How Hard Can It Be? Lessons from Jensen Huang

Navin Chaddha and Jensen Huang outside TiEcon 2024
A humble and inspiring leader, Jensen Huang, CEO of NVIDIA

How Hard Can It Be (to lead a company for 31 years, pioneer new waves every decade, and still be a humble leader and friend of founders)

Watch the full keynote video.

How hard can it be is the question Jensen Huang said he asks himself when faced with any new opportunity and that was my key learning from the fireside chat with him yesterday at TIECON 2024, hosted by Anita Manwani and the TiE team. We presented him with a Lifetime Achievement Award and he joked that he is still very much in the thick of life. When I asked him what advice he would give to his younger self, he said that he would not share all that he has learned, as ignorance can be a superpower. My final question on what still drives him – his answer being that he doesn’t have anything else to do besides serve as CEO of NVIDIA – illustrates the classic Jensen style of being both self-deprecating and inspirational. Along the way, we chatted about founder considerations, how to build and scale companies, and our view on the evolving world of AI.

Navin Chaddha and Jensen Huang at TiEcon 2024
Fireside chat at TiEcon 2024

Here are some key takeaways:

  • First Principles Thinking: With a set of core beliefs, Jensen says you need to test assumptions and if facts change, then your mind needs to change as well.  This informed their thinking on one of their toughest decisions – to swap out an architecture that was based on a palette of technology choices that was wrong. While this was at a time when the company was young and fragile, by keeping in mind that the purpose of the company superseded a single choice, NVIDIA navigated through the transition and has never looked back.
  • Moats & Perspective: We advise entrepreneurs to build deep moats, which Jensen thinks of as having a different perspective. While there were several vendors who were building graphic processors, NVIDIA was the only one that was thinking about applications and building a full stack accelerated computing platform. By combining this with the nurturing of a rich developer ecosystem, which has expanded into their Inception program for startups today, NVIDIA is guided by a model where it succeeds only if others succeed.
  • Leadership & Culture: Jensen is a rare CEO who has 60 direct reports. He pointed out how prior models of leadership were drawn from the battlefield, where only the general makes strategic decisions, while the foot soldiers fight on the ground. He believes that information flow has to be high in companies, and is proud of the world class experts who report to him, along with one person whom he just congratulated on their 30th anniversary!
  • On AI: Jensen sees AI as the 4th Industrial Revolution, following the steam engine, electrons/AC power, and software. He discussed how AI factories can produce intelligence at scale, which resonated with me as we are seeing how AI is being delivered and consumed using Cognition-as-a-Service (CaaS) as the model.  His view on AI sovereignty is unique. He sees that a nation’s wealth extends beyond the natural resources buried beneath the ground with data as a national treasure. He believes that every country possesses the right to harness and capitalize on the potential of its own data to drive economic growth and societal advancements.
Navin Chaddha and Jensen Huang shake hands on the TiEcon 2024 stage
Recognizing his contribution with a Lifetime Achievement Award

I share Jensen’s excitement about continuing to work with amazing people to do amazing things.  He is celebrating his 31st year as CEO, Mayfield is entering our 55th year as a venture capital firm – here’s to having fun and creating the future together!

Fund/Build/Scale: Communicating Your Vision (Transcript)

Here is the transcript (edited for space and clarity) of the conversation between Fund/Build/Scale podcast host Walter Thompson; May Habib, CEO of Writer, and Gaurav Misra, CEO of Captions, on how they transformed their visions into something tangible enough for others to believe in.

May Habib  00:02

There has definitely been a broadening of our vision as a result of really taking a platform capabilities approach and really democratizing access to how we ourselves build, you know, essentially generative AI and NLP apps.

Gaurav Misra  00:21

A lot of it was us convincing ourselves that that was the right vision at first. But then once we were convinced, and we saw the data, and we really liked what we saw, then convincing investors, I think at the end of the day, it turned out to be way easier to convince the investors. The hard part was to convince yourself

Walter Thompson  00:42

That was May Habib, CEO of Writer, and Gaurav Misra, CEO of Captions. Writer is a full-stack generative AI platform for enterprise clients, and Captions offers digital creators a suite of AI-powered creative tools. These are radically new products and services, but before May and Gaurav could build their teams, establish trust with investors or land their first customers, they first had to transform the personal visions into something sturdy and tangible enough for others to believe in and attach to. I interviewed them individually to learn more about how they formulated their initial design and marketing strategies, and the frameworks they developed over time to keep refining their value propositions. We also talked about personal brand building, and the challenges that come with being a company’s chief storyteller. I’m Walter Thompson. This is Fund/Build/Scale.

Walter Thompson  01:33

I’m talking today with May Habib, who is CEO and co-founder of Writer. May, thanks very much for joining me today.

May Habib  02:00

Hi, Walter, thank you so much for having me.

Walter Thompson  02:03

Can you talk a little bit about the idea behind Writer. What initially sparked the notion for this company?

May Habib  02:10

Yeah, my co-founder and I were running a machine translation company. And we were doing localization mostly for technology companies, you know, trying to get their software, working in other languages as they expanded internationally. And, you know, the ideas that became Writer, I usually talk about us, you know, we discovered transformers and encoder decoders, and you know, that’s a really technological way I come at it. But the problem that was very interesting, as we delved into translation that was really exciting as well, there was this problem that we kept seeing over and over and over in source language quality. So the English that you were now trying to take in a Japanese, well, pretty disjointed across the entire user journey and kind of sounds different when marketing is writing about value props and brand, etc. And then pretty different when customer support is writing about the same things on a knowledge graph, knowledge base. And so for us the original kind of founding ideas of Writer were an AI writing assistant, that we would build transformers first. And so in terms of all the other rules-based AI writing assistants, this was going to be just a much more interesting product. And the initial wedge into an organization was content, quality and consistency. And so the first kind of slide deck for Writer after our market research etc., was, you know, an AI writing assistant that did AI writing over time, with this wedge into an organization of a brand and of kind of editorial consistency. And it’s super exploded since in the last four years, the product’s depth and breadth, this has widened a lot. And we call ourselves a full-stack generative AI platform. You can build apps on Writer as diverse as legal review to customer agent support. But those were some of the founding ideas.

Walter Thompson  04:28

This is four years ago, you’re talking about. So at that point, you know, things were very different as far as the AI landscape, the people you’re trying to bring on board. I’m guessing they were fairly knowledgeable about AI and machine learning. You had a deep bench of talent, or were these people who are coming in cold?

May Habib  04:42

Super-deep bench. I mean, these are folks who are building machine translation models right from scratch. So  the encoder/decoder together combo was not something we’ve been doing for a couple years. That team in 2020, We did not add that many people in 2020, we added a head of linguistics, you know, who led NLP engineering and now heads up our customer engineers, everybody from those early months, has just had such a steep learning curve at the company, it’s been so, so beautiful and just such an honor to watch. But 2020, we didn’t add that many team members, we added our founding marketer, Christian at the end of that year, he’s still doing incredible things. We’ve, we’ve really only lost one person since those early days, actually. So the team is pretty, pretty together from early days, and folks have got a lot of a broadened scope and responsibility since then.

Walter Thompson  05:52

So those early employees, they were technically proficient, they didn’t require a lot of education to understand the value you were offering or plan to offer customers. But am I right? And suspecting it is a little different as far as investors — did investors grasp this automatically? How much investor education did you have to do to communicate your vision to investors?

May Habib  06:11

Yeah, in 2020, I do remember spending a lot of time on the AI behind the AI. You know, it’s like, “oh, you use AI. Okay, great. Yeah. Tell me about go-to-market again, you know, like, what about Grammarly?” Right. And so it wasn’t like it is now where you folks are really smart on so much of everything from training costs to inference to you know, ongoing kind of differentiation and modes, right, like kind of within, within the LLM space. It was all very nascent. In 2020, when you’re running, you know, raising our seed for sure.

Walter Thompson  06:51

A lot of the founders I’ve spoken to so far, they all continued to refine their value prop over time as they iterated their way into the market. Was that your experience as well? And how much did your initial vision change over time?

May Habib  07:03

Oh, it’s changed. It’s changed a lot. I think we’ve been pretty consistent since the A since it’s, since we kind of said, look, the transition of the first vision of Writer is the last unstructured business process. Writer’s about great writing for everyone, to now really being a full-stack generative AI platform where our vision is to transform work, there has definitely been a broadening of our vision as a result of really taking a platform capabilities approach and really democratizing access to how we ourselves build, you know, essentially generative AI and NLP apps. There’s so many applications, and we said, you know, we’re not going to be able to think of them all. So better, we expose some of these building blocks. And then the solutions are at 90% of the way there kind of buy vertical. And customers get to customize them a ton.

Walter Thompson  08:05

It sounds like you’re saying this wasn’t a hard sell, when you’re going out and you’re fundraising, investors got this and  you didn’t have to do a long roadshow of a lot of heartbreak. A lot of people were open to this idea. 

May Habib  08:17

Yeah, the A was quick, the B was even quicker.

Walter Thompson  08:20

So, how quickly did you recognize the investors who shared or supported your vision? And can you share an example of when you realized you’ve made one of those connections? Hmm,

May Habib  08:30

That’s a great question. With Insight [Partners] they had done — this is Devin and Ryan, hi, folks, if you’re listening — they had done Turnitin together and Turnitin had been a competitor to Grammarly. And, you know, they sold it for billions. And it had done well. But, you know, they’re sitting on the board and really felt like there was just a lot more in this market in the AI writing space. And so, when I met them, just very quickly, within the first five minutes, they were asking questions about technology that nobody else was asking. And they really understood why our product and our approach and our hook into the enterprise customer was so different than what they had seen before. And so they were really intrigued, because it was just, you know, they just had so much context. And so they really stood out. And it was very clear, they were going to be the best partner for the business. And then with Iconiq, they had been so good since the EA, have really just been in a very humble way, right? Helping get educated on the business. And sometimes like, investors will see you raise a round and then someone sort of I’m going to put air quotes around this, you know, build a relationship for the next round and it’s like, do you Yeah, I know you’re f***ing getting information for your CRM, I hear you typing. Right. And  that wasn’t them at all. And I did not make that mistake with the second company. I don’t do those meetings. But they came to the office, they introduced us to potential customers, potential hires, those were all just really awesome. And then\ in our first meeting, they walked us through their thesis and why they were excited about Writer and you know, folks they had talked to, it was just already like, it felt like they had been part of the company for a few months. It was, you know, that it just stood out. In that group of folks that we talked to, for the B, it was head and shoulders above everybody else, honestly. When

Walter Thompson  10:45

Basically it sounds like, looking back, what was the hardest part of communicating your vision to others early on? And, a follow up, when did it become easier, and how did you turn that corner? Who helped you? 

