’m using it as a vehicle to help founders on what is an otherwise difficult, lonely journey that’s statistically destined to fail. The odds of failure for a venture-scale founder are over 90%. I see these founders as a valuable global resource that isn’t being optimized. So I’ve set out to figure out how to raise the odds of success for them. Founder Nexus is a way for founders with experience to get together regularly and be motivated to help each other by sharing experiences, not advice. I gather these venture-scale founders, put them in subgroups, and create opportunities for them to actively share their experiences to level up their game. Success in building a venture is a series of variables multiplied together. If a single variable is zero, the whole equation fails. If you can get every decision to be made at 50% or above its potential value just by gathering information, that will inevitably raise the odds of success for all participants.

Nataraj: Community is all about curation. How do you ensure the right people are in the room?

Court Lorenzini: Curation is key. I filter out anyone who has never built a company before. They have to be well on their way, having already raised their first venture round or outside capital. I’m looking for valuable lived experiences. I also filter out investors, advisors, and service providers. This way, everyone knows the room is pure; everyone is another venture-scale founder who’s been there and done that. This creates an immediate sense of trust and vulnerability. We also build forums, but unlike others where you extract all the business wisdom in 18-24 months, our forums only last for 40 minutes each. Then, software reassigns everyone to new groups with new topics. You get three of these per event, so you hear from 12 to 20 new voices of lived experience each time. You’re also grossly expanding your network of highly qualified people for recruiting co-founders or C-suite talent.

Nataraj: How’s the traction? Is it limited to Seattle?

Court Lorenzini: We’ve held three events and have about 150 people signed up. We just opened it up to full membership. Our next event will be our first simulcast, with both a live and online component to allow non-Seattle participants. My long-term objective is to have chapters all over the world, stitched together so founders in one community can help founders in another. This way, venture-backed companies can live and excel anywhere.

Nataraj: You’re an LP in a lot of funds. How do you decide which ones to invest in?

Court Lorenzini: I’m very active in the Seattle ecosystem to give back to the community that helped me, but I’m not restricted to it. My wife and I have probably invested in almost 20 venture funds around the world. It’s always hard to decide who will be a good picker. I tend to like very early-stage funds; that’s where my passion is. Sometimes it’s a gut feeling, or seeing if a fund’s thesis gives them a leg up. A number of funds we’ve invested in are run by non-traditional VCs, like women or people of color in different regions. We think those investors know their market better and will probably get outsized returns.

Nataraj: Has any area surprised you in terms of performance?

Court Lorenzini: Geographically, no. But I will tell you that several of the women-run funds are grossly outperforming their peers. Female VCs are historically few and far between, but the ones we’ve invested in are dramatically outperforming the rest of the crew. It’s amazing.

Nataraj: What’s your view on the current valuation landscape, especially with the AI craze?

Court Lorenzini: I invest in early-stage funds, so by definition, these are not high-valuation entry points. If they’re betting on AI, they’re not writing big checks at high valuations; they’re coming in at the concept stage with bigger upside potential. My investing strategy is like a dumbbell. I have a ton of diversified dollars in the low end, and a few very concentrated private equity positions on the high end, right on the cusp of pre-IPO.

Nataraj: Why did you pursue three master’s degrees?

Court Lorenzini: Each of those master’s was opening a door to a new opportunity. I was working for a semiconductor equipment company that had a program to pay for advanced education. For me, each master’s program was a way to get a new promotion. I got three very significant promotions in a short time. Within three years of my undergraduate degree, I was going to Europe to start a new venture for that company. There’s no way I would have gotten that opportunity at 25 if I hadn’t done all that work. I did computer science at Berkeley, manufacturing systems engineering at Stanford, and optical engineering at the University of Wisconsin-Madison. Each one was a gateway to a new career step.

Nataraj: What are you consuming right now that’s influencing your thinking?

Court Lorenzini: I love to read. I recently consumed ‘The Three-Body Problem’ series, which was mind-opening. Also, ‘The Fourth Turning Is Here,’ which contextualizes where we are in history. I’m really fond of a book by John Levy called ‘You’re Invited,’ which was helpful for Founder Nexus. And another called ‘The Power of Pull.’ On a podcast basis, I’m a huge fan of Acquired and ACQ2.

Nataraj: Who are the mentors that helped in your career?

Court Lorenzini: Shout out to my dad first and foremost. My father was one of the eight people that founded Silicon Valley; he invented the process for growing silicon commercially and was on the team that discovered solar power. He started seminal companies. Also, the founder of KLA, Ken Levy; the original CEO of Cisco, John Morgridge; and his successor, John Chambers. They were huge influences.

Nataraj: What do you know now about being a founder that you wish you knew when you were starting out?

Court Lorenzini: I wish I had sought more experiential advice. I got a lot of guidance from people who gave me advice but not experience, and that usually set me in the wrong direction. When I talked to people who had lived the experience I was struggling with, I got better counsel. I also had to learn how to delegate effectively and, crucially, how to follow up to ensure things got done. And finally, learning how to proactively hold people accountable as a leader took a while to understand.

Court Lorenzini’s journey offers a masterclass in resilience, strategic thinking, and the importance of community. His experiences, from the heights of DocuSign’s success to the lessons of failure, provide invaluable wisdom for any entrepreneur.

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With three successful exits and a career spanning the core of Silicon Valley’s technological evolution, Ameesh Divatia offers a rare and valuable perspective on building transformative companies. From his early days in networking silicon and navigating the dot-com boom at Cisco to founding Baffle, a pioneering data protection company, Ameesh has consistently focused on creating new market categories. In this conversation, he shares the critical lessons learned from his entrepreneurial journey, including the importance of a customer-centric view, building strategic relationships with potential acquirers, and adapting to industry-wide shifts. Ameesh provides deep insights into the evolving landscape of data security, the challenges and opportunities presented by GenAI, and the timeless principles of finding the right idea and the right team to bring it to life. This discussion is a masterclass for any founder or tech leader looking to understand the mechanics of long-term success in a fast-changing world.

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Nataraj: We like to feature founders solving interesting problems, and you’re tackling data protection. Before getting into what Baffle does, can you give a little introduction to yourself and your journey so far?