May Habib  10:59

In the B —  I think there was, and it’s funny that this was just the summer, holy s**t, right? It was six months ago, seven months ago. It’s amazing how fast the market is moving in general today, I would say, when we started talking to investors, like mid- or late July, for the B the, the questions were about Microsoft and hyperscaler competition. “And wait, why do you also have an application layer? Like, what’s that about? Are you infrastructure, are you app layer?” And I think the most sophisticated folks have gotten wise pretty quickly, especially if they’re close to enterprise customers, really understanding how it wants to buy this now. And the AI infrastructure, go to market, and the weaknesses of that revenue being enduring and growing with so much competition, I think the benefit of the full-stack approach, I think, is really becoming pretty obvious for people who are spending time with with enterprise customers like a lot of the best, you know, enterprise software investors are. I would think that the next round, that’ll look pretty different. It already feels different from the kind of inbound that we get. But that was a lot of the kind of competitive conversation at the B was around hyperscalers. And the ongoing defensible moat.

Walter Thompson  12:44

I think there’s always a strong expectation that somebody on the founding team has, if not strong storytelling skills to some storytelling skills at all. Do you think of yourself as a natural storyteller? And how have you become more comfortable doing it? If you’re not? If you don’t see yourself?

May Habib  13:00

You know, Walter, no one’s asked me that question. I don’t see myself as a storyteller, I see myself as decent at picking up signal from noise. And explaining that to people, I see people who really have great storytelling abilities, and I know, I don’t have that. I gotta have something to explain for you to remember what I said. Whereas, I think folks who are really good at storytelling make you feel a certain way. I know, I don’t have that. I probably should find time to practice it, I’m the CEO of a company. And so I should have that. But given how dynamic this space is, and how new it is that it’s rare that something is competitive, and dynamic, and new, all at once, it’s been very helpful to have the ability to explain things. And we frequently get the feedback from both technical and non-technical people. It’s not just me, it’s the top 20 people at the company, “I listened when you talk, like, I know what you’re saying, when you speak to me about this stuff. And I don’t see that or hear that when your competitors come to talk to me.” And that is really gratifying. And I do think it comes from our founding team’s ability to try to just get to the root of something. And just that really being kind of all there is, not really a lot of artifice around it.

Walter Thompson  14:33

Again, looking back this and this is again, the conversation mostly kind of focuses on the early days of kind of struggling to translate vision into reality. Did you have any writing or design experience before this as far as helping you present this to an audience? Which tools or platforms did you use if you didn’t have a skill set for design, for example?

May Habib  14:49

You know, what’s funny in our Series A so many folks were like, “whoa, that was a killer presentation. How did you do that?” And Um, it was the presentation, I actually put together myself. But the visuals our brilliant brand designer had done in Figma. And it was both you know, Pete Hodge, a brilliant creative director and videographer Andy Orsow was amazing, he’s at Frame now, we worked with him on contract while he was between Invision and Frame, and we really tried to get to the idea of what it would look like and feel like if all writing at a company was systemized and that really came through in the visuals. You know, for, for the B, we just had so much data right on go-to-market and crazy NRR and just off the charts growth and great customer stories. And so from a visual perspective, the B and A decks looked really, really different. But I do care a lot about design,about brand. Our creative director is a genius, and it’s literally all him. And I think it helps to have founders who really care that if the slide doesn’t look great, I will ask for help. And now we’ve got, you know, another brand designer working with him, Nastia. So, you know, it’s always been a very visual company from a product perspective, you know, we get tons of props from folks on the UX of our chat interfaces, like in the digital assistant interfaces, as well as the the custom AI apps interfaces, the setup. So we’ve made generative AI UX really simple, even in an enterprise setting where you’ve got thousands of users to configure. And so it just has to make its way to marketing. And yeah, I love our site, the team does an amazing job. And you know, the investor decks, I just feel like it’s my responsibility to make sure they really reflect the quality that is in the product, and as in the marketing,

Walter Thompson  17:19

When did you bring in outside help? Was it Series A or seed stage, as far as helping you do the visual presentation?

May Habib  17:25

It’s always been mostly in-house — on the video side, we’ve always used external resources for video. And it hasn’t really been our intention, but every, like 10 to 12 months, we have a company video. So we’re on our third iteration. I love it. It’s on our homepage right now, check it out. Andy helped us with that, too, plus a second person, Jamie, has also been amazing. But we’ve never had an in-house video person, we probably should. It’s not a P0 this quarter. But I imagine it will be next. But on just like the pitch deck, it’s always been internal. And the content for the decks is its own workstream. And for the B, you know, it was a lot of work, because it is the work of really distilling down the data into a story that ties to your future and also really, you know, takes a candid look at the past, that’s not easy. And so I think it really helped that we did the deck in the data room really in the same sprint, Walter. So it actually started with the data, it was kind of iterative, so sort of like a rough outline of what we want to say. And then how would that be supported in the data room? Well, what’s the double-click? What’s the double-double-click? How are we going to gate the process as well? So I sort of did like the under the trnt first meeting. So if I had a lot of trust with somebody, they kind of got one deck in the first meeting, if I was just meeting somebody, they got a slightly different deck in the first meeting. And then what would different kind of gates look like, what would it unlock in the data room? And so that really that kind of iteration with then “oh, what do we put in the slide? What questions are we going to answer in the deck versus you know, where are we going to send people for more data  in the data room?” So that was about a three-week sprint that I did with our head of go-to-market ops and my chief of staff, and honestly they did most of the work after some of my initial thoughts.

Walter Thompson  19:45

The AI landscape has shifted considerably since you raised your initial seed and series A, so how have you adapted your communication strategy or marketing strategy, whatever you want to call it, to to compensate?

May Habib  19:58

Great question. I have got I’m straight to the people, Walter! And I would say, probably, even till the Series A, I think I looked down on people who were active on LinkedIn. I don’t know, it just was like, it just felt like, I don’t know what it felt like —

Walter Thompson  20:18

I have some experience here? I don’t want to, I don’t want to shut you off. From my perspective, but I, but I haven’t liked about LinkedIn is this whole concept is that everyone’s a thought leader. Thought leadership is great, but to me, it’s meant to make the speaker look good. It’s not meant to create a lot of value for the person receiving it. How do you feel about that? 

May Habib  20:40

Yeah, maybe? Maybe that’s maybe that is it? I think that’s it. I think with generative AI, it really was different, because I felt like I had something to contribute. You know, I didn’t feel like I was doing it. Because it would help sales, or — 

Walter Thompson  21:01

 — performatively make yourself look good or establish your credentials — 

May Habib  21:06

I really felt like, almost like an obligation to share. And, you know, there were things that folks had said, Oh, even investors, you know, share your journey, blah, blah, blah, perseverance, blah, blah, blah, you know, that never also felt natural. And I actually, you know, now I’m very active on LinkedIn posts multiple times a week, 25,000 followers, I love LinkedIn. And I love the community there, and the people I’ve met there. And I would say, none of it has been about the journey every once in a while the leader posts about our team, you know, but I’m just not comfortable talking about, you know, the sausage making. The learning, though, is so, so important, it’s mutual, I’ll post a hot take, because I kind of also want to see who comes out of the woodwork on it and the number of awesome customer conversations and prospective customer conversations I’ve had as a result of just posting what we’re learning, you know, on on the enterprise generative AI journey, it just been great. So I guess my shift on communication strategy has really been, don’t be afraid to go out of your comfort zone, but also, you’ve got to be authentic and right. And LinkedIn just didn’t feel right for me until I really felt like I had a unique point of view, to share that people truly couldn’t get anywhere else, you know, otherwise, it just felt like, you know, wasting people’s time.

Walter Thompson  22:42

As hot as AI is, I’ve heard that a lot of startups are meeting strong headwinds when they’re trying to sell to into the enterprise, not because they’re anti-AI, but just because they don’t have a lot of internal expertise to evaluate what’s good or what’s bad, or what’s hype? Is that something you’ve seen, have you encountered this issue? And if so, how did you work around it?

May Habib  23:01

I think enterprises are getting fatigued. And so, you know, startups always had an uphill battle in the enterprise. And now you’re trying to pitch something that AWS and Azure and Google are in there pitching, OpenAI, plus another 50 startups supposed to the CEO and the board is in their inbox plus there is like the 800 gsi, that’s in there for attention to it’s a lot. And the security risks here are really real for the enterprise. And even for enterprise grade platforms, where the whole thing can sit inside of somebody’s cloud, right? The months of work you have to go through after the org wants the thing. It’s real. And it’s not for everybody. And you got to really love enterprise users, and enterprise problems, and working deep on transformation with people to I think, love this. You also have to love going to Vegas, a lot of enterprise stuff happened in Vegas. That’s weird. I’ve been there twice this year. I literally had not been in a decade. That was a half-joke, but you know, it’s just a very different motion. So I don’t know that it’s necessarily an AI problem. It’s a problem that AI risks make really stark that there is just the level of heft, breadth, depth. We’re hiring a CISO, because it’s not just about having the right answers on that security questionnaire. It’s about really having folks on your team that have the same kinds of experiences of these enterprise folks. Right to really be able to reflect kind of confidence right in, in your posture. And so, you know, it’s not for everybody, we love it, we’ve embraced it. We love our enterprise customers.

Walter Thompson  25:19

First half of my last question, could you share a few words of advice for somebody who’s getting ready to fund and launch an AI startup in 2024? How can they communicate their vision in a way that makes them stand out in a very free crowded field? Hmm.

May Habib  25:35

What’s really cool about this space is just how tangible and hands-on the advances of AI capabilities are and the product, the storytelling is so vivid. Today, we were on-site at a customer, a CPG company [with] globally recognized multiple brands. And they’ve got, they’ve got this problem, where the legal review of ads takes literally weeks and weeks and weeks. And so we built an app in real time on the Writer platform in their office, where they uploaded an ad. And it told them whether the dog was too overweight for the laws of that country. Those are actual laws. And it was just — they were blown away, like ‘holy crap,’ right. And that’s what you can do with a full-stack generative AI platform. If you are launching a company, show, don’t tell if it’s AI. Show, don’t tell it, because the capabilities are so wild, you can really blow people away showing them.

Walter Thompson  26:50

That’s amazing. Here’s my last question for you. If you were interviewing at a seed-stage AI startup, you’re across the desk, you’re looking for a job, they’re thinking about hiring you, what are some of the questions or concerns you’d want to have settled before you could say yes.

May Habib  27:07

I don’t know if I put myself in that position. But if I were really young, and were interviewing at a seed-stage AI startup, you’re in it to learn, right? I wouldn’t ask about funding. Well maybe runway, you want to make sure you have a learning trajectory for 18 months, at least. But I would ask, depending on if it’s a non-technical role, I would ask about the customers, “who’s gonna be using this? Who am I going to be talking to every day? Who is this for?” And then if it was a technical role,”what part do I get to work on? And I do think the getting alums to cool, do cool stuff, part of the tech stack has just not been it’s not a solved problem, right. And there’s a lot of innovation in how you connect LLMs to data structured and unstructured, a lot of innovation in how you steer LLM outputs. And so, you know, I think there’s just much more interesting stuff to be doing than training models. That is really hard work. And there’s a ton of innovation there too. But, you know, I think I’d want to be closer to the application layer. And so, you know, depending on the company, what they were doing, those would be some of the things I’d be asking you about.

Walter Thompson  28:40

Excellent. May. Thanks again for a fantastic conversation. I really appreciate it. 

May Habib

Great talking to you, Walter.

Part 2

Walter Thompson

I’m talking with Gaurav Misra today. He’s the CEO and co-founder of Captions. Hi, Gaurav, thanks for joining us.

Gaurav Misra 30:18

Of course, happy to be here.

Walter Thompson  30:19

Let’s start with the basics. How did you and your co-founder come together?

Gaurav Misra  30:25

Totally. So, you know, my co-founder and I have known each other for a long time. And that’s not a very common thing with startups, usually, I think people often meet their co-founders, you know, you know, while they’re coming up with their idea, or the thing about starting a company, but in my case, my co-founder, and I met about 10 years ago, 10 years before we started the company, at a totally other startup. And, you know, we only overlapped there for about three months, but we really kept in touch and got along. And we both always sort of had this idea of, hey, we’re gonna start a company one day, and we would discuss it, we would meet up every couple of months, you know, we even move cities in the middle of that at some point, and still would connect with each other. And that connection really stuck with me. And then when I actually came around to hey, I’m actually ready to start a company now. You know, he’s the first person that came to mind. And since we’d been in touch for so long, it just seemed like the right person to work with.

Walter Thompson  31:18

Can you talk briefly about how your skill sets complement each other? Why does this work for you?

Gaurav Misra  31:23

I think that complementary skill sets are very important. As a founder of a company, you kind of have to have a generalized skill set anyways, very likely, you’ll have to do almost everything in the beginning, maybe you’re an engineer, but you’ll still have to do sales or marketing, or, you know, maybe you’re recruiting, so you kind of have to have that generalized skill set. So it really comes down to at the end, what does your co-founder want to do out of all the things that the company needs to do? And what do you want to do? Because there’s only the two of you, or the three of you at the beginning, right? So everything that needs to be done needs to be divided in some way. So with us, you know, it actually evolved quite a bit, we both have a pretty generalized background, you know, my co-founder, Dwight also has an engineering background, he also has a product background, and he’s done a bit of marketing, a bit of everything, right? I enjoy all of the same things as well. So we’ve kind of shifted over time, done a little bit of this, a little bit of that, and see where we excel, right, do more of that. You know, as the company has grown, obviously, we’ve hired people to do a lot of these things. And, you know, people are way better than we are. But in the beginning, we kind of mixed it up a little bit and tried a bunch of different things.

Walter Thompson  32:36

So when you and Dwight sat down and started formulating ideas for the company, did you start with a vision statement that was kind of an aspirational thing that described what you wanted to achieve? Or was there a mission statement that kind of described what you wanted to accomplish and how you got there? What was your early process?

Gaurav Misra  32:52

What we were interested in was social media, actually, in the beginning, the reason being that it was evolving heavily in terms of you know, how people communicate on social media, whether, you know, previously, it was more maybe text or photos, and now it was more videos dominating the landscape, right? Or whether it was some other scenario, like maybe AI is playing a bigger role in it, right. And so we were excited about that space evolving. And we knew that there was something there that we could solve something we could do. So that’s kind of how we initially picked it as an area, we want to come up with a lot of different ideas in this space and see what gets us excited and what where we can find product market fit.

Walter Thompson  33:38

Okay, so for your first employee, how did you initially articulate your vision?

Gaurav Misra  33:42

The interesting thing at that point is we were a little bit open-minded about the vision ourselves. And I think that’s something that is important to do at the early stage, is not to get too locked into one idea or one angle that you want to take. Because the evolution is so fast at the earliest stage you should almost assume that you will be changing ideas very quickly, evolving and moving. Because if you don’t, then it’s definitely going to be very hard to work out. And very rarely is the first idea, the right idea. The way we thought about it is like, “this is the area we’re interested in, we’re gonna go explore, we’re gonna go talk to customers, see what people are doing, see what the trends are today. And then we’re gonna try to build a bunch of different things. See, what has legs, what do people actually want? What do people come back and use again, and that’ll help us guide right, like, what’s the direction? What’s the flow? Where’s the river actually flowing?” Just to get our bearings and figure out what direction we should be going in. So when we hired our first employees, including Cam, I was just talking about, you know, we were kind of pitching them this idea of we’re going to experiment, right, we’re going to experiment this is the area so as long If you’re interested in, you know, some of these fundamentals, we’re gonna go and experiment, find what’s interesting. And I think that’s really important to set the expectation. Because, you know, the last thing you want is people getting discouraged when you have to change direction, especially in the early days, right? You want people to get excited about changing direction, let’s try something new. Let’s build a whole new thing. It’ll be fun, right? And so that should be almost the expectation from the beginning.

Walter Thompson  35:26

You were talking to early customers, which I mean, everyone does as part of the customer discovery process. But Captions is really a product for social media users. Who are those customers you identified that you wanted to talk to and understand their problems and their challenges?

Gaurav Misra  35:42

We were looking at a lot of college students and sort of people who were trying to get into YouTube, trying to make a YouTube channel trying to, you know, maybe get into TikTok, and, you know, become a TikTok creator, we weren’t going in and talking to people who were established in terms of someone who has a ton of followers or something like that, but really people trying to break into the area, and what are the challenges they’re facing, though, initially when we started the company, our goal was to be a social media platform ourselves. And our thought was hey, maybe we’ll build a creation tool to get people creating on our platform, and that’ll be a way to start off potentially a social media platform. But eventually, obviously, we realized that we were way more excited just about the creation and the opportunity there. So that’s kind of the evolution of the company. But we went out and talked to a lot of people to help solve that creation, you know, problem that we were trying to go after,

Walter Thompson  36:39

Were you talking to investors with the intention of being a social media platform? Or was that something that you did after? When did that even happen?

Gaurav Misra  36:46

We definitely talked to investors about being a social media platform. That was the initial sort of approach, and the initial way we pitch to investors was like, “hey, we’re gonna make a creation tool,” and actually, Captions existed at that point, like it was, you know, the earliest version of it, something we had put together in two days, basically. But we took that and we went to investors, and we were like, “hey, this is the beginning, you know, this is how we’ll attract our first creators on the platform. Right. But once we have a critical mass of creators, we’re gonna convert this into a social media platform.” So that was the original pitch. 

Walter Thompson  37:23

Jumping back, around how much time did you spend doing market research and customer discovery, after you settled on the newer direction for just kind of being a toolbox?

Gaurav Misra  37:35

A lot. So I think this is like counter to probably the advice most people will give, because a lot of people think of user discovery and sort of like talking to customers, especially in a consumer space that we’re in as, not as interesting, or sometimes people think that it’s not as useful, because how are you going to find these people? How many people are going to actually talk to you, right, given there’s billions of people in the world, but actually, some of the social media platforms themselves like TikTok. And, you know, nowadays, there’s Reels and YouTube Shorts, they actually ended up being a really good way to see what is popular to understand what the trends are, and to understand what people are doing right day to day. And I think it’s a really good way to actually even test startup ideas, even if they have nothing to do with, you know, social media specifically, but if they’re consumer ideas, to put, you know, a pitch out there on Tik Tok or another platform and see if it resonates with people, people will comment, right, though, it’ll come on their feet, and they’ll be like, “this is a bad idea. I don’t like it.” Or maybe they’d be like, “oh, I love this, this, if only this existed.” And that initial validation, I think, is very important. And sometimes, if you really get it, right, and if you really hit it, right, it can just go viral right there, right. And you can just get a ton of feedback instantly on what people might be interested in. Maybe you’ve hit something, something really cool, right? So I actually think it’s a great idea to put the idea out there on social media platforms, or even see what the trends are. Currently, what are people doing, you know, there’s a niche for everything on social media is finding those niches and discovering what our existing users are doing. It’s a great way to do that. Without having to think about, “how am I going to find these people to talk to?”

Walter Thompson  39:25

Were the investors you spoke to, were they supportive and on board for the change in strategy and in focus? They believed enough in the toolset that they weren’t scared off by, “let’s not be a platform, let’s just be tools for helping creators, that was okay?”

Gaurav Misra  39:41

Yeah, there was definitely a sort of a transformation period there in the company, right? We were a very small company at that time, just a couple of employees, for the first year or so. A lot of it was us convincing ourselves that that was the right vision at first, but then once we were convinced, and we saw the data, and we really liked what we saw, then going and convincing investors. But I think at the end of the day, it turned out to be way easier to convince the investors. The hard part was convincing yourself.

Walter Thompson  40:16

It makes sense. The investors I talked to are way more open, they expect  the iterative process, they expect pivots, and they’re not spinning, they’re not thrown by it as much as I might be. Or you would be, I suppose, because it’s not their baby. 

Gaurav Misra  40:36

For me, it might feel existential, like “oh, my god, we’re changing the whole direction, is this good or bad?” And it’s something that you really want to get right for your own sake, for the employees’ sake, for the investors’ sake, everybody’s sort of trusting you to build something interesting, right. And so it’s definitely a lot of pressure. But I think, at the end of the day, you just have to kind of come back to that original idea that change is expected. And especially with the initials teams that have this idea that we will be iterating, we will be evolving. If we’re not doing five different ideas, then we’re not doing something right.