Ameesh Divatia: Absolutely. I have a traditional engineering background. I grew up in India, got my bachelor’s degree there, and came here for graduate school. After grad school, I got into the computer networking industry, which was a very hot space at the time. I was fascinated with how computers could be connected and evolve into a larger IT paradigm. My first job was as an application engineer supporting networking silicon, but I quickly moved into an architectural role because I was always interested in the big picture and understanding how the customer was using the product. That has stayed with me forever. I moved into a system architect role and eventually went to work for 3Com, one of the big three along with Cisco. After about three years there, I decided I wanted to do something on my own. I quit my job, came up with an interesting angle on using data networking concepts for optical networking, and that was my first startup in the late 90s. My second startup was in storage networking, the third was a turnaround in silicon photonics, and now Baffle is in data protection. My journey has taken me through very different spaces because I like to learn new things and go after complex technical challenges. I’ve also been extraordinarily lucky; all three of my previous startups were acquired. In every case, we built a completely new market for the acquirer or the space in general.

Nataraj: Looking at your career, you were at Cisco during one of its most interesting times, the dot-com bubble. At one point, wasn’t Cisco the highest-valued company?

Ameesh Divatia: It absolutely was. It was sort of like the NVIDIA of the dot-com bubble. This whole NVIDIA story is something we have lived through. I don’t want to say it doesn’t end well, but it doesn’t stay like this forever. But it was euphoria. You would get into the office and see the stock up six bucks, and we literally thought we could take over the world. We were newly acquired into Cisco, and two things about Cisco were amazing. First, they always reinvented themselves. John Chambers had an edict that companies have to reinvent themselves every four years. We were acquired and built a completely new business on the optical networking side. Second, when you get acquired at Cisco, you are treated very well. I remember we had a record of 33 EBCs in a quarter. It was insane; every day, the who’s who of the networking and telecom world—AT&T, Verizon, Deutsche Telekom, France Telecom—would be there, and we would be presenting to them. It was a magical time.

Nataraj: Any advice for whoever is inside NVIDIA that you did or didn’t do when you were at Cisco?

Ameesh Divatia: Be humble, that’s it. NVIDIA is a different story; it’s an overnight success that took 30 years. They completely deserve what they have, but it will be disrupted. Every company has to fight to be the incumbent and drive the industry. Some are more successful than others, but nothing lasts forever.

Nataraj: Your company before Baffle was also acquired by Cisco.

Ameesh Divatia: That’s right. One thing I’ve done a lot is get involved with prospective acquirers very early. I always tell entrepreneurs not to rely on someone else to find you the exit. You have to build relationships over time. You have to be open about sharing your value proposition, but not your crown jewels. With Lightwire, it was a very capital-intensive project in silicon photonics. You need a big brother. We went out and shortlisted companies, saying, “Look, we have this amazing technology, but we need somebody to productize it.” We got a few interested, and eventually, Cisco not only got interested but invested $20 million in a $40 million round and started working with us. They needed to pack a terabit of throughput in a router blade, which wasn’t possible with existing technologies. They gave us a spec, and our team did it in less than two years. At that point, Cisco couldn’t let that technology be out there because it was critical for their success, so they decided to buy it. It was the first time they had ever bought a component company.

Nataraj: Is this technology actively used today?

Ameesh Divatia: Absolutely, it’s a billion-dollar business line right now for just this product, and they’ve expanded beyond that.

Nataraj: And you served as a partner at an investment fund, Carta. What was that experience like?

Ameesh Divatia: After that exit, I was done with operating roles and wanted a break. I thought I could take my expertise to help others at a very early stage. My CFO, one of my mentors, and I started Carta as a seed-stage fund to invest in companies. We invested in eight different companies, and six of them have been acquired by now. It was an interesting experience to be on the other side, but I quickly got bored. It’s not like running the place; you’re watching the entrepreneur run it. Then a great idea came along, which is how Baffle really started, and I jumped back in.

Nataraj: You mentioned you’ve always created new categories. How was Baffle a new category at that point?

Ameesh Divatia: We had the vision to create a new category. If you look at security, it started with protecting the pipe—the network—which led to the device wave with firewalls. Today, we are in the identity boom because we don’t own the infrastructure anymore; the data center is in the cloud. We think this is setting it up nicely for the next big thing, which is actually protecting the data itself. Identity can only go so far. If you protect the data at the record level with encryption, there’s no way to look at the data unless you have access to the keys. You’re making the hacker’s job much harder. Security has always been a race. We feel data is the next big frontier. If you protect data at the record level, you don’t care if a hack happens, because whatever is stolen is ciphertext. That’s the category we are creating: data-centric protection. The industry is starting to gravitate towards that, especially with the GenAI explosion, because you have to share your data to get good outcomes. The fundamental problem we solve is that once data moves to the cloud, you don’t want the cloud vendor to see it.

Nataraj: At what abstraction level does Baffle come into the picture, and who’s your typical customer?

Ameesh Divatia: We operate at the application tier. It’s a pure application layer solution with no dependence on any processor, operating system, or programming language. We intercept the packet that goes between the application and the database as a network-level proxy. A typical customer is the one responsible for infrastructure in the cloud. But it starts with compliance regulations. We started in 2015, and GDPR came into effect in 2018. Security sets the rules. Data analysts or prompt engineers want to move data to the cloud, but security says no unless it’s compliant. That’s when the infrastructure provider, responsible for the database, has to adopt Baffle.

Nataraj: There’s criticism that regulations like GDPR benefit big companies and make it harder for startups. What are your thoughts?

Ameesh Divatia: If you ask me, regulation is not going far enough. If regulation was great and everyone was compliant, we wouldn’t have hacks. But regulation should be easy to adopt. With data-centric protection, you’re taking a proactive measure to protect your data and ensure your customers’ data won’t be stolen. That enhances your reputation and builds trust. I don’t think it’s worth fighting regulation; it’s important to embrace it. GDPR has now been taken to a new level with things like CCPA and CPRA, so it’s proliferating.

Nataraj: When GDPR first came out, did things improve, and did the tooling evolve so a small company could also comply?

Ameesh Divatia: Absolutely. One of the big things about GDPR is the right to be forgotten and the bring-your-own-key model. That’s something we have enabled for any SaaS vendor. It used to be very complicated; you had to buy an HSM, know crypto, encrypt your data, and manage keys. We’ve completely abstracted that away from the developer. You just tell us who the tenant is, associate a key with them, and our tool handles the rest. If a tenant wants to trash their data, they just take the key away, and the data becomes invisible.

Nataraj: Talk to me about your initial go-to-market strategy. How did you pitch your early customers?

Ameesh Divatia: An entrepreneurial suggestion is you don’t want a channel on day one. You want to go direct to know what the end customer is doing. The key is to find an early adopter with a pain point that only you can solve. We found a gap in the industry with Postgres databases, which are fast-growing but have no native encryption capabilities. Our first customer tried a DIY strategy and failed miserably. They found us. Digital marketing, SEO, and SEM are absolutely critical for any business these days. People don’t like to be cold-called; when they need something, they search. You have to advertise and write lots of content. We started with a direct strategy, and to scale, we’ve gravitated towards using the cloud vendors themselves as our channel. It’s counterintuitive, but they have a shared responsibility model. We help them implement it, allowing their customers to take control of their data. This helps the cloud vendor migrate more customers and make 100x what they would pay for us.

Nataraj: Security is a cat-and-mouse game. What are the current trends in the security industry?

Ameesh Divatia: The most important trend is the evolution away from just monitoring. Things like SIM logs are being reimagined with GenAI for automated monitoring and alerting. But monitoring is great for identifying problems; what about remediation? Discovery is a big space, but just classifying data doesn’t make the problem go away. Remediation is the big trend. How do you remediate data so it becomes invisible? Encryption, masking, tokenization are techniques that can be used. We allow field-based control to transform data so it’s safe in environments you don’t control.

Nataraj: You brought up GenAI. How are you thinking about it as an entrepreneur who has seen multiple technology cycles?

Ameesh Divatia: This is going to be a multi-year cycle and a massive productivity improvement. We’re seeing it in multiple places. Our engineers use co-pilots all the time, which helps remediate things like CVEs. We use it in our customer success environments as well. A new engineer can troubleshoot a problem without needing to know who the actual customer is. We tokenize the customer name, put the data in a repository, and run GenAI models on it. From a product perspective, it will completely transform data discovery, which has never been a fully solved problem. We expect to integrate it across all our functions—sales, marketing, product blogs, all of it.

Nataraj: If you were starting a new company right now, where would you look for opportunities?

Ameesh Divatia: I have lots of ideas, but implementation and commercial fit are key. I strongly feel we are in a phase where ease of use and adoption are critical. One of the biggest problems with GenAI is that it lies with authority. Figuring out ways to detect that is a massive opportunity. In general, anything in the data realm—getting the right dataset into the hands of the right people—is always going to be a lucrative area.

Nataraj: Are your customers doing data deals with other companies to build GenAI solutions?

Ameesh Divatia: Yes. Data sharing was always selective, but GenAI is changing that. You have to share your data, but it’s hard to do without compromising customer trust. That’s where data-centric security and privacy-enhancing computation will be critical. There’s still a tremendous problem in making it easy to use, and I see a lot of innovation coming where you can share data securely.

Nataraj: This is your fourth company. Do you have a checklist or mental model you follow when evaluating a new idea?

Ameesh Divatia: I wish. All four happened for very different reasons. The most important thing is you have to get excited about an idea. Second, and sometimes more important, is finding the right team to work with. It’s like a movie: you need the right plot and the right team of actors. You want people who are subject matter experts in their areas. After that, there’s a whole slew of commercial things: find the right market and make sure it’s a critical solution, not just a nice-to-have. But those first two are the most important to start.

Nataraj: What do you consume for information? Any books or podcasts?

Ameesh Divatia: LinkedIn is a big source of my information. I also like reading business books, though I often get the gist through something like Blinkist. I like to read about entrepreneurs and innovators, so I’m a big fan of Walter Isaacson. He writes really well when it comes to capturing a person’s history.

Nataraj: Who are the entrepreneurs you most admire?

Ameesh Divatia: I’ll start with the founding fathers of this country. I think they were the ultimate entrepreneurs. They completely wrote the model from scratch, which gives me the most confidence in America’s future. Nearer term, of course, Steve Jobs was an amazing entrepreneur, as is Elon Musk.

Nataraj: Who are your mentors?

Ameesh Divatia: I’ve had a lot of them. It starts with my family—a supportive spouse who gives the right feedback. My father was a big influence. And I’ve had many other mentors in Silicon Valley who helped me along the way and continue to help me today.

Nataraj: What do you know about being a founder now that you wish you knew when you were starting your first company?

Ameesh Divatia: This is a tough one. As an engineer-founder, you tend to fall back on the idea that the technology will sell itself. That is seldom the case. You have to constantly adapt the story based on what the customer perceives. The technology is a cornerstone, but you have to constantly make sure the commercial value is there. If I knew that, I would have looked at the business side of it way earlier in a lot of cases.

Nataraj: Ameesh, thanks for coming on the show. This has been a very fun and insightful conversation.

Ameesh Divatia’s journey offers a masterclass in navigating Silicon Valley’s dynamic landscape. His insights on creating new markets, adapting to technological shifts like GenAI, and the foundational importance of data-centric security provide a valuable roadmap for entrepreneurs and innovators.

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In the evolving landscape of software development, the demand for powerful, scalable applications often outpaces the supply of engineers. This gap has fueled the rise of no-code and low-code platforms, but many come with limitations in scalability and security. Enter Xano, a platform dedicated to providing a robust, enterprise-grade no-code backend. We sat down with Prakash Chandran, co-founder of Xano, to explore his journey from leading design at Google to tackling one of the biggest challenges in modern development. Prakash shares how his experiences, including a self-described “failed startup,” shaped his vision for Xano. He discusses the platform’s unique approach of focusing solely on the backend, empowering citizen developers to build complex, scalable applications without writing a single line of code, and moving beyond the prototyping phase to full-scale production. This conversation offers deep insights into the future of software creation and the power of abstracting complexity.

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Nataraj: On the Startup Project, I like to feature interesting products solving interesting problems. As I explored Xano, I found it’s at the intersection of a couple of very interesting trends in how we develop and scale applications. I thought it would be useful for our audience to discuss what you’re building at Xano. Before we get into that, can you give a little introduction about yourself and your career before starting Xano?

Prakash Chandran: Absolutely. After I graduated from Cal Poly Pomona, I joined a small startup called Picasa. Google ended up buying Picasa, and it became Google Photos. My coworkers called me very lucky because I had no idea; I just joined, and then that happened. I spent the next eight and a half years at Google. I had the privilege of leading the design on Google Calendar for a bit and led the design and research team for Google Enterprise, which became G Suite and Google Workspace. I had an amazing career there, learning a lot and working with brilliant people. After Google, I left for the startup world. After a short break, I did a startup, which I call three and a half years of getting the crap kicked out of myself. Then I went into consulting, as one does after a failed startup, for a couple of years before starting Xano. That’s been the trajectory. At Google, I evolved from a UX person to a product person, and after doing a startup, you become more horizontal across the business.