Walter Thompson  41:15

Founders build relationships with investors over time. So how quickly did you recognize the investors who you could work with? And was it harder? Was it easy to recognize ones who just didn’t get it, or were you were just like, “I didn’t want to take your money. I can’t work with you.”

Gaurav Misra  41:29

Yep. At the earliest stage, especially at the seed stage, or pre-seed stage, or anything in that area, I think it’s really important to have an investor who understands the space inside and out. So, if you’re working on let’s say, camera technology, then you should have an investor who understands what goes into building camera technology, right? And the reason I say that is because there are going to be ups and downs in doing that. And if the investor doesn’t have an understanding of why those ups and downs are okay, or not, okay? Or then they might become more of a burden on you, because they’ll just keep asking you questions about are things going okay, or not going? And they may not have the ability to actually make a call on their own, looking at the data to say, “yes, things are going fine. And we just need to do these two or three things to actually, you know, go make this something bigger.” Or they might look at even look at something that potentially has success and be, “yeah, that’s cool, but not at the [moment], maybe that’s not interesting, they may not be able to see something that does work, right for what it is. So I think that alignment, the beginning is really important, which is why we went and looked for investors who really understood the space. And for us, that was social media at that time. We’re still in the social media space in many ways. So that hasn’t fundamentally changed. We’re just building a different product and that space, so the university has turned out to be the right investors for that. 

Walter Thompson  42:57

From your perspective, if you’re doing a lot of investor education, does that mean you’re basically talking to the wrong people?

Gaurav Misra  43:01

I think it’s tough. In that case, I would say it’s wrong every time. And it’s not something we’ve had to deal with too much. But I’ve heard from other people that it can be, you know, a time sink. And usually,  at the later stages, it’s something you know, it’s harder tofind people  who just get what you’re doing. Anyways. So I think it’s a tough ask to say everybody should get exactly what we’re doing, right? Sometimes people bring different values and or have different expertise that you might need in your company. So I think that statement probably evolves over time. But I think at the earliest stage, you probably really want someone who really gets it, who you get along with, because it’s a long journey. I mean, to give you an example, on our first investor, you know, Matt has met with us every two weeks, right from the beginning, right, without, with no breaks, and has listened to the worst of what we’ve done the best of what we’ve done, given us advice at every point, not judge, you know, positive or negative on how we’ve been operating, but given us the right tools to be able to do the right things for the company.

Walter Thompson  44:12

Looking back, what’s been the hardest part about communicating your vision to other people?

Gaurav Misra  44:17

I think the hardest part has been, — I would say it’s not been like articulating it or putting it in the right format, or, you know, putting it on a PowerPoint or you know, whatever. I think that stuff always gets figured out. But the hardest part has been what do we actually want to do, and what did we see actually working? Because if you have investors that can understand the space, then oftentimes, if you’re not convinced yourselves, and you’re not exactly convinced that you really believe in this direction or you want to do this, then investors can see through that a lot of times, especially the ones that are well educated in this space. So I think the number one step is figuring out yourself, what is it that you want to do, and what do you see actually working? And then putting that into a format that other people can understand is probably secondary,

Walter Thompson  45:14

Was it just totally kind of a self taught process? Did you rope in people to advise you? How did that work?

Gaurav Misra  45:22

A lot of it was, I think self-taught, you kind of have to figure out your own way of doing it in terms of people doing it for the first time, I would think of it you know, the startup world is actually not too different than how a big company might operate, like a very large company. Soif someone is starting a company who has worked at a very large company in the past, like an Amazon or a Google or something of that sort, it’s actually very similar, right? Someone has an idea, they have to go to someone very senior to pitch this idea and say, “hey, we need these resources to actually make this.” This person might decide, “you know, what, I don’t like the idea. So it’s not going to happen.” Or maybe they’re like, “you know what, I love it, you’ll get two people, and a year of time to go do this.” And then you do it. And maybe it works really well. And you go back and the next OKR meeting, and you show them, “oh my god, I achieved all these things. We could use five more people, and we could do these other things.”. And so it’s actually very similar. And that’s your Series A or something, right? So I would think of it the same way, I wouldn’t get too intimidated by the process, or the people or the investors. Everybody’s just people, I think everybody’s just trying to do something interesting and cool in their life. You just have to come to the table with that attitude and show people what you’re excited about and what you want to do, and how you can see it working in a similar way as you might do within a company itself.

 

Walter Thompson  46:44

I think with a lot of early-stage founders, there’s a lot of — maybe this is my perspective as a journalist, it seems like there’s a strong expectation that somebody on the founding team has strong storytelling skills. Do you think of yourself as a natural storyteller?

Gaurav Misra  47:00

I don’t think of myself as a natural storyteller. I think it’s something that I had to learn a little bit more of, I do think it’s an important skill, because at the end of the day, you know, the numbers will tell the story of your company to a certain extent, like, “hey, things are going in this direction.” But there is a larger vision. And that’s the whole point of venture capital in some way.  Itt’s not just about what is happening now, but the vision that’s possible years down the line of what could be achieved. And a lot of the time, it’s very transformational. It’s something that is world-changing in some way, Or it could be that big, and the ability to tell that to people, win people over, is kind of fundamental, not just from the fundraising perspective, but from the employee’s perspective. They want to be inspired, and they want to be able to see what could be right. And I mean, for every side, almost for anybody you talk to, as a founder, you kind of have to sell the story. And this idea, this vision. And not everyone’s gonna buy it. That’s for sure. But you have to convince the right people basically.

Walter Thompson  48:11

Weird question, but do you have any experience as a writer? What was your storytelling experience before this? What was the most storytelling you did? Do you have any kind of creative writing experience, or what’s your background before this as far as weaving a narrative?

Gaurav Misra  48:29

I started sort of picking up a little bit more of that for my career. As I mentioned before, it kind of becomes important internally in companies to to an extent, because companies internally operate very similarly. You have to sell what your team is doing. And make sure people are convinced that what you’re doing is important. Those are skills that probably everybody should work on, and everybody should build over time as a career grows. Besides that, I switched from engineering to product design, in my career. So sort of the visual storytelling aspect, I learned a lot at my previous company where I used to work, which was Snapchat, and I got a chance to work, you know, on the design team there and see their world class design team, how they operate. And the team works very closely with their founder, who’s also a great storyteller. So you know, seeing that in action, and seeing how that happens day in and day out, was a huge learning experience for me.

Walter Thompson  49:35

Are you still kind of Captions’ chief storyteller, or have you handed that role off to somebody else?

Gaurav Misra  49:42

Most of the time, I’m the one doing that. So I think it’s important because I think it’s one of the most critical pieces of what drives the vision and the direction of the company. And I think it’s something that the founders should always have a hand in? 

Walter Thompson  50:01

Can you talk about how you kind of attach your vision for the company to your go-to-market strategy? As far as the value proposition you were presenting to people, what was it? And how has it changed since you went into the market?

Gaurav Misra  50:16

One of the interesting things that we’ve all often faced and many companies often face is some sort of disconnect — there’s the vision, but we’re going to mark it in a totally different way. And I think in those cases, you have to be kind of honest with yourself and be like, “something doesn’t seem right.” And often, when something doesn’t seem right, something isn’t right. And you have to either evolve your vision a little bit, or evolve your strategy a little bit. And when you do that, everything feels right. Like, “wait, we actually solve something.” But it does require a bunch of thought. And I think for us it’s shifted over time, both in terms of vision, we’re constantly evolving it and aligning it to what is most current and what will work best in today’s environment. But also on the strategy of how we actually sell the product is evolving exactly with that vision. And as long as we can keep those two things lined up side by side, it seems like we can keep product-market-fit going and expanding. I think when those two things kind of go in different directions, then things start to go wrong a little bit. And you’re doing something and saying something else. That’s the beginning of all problems, I think.

Walter Thompson  51:28

Noted. So the landscape has shifted considerably since you’ve initially raised. Have you adapted your communication strategy since then, or your vision strategy since then with an eye towards raising future funds?

Gaurav Misra  51:42

It’s always evolving. Three years ago was a much easier time to raise money for many people, it was just a different environment. That’s obviously shifted over the last three years, especially with interest rates and all that, just the general macroeconomic situation. Not to say that that’s the most important thing for raising funds. As the company grows, the vision does become more and more crystal clear of what you’re trying to do. A lot of the things that were ambiguous or things that need to be figured out, or things that were a little bit nebulous in the early days, you’ve found answers to those questions by now, you know what works and what doesn’t work. And actually, you have a very simple and strategic idea that works at this point. Hopefully. Now, the problem is now almost in reverse, like, what should you reveal, because at this point, the core of what you have works. And if you say too much, other people might be interested in jumping on that, as well: “Oh, so that’s how it works. I get it, let me do that, too.” Whether that’s a big company, or whether that’s another startup, or whatever that might be. You have to be a little bit more careful about how you articulate your vision at this point, and to what detail you go into, revealing all the learnings that you’ve built over the last three years. You’ve spent a lot of time building a ton of learnings about what works and what doesn’t work? And what is the vision actually, what part of the vision is the core vision?

Walter Thompson  53:22

It seems like the people you’re talking to, they’re eager to adopt new AI products. So it’s not an issue for you?

Gaurav Misra  53:28

Definitely, from what we’ve seen, and we do get a lot of outreach from enterprise customers as well, in terms of integrating our technology into their workflows. And we’re not prioritizing that at the moment. But it does seem like there is an appetite for it. But I think there’s a very specific thing that people should think about when building, certainly AI technologies. Currently, there’s a lot of hype, as everybody knows, and there’s nothing wrong with that, I think it’s a good thing. People are excited about a new technology. But with hype, what happens is a lot of technologies that are built that may not be useful in the long run, but are exciting and interesting in the short run. And those don’t tend to make great businesses at the end of the day. So I think what’s most important to watch for right now is whether people retain and use something over and over again. And in my opinion, the best way to tell that is by looking at what people are doing today. And then you provide an alternate solution, right? Maybe it’s powered by AI, right? And so once people try the alternate solution, they should never want to go back to the original, they should be like, “wow, my life has changed forever. This new thing is what I’m going to do, right, no matter how simple that thing is.” If you can switch people over from the original workflow to something new, and they stick to it, then you have something right. And I think that’s what we look for. I think that’s what you know, we’ll build the right but the best businesses I think in the long term.

Walter Thompson  54:54

Last few questions. Can you share a few words of advice for a team that’s appearing to fund and launch an AI startup in 2024?