Nataraj: I have this thesis about software products: cracking the right software product is about finding the right abstraction layer at which people want to work. Exploring Xano, your background makes sense. Someone like you starting Xano makes sense; you need an eye for what level the product should be designed at.

Prakash Chandran: That’s a keen observation. One of the main pains I felt during my startup was my lack of control as a design and product person over the engineering process. You have to pay for an expensive engineer. They’re kind of like a car mechanic. If they tell you something is going to take a month to make and tens of thousands of dollars, you just have to believe them and hope that it works out.

Nataraj: With that, explain what Xano is.

Prakash Chandran: I always knew that was a painful process. Then I learned that 80% of the time and resources in software development are spent on the backend. So, Xano is a scalable no-code backend. For those who don’t know the no-code space, it’s about helping people create software without knowing how to code. No-code has been around for a long time; a tool like Squarespace is considered no-code for website building. It’s gone through a couple of different iterations. We’re part of a new wave of no-code where you can build anything and scale without limits. We 100% focus on the backend—the server, the database, the API layer—and we connect to any front end you want.

Nataraj: What kind of applications does Xano enable people to build?

Prakash Chandran: Xano is really meant to be a visual programming language. It’s Turing complete. Anything you can articulate in a software programming language, you can do in Xano without code. In terms of the types of applications we see built, we see everything from a dog-walking application all the way up to a customer advocacy platform at a big company like Qualtrics. It’s kind of like asking what you can build with JavaScript; the use cases are endless. In the same way, we see our customers building many types of things on Xano.

Nataraj: One of the assumptions people often have when they hear a product is categorized as no-code is that it might be good for experimentation, but not for running production applications. Can you really go from a demo or a hobby project to actually running something that makes money or building a company on top of it? How do you see Xano fitting in?

Prakash Chandran: I always say that no-code and low-code have some baggage associated with them. This is because the no-code vendors and tools of the past have had limitations, generally around scalability, security, reliability, and compliance. The hesitation is that no-code is something you should just prototype and tinker with, not take seriously at scale. But as I mentioned, these next-generation tools are architected fundamentally differently. For example, as a no-code backend, we are architected differently than some of our predecessors that might look like a spreadsheet on steroids, where scalability and compliance are layered in as an afterthought. We were architected from the very beginning to be enterprise-grade, portable, allowing you to move it to your own infrastructure and control the resources yourself. The flexibility in what you can build was also addressed very early on. The concern is definitely valid, but one of the things we hope to do is break that stereotype and show that you can start with no-code tools like Xano and scale without limits.

Nataraj: While exploring Xano, it almost felt like… because I was a backend and frontend engineer, I’ve played around with different backend stacks. One of the problems I see is that building a small application is getting really complicated, even for seasoned developers, because things are so rapidly changing. It’s becoming more complex even to get started. What is your thought process on this? Am I just a bad developer, or is this really happening?

Prakash Chandran: No, not at all. You call out something that’s pretty important. As we’ve introduced new technologies to handle different use cases, especially on the DevOps or site reliability side, it gives the consumer more choices, which leads to confusion. The most important thing when building software as a business is validating it in the market. You want to get it out the door. We believe vendors should be responsible for making good long-term decisions regarding infrastructure and DevOps, so you can focus on the business logic and your relationship with customers. The more quickly you can do that, the better. You’re either going to fail and learn and then iterate, or you’re going to get it right and scale your business on something you can trust. A general rule of thumb we tell everyone is you’re always going to rebuild. No matter what stack you build on, you’re going to rebuild it at some point. So the stack you can use to iterate the quickest is probably the best one. We wanted that to be true to our spirit, but on a trusted infrastructure, so if they did find product-market fit, they could rely on it to scale with them.

Nataraj: Whenever I talk to early-stage founders, what they start with and where they end up is slightly different. Talk to me about the process of finding product-market fit for Xano.

Prakash Chandran: We generally knew that this no-code, low-code space was growing. More people were turning to it despite its limitations because there’s more demand than there are engineers. We saw this limitation on the backend regarding security and scalability. So we made two decisions. One, we decided to 100% focus just on the backend and not do the full stack. This was the non-obvious thing everyone said was probably not a good idea. The second piece is we decided not to abstract away the core principles of a software development language. For example, we chose to call it an API instead of a workflow or a Zap. We chose to call it a webhook. We believe you should teach the next generation of software developers by abstracting away the code but making those concepts more accessible. Those two decisions were non-obvious. Getting product-market fit started with a landing page as we were building, saying, “Hey, this is a no-code backend. If you’re interested, sign up for early access.” Then once you have people using the product, you see how quickly they start relying on it. The next step is, will they pay for it? And over time, you see that word of mouth grow and how sticky it becomes. We got lucky in that we had this non-obvious approach and we thought it was a need in the market.

Nataraj: Because the backend has so many components, was there a specific customer use case that gave you the confidence that you had really found something?

Prakash Chandran: It wasn’t a specific customer or use case, but Xano was actually born out of a development agency. It started as a command-line tool to make backend creation easier without having to grow the team. When you see hundreds of different use cases, you realize most software is the same. They have the same kind of infrastructure setup, the same database. There are the same motions you’re doing over and over. For us, it was less about the specific use case and more about the procedure and those steps you had to go through just to start validating your idea. You could do this on other tools, but you couldn’t rely on it once you started to get usage and scale, or if security was a prerequisite. So that was the approach we took, and we found that being pretty horizontal has worked for us so far.

Nataraj: You mentioned it came out of a studio. Is it from your consulting, or were your co-founders running a studio that gave you that insight?

Prakash Chandran: My co-founders were running the development agency. I had done some consulting work as an individual for that agency. It was in doing some of that joint client work where I had seen the evolution of Xano from the very beginning as a command-line tool to a decade later, having served hundreds of use cases. I told my two co-founders, “If we took this and we productized this, I think we could serve a pretty big need in the market and we might have something special.” That’s how it came about.

Nataraj: We’ve evolved products based on the cloud, right? We had infrastructure as a service, platform as a service, and now probably with AI, intelligence as a service. We are moving higher in that abstraction level. I was thinking at some point someone has to abstract away why everyone has to build a scalable website. You’re sort of an evolution of abstracting away that complexity from a backend perspective.