Gaurav Misra  55:04

My take on it is that it’s always good to have a prototype at the beginning, right? Don’t start by just going and raising money, start by putting, pen to paper and just creating a first version of something. It doesn’t have to be the idea that’s going to be the company forever, but you want to at least create the first version of something that you can show investors and get them excited. Maybe you can even show it to people. And you’ll get a lot of feedback very quickly on whether people like it, whether it’s useful or not, and investors will give feedback as well. It helps quite a bit with even just showing investors that you have the ability to actually create at the end of the day and put something in people’s hands, which I think is the biggest blocker at the earliest stage, actually taking an idea and converting it into reality in any way, even if it’s not a great idea, that doesn’t matter. That’s what I think helped us the most in the beginning is creating actual prototypes and showing those to investors. So I think the same applies even today, it probably is evergreen, especially in the AI space where it’s very difficult to create some of these things. But the right people with the right mindset can definitely do it.

Walter Thompson  56:28

Final question, words of advice for somebody who’s working in tech already, let’s say they’re working in a FAANG company or a large startup, who’s interviewing about an AI startup. What kind of questions should they be asking during the interview process? What should their due diligence process look like?

Gaurav Misra  56:43

The number one factor that will determine the long term success of most of the AI startups that are there right now is retention at the end of the day. Are people going to come back and use this thing again and again? And if retention is there, then everything else can fall into place. So I would think most about that. But at the end of the day, you know, regardless of the retention question, I think it’s a good time, in general, for people to switch into the AI space. It’s not, you know, it’s not one of those things that’s a small change that will kind of be there and then be gone. It does feel like a more fundamental change, especially for more technical people. Whether it’s an engineer, or maybe a designer, where there’s a whole new skill set to learn. There’s a whole new space that’s expanding, that’s very different from traditionally how engineering has been done. And the earlier you can get into it, there’s a lot of value in it. It may not be the one company today that you join, right, but the skills that you’ll learn there actually will be very applicable in many, many, many, many companies in the future, I believe. But I think for the success of the company, retention is probably the number-one factor.

Walter Thompson  58:04

Gaurav, thanks very much for a great conversation. I really appreciate the time.

Gaurav Misra  58:07

Thank you. It’s been awesome.

Walter Thompson  58:11

I’ll be right back with some show notes. 

Thanks again to Gaurav Misra and May Habib for joining me on the podcast. Coming up next, I interviewed Rehan Jalil, President and CEO of Securiti, about basic best practices founders need to get a startup to a million dollars in annual recurring revenue, and beyond. A serial founder who’s now in his third company, Rehan reflected on his own journey to share what he’s learned about connecting with early customers product development, conducting ecosystem research and establishing an initial sales motion

Rehan Jalil 59:09

Yourself, and not just you, but as a team, you’re ready. If you’re ready, responsive, that’s where things change. You get ready, you establish strong relationships and strong trust with you and your customers.

Walter Thompson  59:23

If you’ve listened this far, I hope you got something out of the conversation. Subscribe to Fund/Build/Scale so you’ll automatically get future episodes, and consider leaving a review. Follow Fund/Build/Scale on LinkedIn and YouTube. For now, you can find the FBS newsletter on Substack. The show’s theme was written and performed by Michael Tritter and Carlos Chairez. Michael also edited the podcast and provided additional music. Thanks for listening.

Embrace the Future: Meet Your AI Teammates

Sketch graphic of the 5As of Cognition as a Service (woman with robot at a computer)

AI may not be coming for your job anytime soon, but it surely is coming to work alongside you.

Introducing your new teammates: Devin, the AI software engineer; Hippocratic, the AI healthcare worker; Outreach Kaia, the AI sales assistant; Evenup, the AI legal assistant; and Hawkeye, the AI ITOps engineer (founded by Goutham Rao and Vinod Jayaraman of NeuBird, a team of Mayfield repeat founders who debuted with $22 million in funding today).

Reflecting on conversations with 100s of entrepreneurs, we’re witnessing a shift from Automation to Augmentation. Artificial intelligence isn’t about replacing humans; it’s about augmenting intelligence. In this new era, AI liberates us to forge new relationships and adopt innovative behaviors.

Despite fears of AI replacing humans, I recall the discussion about offshoring two decades ago as the lead investor in Persistent Systems, India’s product engineering offshoring giant today. Then, as now, there were concerns about the impact of technology on humans. However, unlike the offshoring wave, I firmly believe AI teammates will not only boost productivity but also enhance, amplify, and elevate human capabilities.

Take Hawkeye, unveiled today by NeuBird. For example, an e-commerce company may notice that its website is performing poorly at populating shopping cart suggestions. Traditionally, this would require assembling a cross-functional team involving IT, web developers, and data analysts to investigate the issue, a process that can be time-consuming and resource-intensive. Using NeuBird, the same company can simply ask, “Why is my website running slow?” and “How can I resolve that?” NeuBird’s Hawkeye will diagnose the issue, contextualize potential reasons for the problem, share steps needed to resolve it, and even write code to fix the issue. This frees ITOps engineers to assist more customers and tackle complex issues, showcasing the power of AI-human collaboration.

Welcome to the Era of AI Teammates. Together with humans, they automate tasks, accelerate productivity, augment capabilities, and amplify creativity, advancing humans to superhuman levels.

Fund/Build/Scale: Understanding Privacy and Compliance (Transcript)

Here is the transcript (edited for space and clarity) of the conversation between Fund/Build/Scale podcast host Walter Thompson and Laura Bisesto, global head of policy and privacy at Nextdoor.

Laura Bisesto  00:00

I think the person who’s developing the product should have a conversation with their fellow colleagues about different issues, that the product may raise different risks. And that’s — you know, in itself AI ethics — you don’t have to be an ethicist to start an AI ethics program. I think anyone who’s developing a product in this space should consider a way to measure its impact, or at least talk about it.

Walter Thompson  00:30

That’s Laura Bisesto, global head of policy and privacy at Nextdoor. I interviewed her in January 2024 at her company’s San Francisco headquarters to get her thoughts about the regulatory landscape facing AI startups. We talked about compliance, how small teams can build frameworks for managing data and privacy, how to recognize when you need to hire a lawyer, and the overall importance of planning for worst case scenarios. She also had some advice for rolling out new AI-powered features, and navigating a patchwork of state, federal and international laws. I’m Walter Thompson. Welcome to Fund/Build/Scale. 

Laura, thanks very much for being here today. I appreciate it.

Laura Bisesto  01:32

Thanks so much, Walter, for having me. I’m really happy to be here.

Walter Thompson  01:35

So your title is, exactly?

Laura Bisesto  01:39

I am the global head of policy and privacy and regulatory compliance at Nextdoor. I am a former prosecutor and I came here to start our policy program, which includes working with governments around the world, developing our own internal content policies, as well as managing our privacy and regulatory legal work. And, and all of that with AI. There’s a big through line, it covers all those surfaces. And so recently, I started our AI ethics committee as well.

Walter Thompson  02:04

I wanted to talk about a lot of very basic issues that early-stage AI founders are gonna face, but kind of starting off first with building an AI ethics framework. I guess the first question I would say is, if we’re talking about a small team of people, largely technologists, whose job it is to get the ball rolling for creating this ethics framework, who does that? Who owns it?

Laura Bisesto  02:27

I don’t think it necessarily needs to be a lawyer or policymaker’s job, I think the person who’s developing the product should have a conversation with their fellow colleagues about different issues that the product may raise, different risks. And that’s, you know, in itself AI ethics, you don’t have to be an emphasis to start an AI ethics program, I think anyone who’s developing a product in this space should consider a way to measure its impact, or at least talk about it. And we’ll call it the red team, some places just sit in a room and talk about some of the bad things that could go wrong and, and how to mitigate against them, and maybe write them down or write down potential solutions as you think through them.

Walter Thompson  03:08

So I’ve worked in a number of startups myself, worked on things like community management and content, where it was my job to come up with a Terms of Use document, is an ethics framework  something you can templatize? Can I take somebody else’s AI framework and kind of adapt to make it my own? Or do I need to start from scratch to really reflect my own problems and challenges?

Laura Bisesto  03:27

You can definitely start with other people’s. At Nextdoor, we developed an AI framework based on the White House’s blueprint, as well as the UK’s white paper. As we were looking to develop it, we took inspiration from other sources, there’s no reason to reinvent the wheel here. I mean, there’s really, you know, some different options in terms of how you want to protect users, protect consumers, or how your product will work and thinking about the different risks, and there’s just a suite of different principles, you could work for your business, for sure.

Walter Thompson  04:03

Actually, going back to that, recognizing when you actually need a lawyer. I know a lot of startups get along early on the kind of a fractional counsel approach, but a four-person team who’s just kind of getting started at the seed stage. When should they start thinking about, “when do we need a lawyer?”

Laura Bisesto  04:19

Yeah, and they don’t have to hire a general counsel, per se. I mean, if you’re thinking about complying with regulations, or just getting ahead of policy or ethics, I mean, there’s a lot of people that can do that work, they could be on your board, for example, and help give advice there for you know, a different a different setup. You know, traditionally you might have waited till person 100 to make a move, but nowadays, given the regulatory framework you’re seeing around the world in terms of AI, it’s no longer the environment where you can just launch, and eventually it’ll catch up with the rules and laws. It really will pay off to get ahead of it in advance. So when there are 10 people or when you reach a certain threshold of user data, it might be a good idea to start thinking about bringing someone on board at least on your board or asking your investors or outside counsel for advice. And you know, frankly, if you’ve got this incredible product, you may want to really be on top of the policy and the regulations. Because you, you know, maybe there’s actually even a story to tell to make sure you don’t have a competitive disadvantage when it comes to regulatory making that we’re seeing around the world.

Walter Thompson  05:33

Are there situations where the thing you’re making you’re working on kind of raises or reduces your need for legal assistance in-house? For example, if you’re working in something health or fintech-related or you’re collecting a lot of personal information or data on people?

Laura Bisesto  05:48

Yeah, absolutely. If you’re collecting personal data, there’s tons of new privacy laws that are passing around the US. I mean, we’re talking in the tens to twenties to 20s site that will go down because there’s just not that many states over the next few years. But there’s a real patchwork of regulations. When it comes to consumer data, there’s the general data protection regime in Europe GDPR, and the UK has its own and other countries have that as well. I think if you’re working in employment, if you’re creating a product for employment purposes, that’s a pretty sensitive area of FinTech as you as you mentioned, also any in biometrics, if you’re working with with that type of, of user, or personal data, or healthcare for that matter. There’s just different, those things can be pretty risky.