Prakash Chandran: 100%. We could serve that use case pretty well. A lot of companies in the no-code space are very good at building building blocks, these connectors that connect one service to another. We took the other approach and built the engine and the foundation, this visual development layer on top of an engine that abstracts away the DevOps component—the infrastructure, Kubernetes, Docker, Postgres. You don’t have to worry about those things. So if someone wants to build, which you can do in Xano today, an Amazon.com template with the right database schema, and you want to be in multiple geographic regions, you can start with that business logic layer and the database. And then from the infrastructure side, we’re able to deploy in whatever region you want. It’s really just building the foundation where people agree this is the right layer of abstraction for business logic in the backend, and then they’re able to move it as they grow.

Nataraj: Who is the ideal user today for Xano?

Prakash Chandran: We service primarily the citizen developer. If you haven’t heard of that persona before, it’s a Gartner-defined persona. You can think of them as a product owner type. They’re a systems thinker, they don’t know how to code, but they need to build software leveraging low-code tools. There are also developers on Xano as well, but primarily we serve the citizen developer. Now, there’s a wide spectrum of experience. People more on the citizen side will use tools like Airtable or Google Sheets because it’s very easy to pick up. That serves simple use cases very well. We serve an advanced citizen developer who needs to graduate out of tools like Airtable when their needs require scalability, security, and reliability. That’s who we serve. And we’re constantly working to make ourselves more accessible to the broader citizen developer.

Nataraj: Let’s talk about how you’re doing as a company. I think you raised your Series A. What is your revenue split between enterprise and SMB or citizen developers?

Prakash Chandran: We launched in January of 2021. Since then, we’ve seen some pretty exponential growth, largely due to word of mouth. We’re just a backend, so we’re front-end agnostic. All the different front-end forums, whether it’s a JavaScript forum or a no-code front-end forum, mention us. We have over 70,000 backends that we’ve deployed. In terms of the enterprise versus self-serve split, it’s about 20% enterprise revenue, and the other 80% is self-serve. We’re obviously working right now to develop our muscle in the enterprise go-to-market motion, but for right now, we are mostly known in the small to medium-sized business space. In the enterprise, no-code is still very early in adoption, and we’re trying to prove ourselves there.

Nataraj: How is the competition in the space, specifically at the abstraction layer you are operating at, focused on the backend?

Prakash Chandran: There’s a spectrum between citizen and developer, and then a spectrum from developer to engineer. We service the upper end of the citizen developer into the midway point of becoming an engineer. In that space, there are a number of different tools. When you think about the backend specifically, if I’m going to pick the number one competitor, I think we serve different markets, but we definitely see them, is Supabase. Supabase is basically Postgres in the cloud. They’ve done an amazing job. Great founders, they execute very well. But I think there are tools that believe making a developer’s life easier is the future, and then there are tools like us that believe the next generation of software creators are going to look more like citizen developers. We serve these two markets, but because we serve the upper end, we tend to see each other there.

Nataraj: You mentioned you almost thought of Xano as a design language. That gave me a thought that AI could use this design language to make things happen on Xano. How are you thinking about AI intersecting with Xano?

Prakash Chandran: I mentioned visual development because we use all core foundational software engineering principles—variables, loops, conditionals—things that every programmer knows, and we visualize that. When it comes to AI, AI understands these concepts. AI has been such a beautiful thing because it has opened up so much more opportunity and built awareness around creating software and making it more accessible. People can ask AI to generate simple applications for them. I love AI for that reason. That being said, something else is needed to pick up where AI leaves off. If I say I want to build an Uber-type application and you give the same prompt, we’re probably going to receive two different code sets. Even if we don’t, what I mean in my mind with an Uber application is very different than what you mean. In that case, we’re going to keep re-prompting until it spits out obfuscated code. What’s better is you need to pick up from that scaffolding and take a visual canvas where you can infuse your intention. We believe Xano will be the visual canvas that can pick up where AI leaves off. I think a lot of people make the mistake of saying AI is going to replace coders or replace no-code. I don’t think that’s going to be the case. They’re going to work very well together.

Nataraj: I’m curious, what are some of the techniques you guys use to acquire new customers?

Prakash Chandran: One thing that we’ve done very well is create lots of valuable YouTube content. If you go to our YouTube channel, you will see videos starting from, “How is software made? What is a backend?” all the way to, “How do you merge two JSON arrays?” It is very important to continually put out content because this is how people consume it these days. It’s probably our largest source of high-quality traffic. The beautiful thing about content is it just keeps giving; some of it is just evergreen. We also started running office hours, which was pretty unique at the time. Every user, even a non-paid user, has the opportunity every week to come and meet with the team and get their questions answered. If they ask something unique that can help other people, we clip that and put it on YouTube. The final thing is having a community tool that can be indexed on the questions that are answered and searched for. The chances are the problems your customers are having today is a problem a customer is going to have three months from now. It’s a mistake to have a community on Discord or Slack because all of that knowledge evaporates.

Nataraj: I’ve seen this in other tools which became ecosystems, where you have marketplaces of people who can develop things. Are you seeing a marketplace evolving in Xano?

Prakash Chandran: Absolutely. We already have a marketplace of developers, agencies, and coaches. We’re currently working on a marketplace where people will be able to release and soon be able to sell capability, all using the Xano platform. The ecosystem and this partner marketplace are extraordinarily important. We’re even working on a certification process because our agency partners need to separate themselves from everyone else that says they build on Xano. So we have certification programs that we’re actively working on as well.

Nataraj: It looks like you should almost rebrand yourself to calling as a ‘backend cloud’ instead of a no-code backend. We’re almost at the end of our conversation. What are you consuming right now that’s influencing your thinking?

Prakash Chandran: I listen to a lot of podcasts. I subscribe to podcasts like the All-In podcast, Revenue Builders, The Logan Bartlett Show, and Invest Like the Best with Patrick O’Shaughnessy. I learn something every single week. Some people will work out to music; I’m working out to podcasts. I’m listening on my commute. I’m one of those types that listen at 2x and skip around because I’m at the point where I kind of know the nuggets of wisdom I’m looking for. I’m just so grateful for the community of podcasters that have amazing guests I can learn from about management style, growing a business, or customer acquisition.

Nataraj: Who are your mentors that have helped your career?