Walter Thompson  06:34

So let’s say a small team, they’re working today, they’re spinning up. They’re not in the market yet, but they’re doing customer discovery, and they’re talking to people. How do they fully understand let’s say, like, in talking to customers, if I was doing like, you know, I’m, I’m trying to spin up a veterinary services startup, I’m talking to vets and people who do health care, it’s that kind of thing. Pet Health Care. How do I come up with a checklist? Am I talking to industry experts? 

Laura Bisesto  06:59

Yeah, I think it’s a good idea to reach out to experts if you can. But there’s also a number of public resources. As I said, the White House blueprint for AI is really, really helpful. The AI Bill of Rights is what it’s called, also, the UK government’s pro innovation approach to AI regulations, they have just a number of ideas in there that could help you come up with different opportunities. Even on Nextdoor, I’ll give a plug for next door, we have publicly listed our principles for deployment of generative AI. I mean, those are just different resources that are available online to give you ideas about what might matter to regulators, but also your customers. And then of course, investors as well who want to know that you’re thinking about this and that you’re not going to have huge costs down the line.

Walter Thompson  07:43

I know you’re a very skilled attorney, but you didn’t create your GAI principles out of whole cloth. You had a team of people, I presume?

Laura Bisesto  07:51

Yes, I did. I had some folks. And we and most importantly, you have technologists and you have product people, you don’t want a roomful of lawyers creating these policies, you really do want it to come from the people that are building the product. So you want to bring everyone together and really talk through what you need, what you can commit to, how can you, you know, manage privacy, make sure there’s transparency, and that all is built into a product. And we absolutely use the White House’s blueprint for an AI Bill of Rights as inspiration as well as the UK’s work to help us come up with ours. And then also make sure it’s something we can commit to as well.

Walter Thompson  08:27

Have you rolled out these principles to Nextdoor’s users?

Laura Bisesto  08:33

Yes, we absolutely did at Nextdoor, one of our main values is to make sure we have users’ trust. And so we’ve launched several generative AI features. You can have your content rewritten if you’d like by what we call an assistant. And you can also have your content edited. And when we rolled that out, we also launched our principles. At the same time, our public commitment to making sure that users understand how their data is being used with generative AI as well as that there’s transparency that they know they’re interacting with generative by just some of those things are strong examples. And also, before we launched the product, we went through a series of tests to make sure that it wasn’t going to give a sub optimal experience to users. And we talked through risks, which really at the size of our company, we also have an advisory board that we can talk to about these issues to make sure that the experience is good for users. So really building that out

Walter Thompson

A user advisory board?

Laura Bisesto

This one is an advisory board of social scientists and academics that help us think through some of the issues. But we also created a way for users to give feedback. For example, on Nextdoor when neighbors are providing comments or feedback, you know, there’s different language or tones in different communities and we wanted to make sure that it sounded like the neighbors who were speaking — not too formal, very conversational, that sort of thing. So we actually created a way to get feedback from users as well

Walter Thompson  10:03

Who looks it over before it rolls out? And who decides this is safe to roll out?

Laura Bisesto  10:08

The product manager should really oversee a lot of that risk management. And I think the most important thing is that, before you launch a product, you get in a room and you talk about the bad things that could happen with the product, like just talk about it, it doesn’t have to be this perfectly organized, lawyer led meeting, it can just be like, let’s just talk about worst case scenarios here. And, and talk about because nobody’s thinking about that when they’re building a product. They’re thinking about all these incredible things that we’ll do, and I’m sure it will. But let’s talk about the risks and the things that could go wrong. And, you know, just just doing that is simply a good step. But also being aware if you’re launching a product that is, you know, taking a bunch of user data and doing something with it that maybe users wouldn’t expect you to do. And you should also be aware of the regulations and rules around using private private users data and the risks you’re going to engage in. So there’s different, it just depends on what you’re doing. But at the very least, for anything you should get in the room and talk about where things could go wrong.

____________

Walter Thompson

How would you describe today the regulatory environment for AI startups operating in the US and in Europe?

Laura Bisesto  12:25

The regulatory environment is evolving. Absolutely. I think AI will remain a top priority for governments around the world for the foreseeable future, at least the next five years. And I think there’s an urgency from policymakers to get it right. I think there’s a sense that they haven’t been able to regulate as well around competition or liability content, moderation and content liability. There’s been concerns about that. And I think there’s a real desire to get it right. So there’s real attention and priority. I think the problem is, is what you’re going to see is that you’re going to have a patchwork of regulations, which is really not the reality of how your business will operate. You don’t intend to have a different operating model in different US states, for example. So I think what you’re going to see is, you know, a ton of action, but it depends, it remains to be seen where the actual legislation will come into play. I mean, you’ve recently seen that the European Union passed its AI act in December, the language won’t even be out for another month or so. And really will have a risk-based approach to how it starts going into effect, starting with the most riskiest uses of AI as the law classifies them. And then you’re probably going to see next a ton of US states introducing legislation, and it’ll remain obscene, what what’s going to pass in Congress, tons of hearings, tons of talk, I think, being aware of politics at play is important and to be able to make an educated guess as to whether things will move forward.

Walter Thompson  14:02

I’m guessing most of these companies are going to be based in California, at least to start. So does this mean that similar to the way that manufacturers are selling cars all over the country, but you want to make sure that they’re emission-proofed for California? Is this going to be the same thing for AI startups where they’re basically you’re in Columbus, Ohio, but you have to be compliant with California and the EU?

Laura Bisesto  14:23

California definitely wants it to be that way. I’ve been to EU events here around the AI Act in the San Francisco Bay Area and I’ve seen California legislators there seeking inspiration. There’s a number of pieces of legislation that are pre filed, that you can already see California’s leadership in action in that space. So I think that there’s definitely you can expect to have some laws to follow. I mean, at the very, very least you’ve got California’s data privacy law, and that really, if you use personal data that will come into play pretty quickly and a number of other states have followed suit, but California led the way there. And I think we can expect that with AI as well.

Walter Thompson  15:04

Getting into the Biden administration’s executive order that was issued in October of 2023. Is that correct?

Laura Bisesto  15:10

Yes, it was, I believe it was the very end of October, maybe October 30. So if I recall correctly.

Walter Thompson  15:18

Back of the napkin, what are the big points here, basically?

Laura Bisesto  15:22

Yeah. The Biden executive order really is dealing with eight core issue areas. And this is to be a leader in the world in terms of AI governance. I mean, this was announced before the EU passed its AI act before the UK’s safety Summit. I mean, this was leading the way. And it talks about eight issues, including testing and evaluation, competition, workforce and impacts, equity and civil rights, consumer protection, privacy, strengthening AI expertise, and government and global leadership. And a lot of the work it’s seeking is seeking its agencies, the federal agencies, to put forth rules and regulations around some of these issues. 

Walter Thompson  16:08

But Washington doesn’t move quickly.

Laura Bisesto  16:12

And no, no, no, no. And so I mean, some of these some of the things like for example, AI frameworks for NIST, that would deal with risk management issues. 

Walter Thompson

Sorry, NIST is?

Laura Bisesto

NIST is the National Institutes of Standards and Technology that has to do with cybersecurity. And it’s part of the Department of Commerce, their regulations, they’ve been instructed within 270 days to develop regulations and resources, and a new secure software development framework. And they have to create guidance and benchmarks for auditing and evaluation. Now, they’ve been told they have 270 days. But there’s there’s other issues like privacy. I mean, the White House urges Congress to pass bipartisan privacy legislation, given how AI can link together different forms of personal data. And I think that that’s, you know, less realistic that a bipartisan privacy agreement will pass in Congress at this point. So there’s different parts to the executive order, but none of it has an immediate impact, I’d say.

Walter Thompson  17:27

So if I asked you how this will be monitored and enforced, there’s no real answer at this point.

Laura Bisesto  17:33

But no, it’s totally spread out among different federal agencies. They did invoke the Defense Production Act to compel certain AI companies to share results of red team exercises with the government ahead of launch depending on what you’re developing and how sensitive it is. But the Commerce Department is supposed to help stand up standards for red teaming, and inform what has to be shared. So there’s a lot and they want to, you know, get into gene synthesis, screening standards, cyber issues, just AI with critical infrastructure is a huge concern. So there’s just a variety of issues, including labor as well, and how it will impact the workforce, but not clear cut by any means, at this point, just a really general statement of leadership.

Walter Thompson  18:18

So given that this is this new regulatory environment is still murky. I mean, that’s the best word I can use at this point. What do early-stage AI founders need to do today to set themselves up for future compliance?

Laura Bisesto  18:32

Right, that I think the best thing to do is be mindful of, first of all, the privacy laws, the consumer data privacy laws out there, that’s number one. Those laws really deal with a lot of some of the issues people are concerned about with AI when it comes to user data. If your product is using consumer data, that’s definitely something that’s concrete that you can look to. But you really need to try to follow along the best you can see if there’s someone you can get on your board that follows along politics doesn’t need to necessarily be your general counsel, as I said before, outside counsel, have someone that’s worked in emerging technology before or worked in DC worked in the political space and can really read the tea leaves and understand where where laws might pass or not pass. But I’d say, if you’re working with consumer data, figuring out the privacy laws is like a great first step in building that into your product as you design it, rather than waiting till later. And also just understanding that risk, as I said, doing an impact assessment and understanding where the risk areas are, then you will at least have a concrete understanding of the issues. When the regulations come up. You’ll say, hey, that one probably would apply to us because we’ve got that risk. And you’ll have that understanding of what’s going on for you.

Walter Thompson  19:49

Like, the government’s plans for model evaluation tools and testbeds. Like, what even is that?

Laura Bisesto  19:58

I think it will remain to be seen, it’ll probably start as voluntary. I mean, you’ve seen people who are voluntarily joining some of the commitments that the White House has asked companies to join in terms of AI programming, but it’ll probably be in partnership with some of these federal agencies, you know, the US wants to be a leader here. And so they’re going to want partners to help facilitate leadership and make sure the technology stays on shore and or advances onshore for sure. So there’s definitely an opportunity to work with the government, which is more foreign in the US, it’s not as typical as… other places where you might have a closer relationship with regulators, like in the EU or UK. But I think there’s definitely opportunity, especially if you have a unique product that, you know, implicates national security or could be useful. I mean, that’s another reason to pay attention to the regulations. And what’s happening, you may have something interesting to say, that could get you an advantage competitively in regulations, which is equally exciting and good for your business, and I think would definitely appeal to investors.

Walter Thompson  21:05

Based on what I’ve been reading, the Commerce Department is basically expected to weigh in on things like foundation models, and I’ve watched some of these congressional hearings where these senators and congresspersons talk about — they ask questions that really belie their lack of understanding of this technology. And that’s different from the Commerce Department, but from your perspective, is there a deep enough bench of talent in the federal government to actually regulate this meaningfully and effectively?

Laura Bisesto  21:31

I think there needs to be a solid partnership with the private sector here in the US. The Department of Commerce has had great success advocating for US interests abroad, even in the tech space. And I know they’re tasked now with AI labeling and ultimately issuing guidance on identifying general AI generated synthetic content. And including authenticating official US government digital content, like there’s some real national security issues there, no doubt that they will find the way to figure out the best path forward. And there’s definitely the opportunity for private partnerships, particularly if you have a product that you think would be helpful in this space, I think there’s probably that opportunity to, to work with the government. And also, if you want to see a certain type of regulation, that is the way you do your business, you’d also benefit for potentially sharing that as well. So I think there’s opportunities and you shouldn’t shy away from sharing them if you think you have a solution for what the government is trying to achieve. This is what I would say I think people are scared of necessarily working with the government. But there’s definitely a lot of opportunity there. Especially if you have a way of doing things and you want to preserve that way. That’s it’s not a bad idea to share how you do it.

Walter Thompson  22:55

So something just occurred to me. A lot of teams are distributed. So what does that mean, as far as clients and liability, you’ve got data, you’re sharing customer data with someone who’s in Bratislava, they may not be under the same regulations that you’re under, how do you keep everything tight and zipped up? You

Laura Bisesto  23:13

depending on the type of data you’re sharing across countries, there’s different rules that apply. Of course, if you have an employment agreement with someone, you want to make sure that that’s sufficient that they’re, you know, you’re willing to enforce that agreement, you’re able to enforce that agreement. But if you’re sharing data of consumers across countries, you want to make sure you’re following different rules. For example, the European Union has very strict rules for transferring their users’ data to the US and you have to have a certificate from the Department of Commerce, it’s a new one that they’ve just come up with. Or you have to have previously, you could have done it contractually. But there are different rules for sharing user data across countries. And it is useful to be aware of that, depending on what your objectives are, including sharing the data, just with employees, just sharing it across continents is really important to be aware of those issues, too.

Walter Thompson  24:09

I’ve kept the conversation largely positive and somewhat aspirational. Let’s talk about where things go wrong. And the last bit here, I know you’re here at Nextdoor, so things are pretty steady. No surprises, I’m sure. But in the world of smaller scale startups, you’re seeing, what are some of the most common mistakes that you perceive AI founders making with regard to privacy, compliance, trust and safety?

Laura Bisesto  24:33

Yeah, I think it’s the “it can’t happen to me” or just refusing to look at the risks and the bad things that could happen. I mean, cyber is an obvious place that I think everyone can conceptualize not securing personal data of users, or just thinking, hey, you know, the user told us we could use the data for this reason, but we’ll use it for another reason and getting hooked on that kind of lack of transparency and trickery is strong word but essentially Really, it may be perceived as trickery. So just be pretty careful and cautious when it comes to personal user data for sure. And also just really thinking about the risks and how things could go wrong. I mean, you know, we have an election coming up here in the US, there’s elections all over the world this year, I think it’s one of the biggest election years ever. And so there is a lot of a lot at play, and a lot at stake, depending on what your product can do. So it’s good to think about that. And, yeah, just just just think of the bad things along with the good things, even if that’s not the way you often think, it’s important that you do so here. Again, these mistakes can be expensive, and you can get hooked on them too, because they may cut corners, but in the long run, they’ll be really costly. And it’ll be such a pain to go back and make huge changes.

Walter Thompson  25:53

It’s always good to be virtuous. But is it fair to say that mitigating your risk early makes you a better bet for investors?

Laura Bisesto  25:59

Absolutely. I think, you know, you can say that you’ve thought about these things that you’ve you know, you could even say, you know, you took a look at these AI regulations, you’ve, you know, you believe the tea leaves are going this direction, you think it’s really just going to be a privacy thing, maybe. And you’re just you’re going to focus on that. I think that all just shows you’re looking ahead. And you can even say we won’t have to spend this money in the future to go back and re-engineer. We’ve got these, these consumers and our customers like this as well, so that a lot of customers, especially big B2B Customers want to make sure you’re following different rules. A lot of contractual terms ask that as well. So it’s important to be able to say that

Walter Thompson  26:38

Last question: would it be crazy if you have a 10-slide pitch deck, should one of the slides be about privacy and compliance?

Laura Bisesto  26:45

Absolutely. And considering I think that would be a brilliant idea. And you can talk about how trust is something you’ve been doing since the beginning. And, you know, being, you know, trustworthy and thinking about risk and making sure that you’re with all the things going around with their regulations, making sure you’re staying on top of them. And you know, what’s happening? I don’t think that would be unreasonable at all. And, and you can say that, you know, customers want that, especially your big target enterprise. Customers want that, and it’ll pay off in the long run.

Walter Thompson  27:18

Awesome, Laura. Thanks very much for the time, it’s been a great conversation. I appreciate it.

Laura Bisesto  27:22

Thanks so much, Walter. I appreciate it.

Walter Thompson  27:27

Thanks again to Laura Bisesto of Nextdoor for today’s conversation. On the next episode: coming up with an idea for an AI-powered startup is actually pretty easy, but how do you translate your personal vision into something that’s tangible enough to attract a co-founder investors and eventually paying customers? To find out, I interviewed May Habib, co-founder and CEO of Writer, and Gaurav Mitra, co-founder and CEO of Captions. We talked about building a founding team that aligns with your values, how they validated their ideas before bringing them to market, and how to successfully pivot with the support of your investors and your team if or when you need to. May and Gaurav also spoke frankly about the challenges they both needed to overcome after stepping into leadership roles. I really think this episode’s gonna be useful for anyone who’s trying to hone their storytelling skills, connect with investors, or even become a better marketer. If you’ve listened this far, I hope you got something out of the conversation. Subscribe to Fund/Build/Scale so you’ll automatically get future episodes, and consider leaving a review. For now you can find the FBS newsletter on Substack and check out the new YouTube channel with audio of every episode. The show theme was written and performed by Michael Tritter and Carlos Chairez. Michael also edited the podcast and provided additional music. Thanks very much for listening.

Fund/Build/Scale: Breaking in to Enterprise Sales (Transcript)

Here is the transcript (edited for space and clarity) of the conversation between Fund/Build/Scale podcast host Walter Thompson, Maria Latushkin, GVP of Technology and Engineering at Albertsons, and Jack Berkowitz, Chief Data Officer at Securiti.

Maria Latushkin  00:04

If you hit it right, the rewards are plentiful. You get to innovate, you get to figure out the roadmap together. There’s a lot of goodness in this. But you have to put in a lot of energy as an enterprise in order to make sure as you see it through. And so there will always be a very limited number of early stage startups that we would feel we can afford to engage with.

Walter Thompson  00:27

That’s Maria Latushkin, GVP of Technology and Engineering at Albertsons, the second-largest grocery chain in America. I interviewed her and Jack Berkowitz, Chief Data Officer at Securiti, to get an insider’s perspective on how enterprise-level customers buy software and services from early-stage AI startups. The most surprising thing I learned came early in the chat: spinning up a pilot program or a partnership with a startup creates tangible risks for enterprise customers, which means they can only afford to work with a few of them at a time.

Jack Berkowitz  00:57

Because at the end of the day, we only had so much energy. And so we would balance between established companies, and three startups maybe an actual execution. Maybe we were having discussions with others, it was probably two or three at any one time.

Walter Thompson  01:14

Maria and Jack each have experience working inside early stage startups., but their time working as C-level execs at public companies gives them a unique perspective on breaking into enterprise sales. In this episode, we’ll talk about sales strategies, navigating the procurement process, how to run a proof of concept or pilot program and other essential topics. I’m Walter Thompson. This is Fund/Build/Scale. More after this.

Walter Thompson  01:47

Fund/Build/Scale is sponsored by Mayfield, the early-stage venture capital firm that takes a people-first approach to helping founders build iconic companies. The podcast is also sponsored by Securiti, pioneer of the data command center, a centralized platform that enables the safe use of data and Gen AI.

Walter Thompson  02:12

If you could just both say, Jack starting with you, approximately how many vendors do you work with each year that are early-stage startups?

Jack Berkowitz  02:20

It’s a great question. Um, you know, in my last role where we were really encouraging startups to come because we were interested in the latest things in AI and ML, even then we were sort of limited, we probably only had three at any one time coming through the system. Because at the end of the day, we only had so much energy. And so we would balance between established companies and three startups, maybe an actual execution, maybe we’re having discussions with others, but it’s probably two or three at any one time.

Maria Latushkin  03:00

Same here. And the reason being is, whether you are like right now I work for a public company, real large public company, but even when I wasn’t working for a large public company, there’s a lot of responsibility you take on as a buyer, and you want to make sure that you do that well. So there’s a lot of energy, as Jack says, that needs to be put in, in shepherding a very early-stage company, there’s the rewards, if you hit it, right, the rewards are plentiful, you get to innovate, you get to figure out the roadmap together, there’s a lot of goodness in this. But you have to put in a lot of energy as an enterprise in order to make sure that you see it through. And so there would always be a very limited number of startups that early stage startups that we would feel we can afford to engage with.

Walter Thompson  03:53

I mean, it sounds kind of like a partnership, not just a customer-client relationship.

Maria Latushkin  03:58

It truly is. It truly is.

Jack Berkowitz  04:03

I’m sorry. Well, I was just gonna say it’s a two way partnership in a sens  because the startup wants to fail fast. And unfortunately for the executive for the team, failing fast on the enterprise side is probably not the best outcome.

Walter Thompson  04:23

How often are you someone’s first customer?