Prakash Chandran: There are moments of wisdom you pull from all of these podcasts and individuals that influence you. Two people I’ve never met but who have really influenced my way of thinking are Chamath Palihapitiya, who has a wonderful framework of intellectual honesty and seeking the truth, and Dev Ittycheria from MongoDB, for his philosophy around management. In terms of in-person people, I used to work with Adrian Graham and Carl Showalter. They were at Google with me, sold their company to Facebook, and then created Seesaw. Working with them directly, they’re just brilliant individuals. They work really hard and always have this healthy dose of skeptical optimism that has taught me to build in a very measured way, where you have your head in the clouds but your feet on the ground.

Nataraj: One final question, what do you know about being a founder that you wish you knew before starting Xano?

Prakash Chandran: I’m very happy with all of the mistakes that I’ve made. Obviously, it’s shaped where we are today. But if there was one thing, it’s that the things that matter take time. I think when we’re younger, we’re always in a hurry. We think there might be a silver bullet shortcut and we’re always looking for it. But when you’re trying to do something impactful that will have a long-lasting impact, there’s no shortcut. It just takes day-in, day-out work, trying, and learning. It’s important to align yourself with your zone of excellence and what gets you excited because it’s going to be a very long journey. In this case, Xano is it for me. I really feel like I’m doing what I’m meant to do. But when I was younger, especially before my first startup, I didn’t really have that mindset.

Nataraj: That’s a good note to stop the conversation. Again, thanks for coming on the show, Prakash. Really looking forward to what Xano will do in the future.

Prakash Chandran: I really appreciate it. Thank you so much for having me.

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Conclusion

Prakash’s journey with Xano highlights a critical shift in software development towards more accessible, yet powerful, tools. By focusing on an enterprise-grade, scalable backend, Xano empowers a new generation of builders to bring their ideas to life without being limited by traditional coding barriers.

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The world is more connected than ever, but with increased connectivity comes increased risk. From life-saving medical equipment in hospitals to the traffic signals managing our city streets, the Internet of Things (IoT) has become the backbone of modern infrastructure. Yet, these devices are often the most vulnerable entry points for cyberattacks. In this episode, we sit down with Shankar Somasundaram, the founder of Asimily, to discuss how his company is tackling this monumental challenge. Shankar draws from his extensive experience at Symantec and his deep engineering background to explain the unique security threats facing healthcare, smart cities, and manufacturing. He breaks down the complexity of securing these heterogeneous environments, the evolution of customer needs from simple visibility to sophisticated vulnerability management, and his journey as a founder in a highly regulated and mission-critical industry. This conversation offers a crucial look into the future of IoT security.

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Nataraj: On the podcast, we feature interesting companies solving big problems in different sectors. You’re in two intersecting sectors: security and the Internet of Things. It would be a useful session for our audience to talk about the problems you’re solving. To level-set for the audience, can you give an introduction to yourself and your career until now?

Shankar Somasundaram: Thanks, Nataraj, for having me. I’m Shankar. I started Asimily a few years ago. Asimily is focused on helping provide visibility and security for medical, IoT, and OT devices. We work across verticals like healthcare, smart cities, universities, and manufacturing. Healthcare is our prime vertical where we started the company and have since expanded. Prior to Asimily, I ran the IoT business at Symantec for a few years, which is where I got exposed to IoT. Before I even started the business, I did a full strategy project for Symantec on how they should expand into the IoT vertical. My journey in IoT has been going on for 13 or 14 years now. It started as a strategy project, which led to a few other things, and then Symantec started a business and asked me to run that group. Eventually, I reached a point where I wanted to start Asimily. Before that, I had a product and engineering background. I built the iPhone 3G modem many years ago and some of the early chipsets and algorithms at Qualcomm. I’ve mostly been on the product and engineering side. I like the space I am in because there’s a lot of innovation possible, which aligns well with everything I have done so far.

Nataraj: Going back a little, what was the idea when you were first thinking about starting Asimily? What was the forcing factor and the big problem you were trying to solve?

Shankar Somasundaram: When I was at Symantec, I saw the opportunity in healthcare. The initial idea was focused there, and we did a lot of work for many years. The big problem then was that healthcare is a very complex, heterogeneous environment. I call it a system of systems because it’s not just what’s happening inside the organization; it’s the suppliers and vendors. It is the one environment that singularly contains all kinds of devices: medical, IoT, and OT. I don’t think any other environment has everything. In that kind of environment, how do you provide visibility, vulnerability management, detection, and all kinds of operational metrics? And you have to do it in an environment that is very constrained, fairly regulated, and where there are severe patient impacts if you get it wrong. It is the most challenging environment I know among all verticals. I saw a couple of players in the space taking a very IT-centric approach, but there had to be a completely different, bottoms-up approach to solve for these unique devices. I said, we’ll go solve this problem in healthcare, and we can do it better than anybody else. That’s how the company began. Symantec wasn’t as interested then in going after this problem, and I decided if they weren’t going to do it, I would.

Nataraj: How does Asimily help its customers today? It’s a primarily security-based product, but healthcare is such an interesting space in terms of software. How do you connect the hardware monitoring to the existing software used in healthcare?

Shankar Somasundaram: Our system’s principle is the same whether it’s healthcare, smart cities, universities, or manufacturing. In healthcare, we’ve done a ton of work. We put a hardware appliance inside the environment that connects to the network and collects and extracts device-related data. Because of HIPAA, GDPR, and other regulations, you cannot transmit patient information outside. So, we transmit only device-related information to our cloud, or we have an on-premise version. There, the data gets processed for more than just cybersecurity; we provide visibility, operational metrics, and we are adding new capabilities that go beyond cybersecurity. The data we collect then integrates with other systems. We have APIs with configuration management systems, CMDBs, asset management systems, vulnerability scanners, SIEMs, NACs, firewalls—you name it. Our system does a ton of work by itself, but we interoperate with other systems, creating an integrated view for the health system, city, or manufacturing plant. We provide a high level of data granularity, deep visibility, and robust capability around vulnerability management and incident response, which improves their overall posture and enriches other systems that lack the context of these devices.

Nataraj: You mentioned Asimily has a hardware product that collects data from other devices. How are you interacting with those devices? Is it through the firmware on the other hardware?

Shankar Somasundaram: To be clear, we are a software company. The hardware we use is just a commodity; we can also put our collector as a virtual machine in their environment. We are collecting purely network data. We have other non-network mechanisms, like collecting manufacturer documents, but the primary method is passive, where data is fed from the network into our box. We don’t have to interact with the hardware directly because we’re not interrogating these devices. For medical devices, it’s very risky to interrogate them. For certain kinds of IoT and OT devices, you can, but mostly you are getting data from these devices on the network. Based on that data, you act on them without directly interacting with the hardware’s firmware.

Nataraj: Healthcare is notorious for security attacks and being prone to hacking. We often hear about healthcare organizations being hacked and held for ransom. Do you see that as a common pattern you’re helping to solve? What types of issues are you solving for customers?

Shankar Somasundaram: Cybersecurity is a multifaceted problem with no single silver bullet. Our focus is on the IOMT, IoT, and OT devices in the environment. Ransomware attacks have become more common because health data is so much more valuable than credit card data—I think 100 or 1000 times more. So, this is here to stay. Securing all these other devices is one big step toward protecting against ransomware attacks. We are a big piece of the puzzle. A hospital might have a firewall for IT systems, DLP, and an email gateway, but what about the medical and IoT devices? There are two problems: what if they’re connecting externally, and how do I protect them against internal threats? You have to assume some threats will bypass your perimeter. When they get inside, you need to know what your devices are and where attacks can come from. We do a ton of work around attack analysis, identifying how vulnerabilities on these devices could be exploited and what lateral movement could happen. We also help collect data for forensic analysis. This in turn helps protect against ransomware because medical IoT devices are the core bread and butter of a hospital’s operation. Protecting the core of the system is what we are doing.

Nataraj: You brought up smart cities. We’ve heard this phrase and passed the hype cycle. From your observation, what does it mean to be a smart city today, and where does Asimily fit in?

Shankar Somasundaram: I’ll rephrase ‘smart cities’ because that term has been used so many times. I think the concept is simpler: more devices are getting connected. For example, wastewater plants, which come under the city’s purview, are fairly connected. What if your wastewater plant gets attacked or goes down? Imagine your sewage isn’t flowing anymore. That would be a nightmare. All the traffic signals in a city are connected to a central controller. What if some of them fail or get attacked? The concept of a smart city I’m talking about isn’t the futuristic one touted for 20 years. It’s simpler: all these devices, whether traffic lights, sensors, or wastewater plants, are connected. How do you understand what’s in that environment and protect it? The problems are similar: protection, visibility, and operational metrics. I think the difference between then and now is there’s a lot more focus on critical infrastructure, partly because connectivity has risen. When you reach a certain threshold, like 30-40% connectivity, it becomes important. The present reality is that devices are connected, and with that comes the need for visibility and cybersecurity management. That’s what we have solved.

Nataraj: You mentioned catering to clients in healthcare and smart cities, both of which are highly regulated. You mentioned HIPAA, which I know from a past job can be complicated. What was the experience like dealing with two highly regulated sectors?

Shankar Somasundaram: The good news is that we touch device data, not patient data. Regulations focus on patient data, PII in smart cities, or confidential information in manufacturing. We aren’t touching that, so it’s simpler. The architecture we built, where we only send certain kinds of device data to the cloud, helps. For very critical environments where customers won’t allow anything to be transmitted to the cloud, we also have an on-premise version. Because of these architectural capabilities and our focus, regulations don’t directly impact us. However, because these are more regulated environments, there is far more scrutiny on the technology and the product. You have to have an enterprise-grade product, which is something we have built. There are certain levels of quality and assurance you have to provide in these verticals, which we have been able to do.

Nataraj: You mentioned you got started with Asimily because you were writing the strategy paper. When you decided to start this yourself, what were those initial days like? How did you bring together the founding team?

Shankar Somasundaram: It was pretty challenging. When you leave a large company where you’re running a business and then suddenly you’re all by yourself, it’s tough. Initially, I was lucky to have built some core advisors and relationships. One of the ex-CEOs of Symantec, Mike Brown, is an advisor and investor. I call him our first co-founder. He was one of the first people I spoke to about it, said it was a good idea, and even gave me a check. One of our investors, Ashmeet from Engineering Capital, wrote our first check. He took a bet on me when I had nothing but some slides. I would almost call Mike Brown and Ashmeet our co-founders. I got the backing of people who believed in me through previous relationships. Then I was able to reach out into my network. I brought in Hitesh, whom I had studied with at Rutgers, and he’s still with us. Then we brought in some other people and expanded the network from there. We’ve since built a very strong leadership team, mostly from Symantec and other areas. It’s a struggle initially, but I was fortunate.

Nataraj: How did you get your first customer? When you work in big companies, there’s a whole sales system working for you. As a product builder, your job ends at supplying information to marketing and sales.

Shankar Somasundaram: Because I had been in the industry and doing IoT, I knew a few people. I was able to reach out to some partners and people in the industry to get feedback. When I got feedback, some people said it was a good idea and to come back when I had a product. It took us a little time to get there, but once we had something, I could go back and show them. It wasn’t easy at the beginning because healthcare has a very high bar; they don’t buy half-baked products. They want a more sophisticated product even in the first round. It took us a couple of iterations, but the product had and still has some very core differentiators. That allowed us to get some initial customers. Then we were able to improve the quality to an enterprise-grade level. Through the contacts I had built, the quality we had built, and the differentiators we created, we were able to land our initial customers.

Nataraj: How does the sales process look today compared to then? What is your process for reaching customers?

Shankar Somasundaram: The very first sale was just me. But now, we have a full-fledged sales team, a channel team, a marketing team, and solution engineers. We also have partners. It’s a very different motion now. Our partners refer us, and being the number one rated Gartner vendor helps, so people sometimes reach out. We are constantly getting customer feedback, and we have some very strong, loyal customers who refer us. Our sales process is now largely channel-first. A lot of our business comes through our channel, and we want to encourage that. At least in healthcare, a lot of people know us. In non-healthcare, we have a channel ecosystem in place. So, between our sales channel, our existing relationships, and the credibility we’ve built, that’s what’s driving many of the leads. It’s a more formal, defined sales momentum, whereas the very first sale was completely ad hoc.

Nataraj: When you’re talking to prospective clients, who are the decision-makers, either in healthcare or smart cities? For example, with cloud products, it could be a top-down decision from a CIO or a bottom-up decision from developers.

Shankar Somasundaram: It does depend, but I would say 80% of the time it’s the CISO, the Chief Information Security Officer, or someone in that area like the CIO who takes care of IT and cybersecurity. Beyond that, there is some dependency on the vertical. In healthcare, it could be the Chief Clinical Officer or Biomed. In smart cities, it could be someone who manages operations. In manufacturing, it could also be someone who manages operations. There is some nuance to every vertical, but the common thread across all of them is the CISO.

Nataraj: I think of Asimily as a security company, but security is such a broad term. Can you give an idea of the layers in this industry, who’s capturing what value, and where you position Asimily?

Shankar Somasundaram: We are focused on device-related security—IOMT, IoT, OT. Security has different layers like data security, network security, and email security. We are focused on the non-IT side. In the non-IT world, there is a different kind of value chain. There are part suppliers, full device suppliers (like someone who provides a traffic light or an ultrasound), and system integrators who put the entire network together. There are also people who manage and maintain these devices, which can run for 10 to 15 years. Then there’s an IT infrastructure, networking, and cybersecurity overlay. We come in after these systems have been connected. We fall into that IT, networking, cybersecurity, and even maintenance layer, because we provide some metrics that help with maintenance. A lot of what is done in these industries is manual. Our value proposition is to automate much of that and bring them to a similar state of capability as the IT side. That’s where Asimily fits in the value picture.

Nataraj: You mentioned being number one in Gartner. How do you think about competition and differentiate Asimily from other companies doing similar things?

Shankar Somasundaram: There are players in this space, but I feel there’s a lot more innovation to be done. We are launching two completely new modules now that are the first of their kind in the industry. I feel the industry is at 50-60% of where it needs to be. What eventually needs to happen is a much broader, wider set of capabilities. When I started Asimily, all people wanted was visibility. That’s still a big problem, but now people are asking for more. They’re asking for more and more with every passing year. They want to manage all their devices with similar parity to IT devices. So one level of differentiation is innovation. I think in a space like this, similar to AI, the winners will be decided over a 10-12 year timeframe as innovations play out and customers pick more capable, mature, and holistic platforms. The other place we differentiate is depth. Whether it’s inventory, vulnerability management, or incident response, we have some core differentiators. For example, everything is vulnerable, but which vulnerabilities can be taken advantage of by an attacker for that device in that specific environment? How do you mitigate it if there’s no patch? We have unique approaches to mitigation and remediation. So, depth of capabilities and continuous innovation are what will determine the winner.

Nataraj: Security and the IoT space are huge. If you were to look at some white spaces for a new founder interested in security, is there any area you would suggest they look into?

Shankar Somasundaram: It’s hard for me to say because I’m so focused on this. If there was a white space, I’d go to RSA and there would already be 10 companies attacking it. You could have said GenAI is a white space, but what if GenAI starts to misbehave? Now I see five companies doing GenAI security and compliance. This question is probably better suited for a VC who is looking at all spaces. But I do think a lot of things are happening in AI that open up a ton of opportunity in security. GenAI security is just one aspect. There’s an entire suite around data loss prevention and sandboxing around it. I think that will open up a ton of opportunities, and the companies I’ve seen are still scratching the surface. Then there will be something new that comes next year and that will open up another Pandora’s box.

Nataraj: Speaking of GenAI, are you using it in any way to improve your own startup’s productivity, not just as a business offering?

Shankar Somasundaram: Yes, we are using GenAI. We have some partnerships with some of the larger companies releasing GenAI tools. We are using it for our own internal productivity. We actually adopted a form of AI long ago for some of our research, building our own NLP algorithm to improve our research abilities. We have used GenAI more recently to improve our productivity, DevOps processes, and internal research. Beyond that, we have always been using AI in the product, even though we haven’t created a buzz around it. As GenAI comes in, it’s just an evolution for us. We’re introducing it into our engineering productivity and also have some uses in our product.

Nataraj: Are there any specific products or companies you’re using that you can mention?

Shankar Somasundaram: Right now, we are partnering with the big companies. We have a deep partnership with Google and we’re doing some work with Microsoft. We’re using those kinds of tools internally for our own productivity purposes. We never feed them any customer data; that’s a strict no. We use it for our own productivity, and as GenAI has evolved, we are continuing to evolve our own algorithms because there’s more scope to do so. But partnership-wise, we are leveraging some of the bigger, more established AI models to improve our productivity and go faster.

Nataraj: And is the productivity gain meaningful? I’m asking because there’s so much hype in the news.

Shankar Somasundaram: That’s a good question. If you ask me this in three to six months, I’ll have a more concrete answer. You’re right, there’s a lot of hype. We’ve asked ourselves internally if paying for these tools is really improving our productivity. Is it a 5% gain for all the work we are doing, or is it truly making us significantly better? We decided to try it out. We’ve been running this and we’ll see over the next two or three quarters and get an answer on how much better and faster we can move. I don’t have a real quantifiable answer right now, but it looks promising. We have to see whether it works for us or not.

Nataraj: We’re almost at the end. I have a couple of quick questions I ask all my guests. First, what are you consuming these days? What are you reading or listening to?

Shankar Somasundaram: I listen to some general podcasts like Masters of Scale and sometimes read Andreessen Horowitz’s content. As the company is growing, I’m trying to understand how to scale by talking to people in the industry who have grown bigger companies. My focus is on how the company scales—what happens when it grows bigger and larger. We’re operating internationally and growing every year. So I’m looking at that, and there are some podcasts and go-to-market books on that topic. But a lot of my thinking also comes from talking to mentors and people. That’s how I learn fastest—not necessarily reading or listening, but talking to people in the industry. I’m also part of some CEO forums, and our investors introduce us to other people.

Nataraj: Who are your mentors that have shaped your career?

Shankar Somasundaram: There are too many to name over my entire career. But specifically for Asimily, like I said, the company doesn’t exist without Mike Brown and Ashmeet Siddharth. Thanks to them. But over my career, many other people have gotten me here. I wouldn’t be a quarter of where we are without these mentors, and also the people you work with—your team members.

Nataraj: One last question: what do you know now about starting a company that you wish you knew when you started Asimily?

Shankar Somasundaram: That it’s going to be harder and take longer than you anticipated. You truly realize what that means when you run a company.

Nataraj: That’s pretty much what every founder says. This was a really fun chat, Shankar. Thanks for coming on the show and sharing your story.

Shankar Somasundaram: Thank you, Nataraj, for having me. Thank you so much.

This conversation with Shankar reveals that securing our connected world isn’t just about technology but about a deep, contextual understanding of each unique environment. As industries from healthcare to smart cities continue to evolve, holistic security platforms like Asimily will be essential in protecting the critical infrastructure we all rely on.

→ If you enjoyed this conversation with Shankar Somasundaram, listen to the full episode here on Spotify or Apple.

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