Maria Latushkin  04:28

Not in the company I’m at right now. Previously, we have been first customers, small companies I was at. And there’s a lot that goes into ensuring that you are safe, first customer and some of the things that you really have to think about and that would be important for the startup to be able to have answers to is how much risk do they introduce. For the person, depending on what it is that they’re developing for the person that is a buyer or the person that is piloting, how easy or difficult is it to integrate with the company, because the more you have to put in upfront, knowing that you’re the first customer, and it’s really more of an unknown situation, you want to make this a smaller decision for the person that is partnering with you. And so, the looser the integration, the less kind of upstart effort it requires, the better the company that being able to demonstrate that the risk is going to be mitigated, there isn’t ever a zero risk, but like to the extent that you can look under the covers, and see how they would help you mitigate the risk, that would be the important parts for us to consider,

Jack Berkowitz  05:52

Yeah, my last role, it was at a Fortune 250 company. We were never the first customer, never; it just wouldn’t hit our profile to be able to even deal with our procurement group and the insurance and the financing needed. What I would say, though, is when I was in smaller companies, five, six hundred-person companies, then yeah, we were happy to be the first customer because we had flexibility to be able to do it as well. And, you know, the notion for me buying at, or partnering at the Fortune 250 company is, “we’ll tell you what, who do you have already?” So if you got 10 or 15, then I’m comfortable, right? So 10 or 15, mid, mid-sized enterprises, before you go to, you know, one of the biggest companies in the world.

Maria Latushkin  06:45

It’s my advice, having been in small startups, my advice to startups would be not to target these really, really large companies, because the amount of overhead a companies that are large, established companies will present this startup out of necessity, not on purpose, but they have to do certain things. And they have to be able to guarantee certain things for their executive team for the shareholders may become too much overhead and may not actually be good at the end of it good for the company. So maybe taking careful who you want to target as your first customers or first pilot is actually really important. Yeah, when the company is quote unquote, smaller, you buy all of the needs that it would have.

Jack Berkowitz  07:33

Yeah, I was just thinking exactly the same thing, Maria. The killer whale hunting, you don’t want the whale to pull you under?

Maria Latushkin  07:41

Yeah. Yeah.

Walter Thompson  07:43

That’s a great analogy. I mean, yeah, that’s a great analogy, because everybody wants to land the whale. I’m getting all this Moby Dick imagery in my head, certainly. So what are some of the consequences? It sounds like you’re saying, you know, an enterprise customer can literally make or break your business, so what does it look like when things go bad? What are some of the consequences for you as a client, as a customer? If things don’t go well, if this partnership isn’t paying off, doesn’t bear fruit? What are you worried about going wrong?

Maria Latushkin  08:13

There’s a multitude of things. I mean, I’m not gonna go into the doomsday scenario, but I’ll just, you know, even on the surface some of the things would be — I mentioned risk, right? Depending on the type of the solution, depending on the partnership, managing risk is an important thing, is that something that can be introduced? Whether that’s vulnerabilities or it’s some other risks to your company that you have to think about? That’s one. Another one is the company’s solvency. If you have a business case, and presumably you were counting on something as a company that this partner will deliver in the case that they are not, what happens to that function, what happens to that need that you have as a customer? That is another thing that we always think about scale. If your pilot goes well, and then you’re trying to scale it to your whole operation, is that something that is going to work? Will they be able to scale with you both in terms of, you know, traffic volume, all of that, as well as maybe geographical needs, like other elements that scale introduces with it? Will they be able to continue to be a partner, or you will your crush them with your needs, like that’s also something that is very important, both for the company because the company doesn’t want to be crushed, and for the buyer, because the buyer also wants to make sure that that, you know, we’re able to deliver with a solution that we’re recommending,

Jack Berkowitz  09:50

And that can come into play, even if it’s a successful pilot. So you run a pilot, you run a POC, and you’re ready to go and suddenly, as a buyer, you’re having to fund the company? Or find people to fund the company. And so it really is a dance as you move forward to make sure that the company is stable and able to grow with the big enterprise. And we had that recently where, you know, thankfully, we were able to help one company get some additional funding. But, you know, in this environment right now, it was an interesting set of discussions, if you can imagine.

Walter Thompson  10:30

But there must have been some clear benefit for you at the other end, if you’re willing to extend yourself that far, I’m imagining,

Jack Berkowitz  10:35

Yeah, yeah, this system worked better than anything that we had seen and fit into our architectural approach. So it was worth it, for us to extend and stretch further than we normally would. Because of the benefit on the other side, for sure.

Walter Thompson  10:55

Jack, in our pre-interview, you said something that stuck in my head, I asked you when is it too early to talk to an enterprise customer? And you said, you know, well, you know, we can be brutal, as far as, you know, data and compliance in our systems and volumes. But you tempered that by saying, “you can talk to us, but don’t sell to us.” So what does that look like — someone’s trying to figure out how to talk to you, how to sell to you, but they’re not ready to do that yet? How do you want to experience customer discovery from your side of the desk?

Jack Berkowitz  11:21

So I’ve been thinking a little bit about this, you know, at the end of the day, my role level and Maria’s level work selling right now. I mean, we’re, that’s part of our job is to sell, right. But we don’t sell by going in and giving a 20-page PowerPoint pitch, we’re pushing and pushing and pushing, we’re selling through influence, selling through the ideas being there. So the conversation is really about the ideas. It’s much more important to us as a big enterprise dealing with a startup, what’s your long term vision? What do you actually see — I don’t care about your vision for making money or the fact that you’re gonna go work remotely, that doesn’t matter to me. But where do you see the technology space evolving? How do you see things evolving? Where are you going to play if things change in a different way? So really, I’m looking for that same discussion I might have with one of my peers, with my boss, with somebody in the business that I happen to be in, or in the technology business technology area that I’m in that conversation, that helps me understand the product. But if you come in with a list of features, and why you’re better than some other company, and then what you don’t do, I didn’t know you didn’t do that. And I don’t even know that other company. It’s more about for me, understanding where you’re headed and how you fit into, you know, a technology landscape that’s changing rapidly. I mean, today’s technology landscape didn’t even exist 12 months ago. And so that’s what I’m really interested in.

Maria Latushkin  12:59

To add to that, I would also say I love what you said, as in terms of the influence. And really this whole selling process being a conversation. As buyers, we understand that you if you talk to a startup we understand it doesn’t it’s not as bulletproof, as in a large enterprise that comes it’s given, we don’t expect that — we do expect vision, we do expect somebody to be innovative and knowing where the industry is going, where they’re going. And that would be something that we would benefit from. The other thing is my advice to startups would be to learn the customer. Unfortunately, too often I get into a discussion and with one or two questions, I understand that they don’t really understand our business, don’t know our business, and can’t solve — or they’re not even close enough to solving the business problems we may have. And that to me feels like the ones that did bother, they stand apart from the ones that actually learn the business. So try to learn the business to the extent that they can, like did their homework, did their research, and are trying to be relevant to us in that conversation. That’s important.

Walter Thompson  14:12

That’s weird, going in totally cold. Doesn’t make sense to me. But maybe it’s a volume game. They’re just kind of trying to hit so many of the people. Maybe they don’t bother to prepare, I don’t know.

Jack Berkowitz  14:21

I think the thing is, particularly the ones that have raised money from venture capitalists, and I, I’ve raised over $100 million as part of management teams myself, you get so wrapped up into the venture capital world, thinking that they’re they’re your buyer, and they’re your customer. And to be frank, they’re not. They’re bankers. Some of them might have actually worked in a company, but a lot of them haven’t. You know, and I literally just hung up from a VC — of course they’re getting information and trying to build things, but your customers are the technologists.To impress the table at your customers, and so you really need to understand who they are, and what’s motivating them. And what the company does way more important than the PC world.

Walter Thompson  15:11

So, domain expertise, it sounds like we’re kind of, you’re kind of dancing around that word, but perhaps  that’s kind of the middle of this, as far as if you’re going to, if you’re going to tell me you’re going to solve my problem, you need to have some understanding, some frame of context for my problem, and like, the causes and so forth. So how does someone get it? Am I wrong about that? That’s a question, I suppose? Or am I making an assumption here? How much domain expertise do I need to sell to you?

Jack Berkowitz  15:37

You know, my last firm, we did a lot with moving data and moving payments, and things like that. And so, for us, you know, coming in and talking about you know, streaming information on public internet is probably not the thing we were interested in, we’re moving systems into bankings capability. So understanding that at a time is important. 

Maria Latushkin  16:06

It’s always, in my opinion, it’s always better to have a successful first client, successful first implementation versus maybe the biggest one, right? And so picking the first one, or the first couple is really important. If I had to do it, I would go and I would try to find out where my chances of success maximized, and having domain expertise, being able to speak with from the point of like, confidence and authority to some degree about the problems that you’re solving for the customer, does put some, you know, winning points for you in in that discussion, in that partnership in that division and gives credibility. So I would work hard on trying to understand what my connections are, how can I get that domain expertise before I show up to that buyer?

Jack Berkowitz  17:00

You hit it, right? It’s about connections. It’s about networking to go find that information. So, you know, find businesses around the company, find businesses that have sold to the company, find people inside the company that can, you know, “hey, I’ll spend 10 minutes explaining to you what this process is, or that process is.”

Walter Thompson  17:24

Even if you’re not a buyer, there’s a stakeholder who has a problem.

Jack Berkowitz  17:28

Yeah, they’re influencing or they may not even be connected, but they just have context and are giving you context as to what you’re selling into, and what you’re about to get into. Even in that process, you may be like, “well, wait a second, why am I getting the idea that I’ve got this meeting with a C-level person, but we can’t actually help them?” You know, do everybody a favor: Don’t have the meeting, right?

Walter Thompson  17:54

I wanted to talk about creating a framework for enterprise product development for AI startups. Maria, my first question for you is, table stakes: What do enterprise customers want or need to hear before they sign with a new AI vendor in this environment?

Maria Latushkin  19:17

AI is especially interesting, I would say that everything that I mentioned before in terms of the ability to scale, the security compliance, all of the areas of “how will we not get in trouble?” apply. In addition to which, I will try to understand I will pay special attention as a buyer and I will pay special attention as the person that could start up it is in trying to articulate what is it that AI does and being able to show to the buyer the risk that it’s done responsibly and the best practices are in place. And that it’s, again, it’s a little hard to answer because AI is a broad term, and depending what it is they do approach I would have would be different. But if I had to like really, really up level it, it’s ensuring that responsible AI practices are in place would have been my number-one concern, as well as security.

Jack Berkowitz  20:23

And you probably don’t need to be the one who invents it all, you know, talking about how you can take advantage either of things in the company’s environment, or you’ve got partnerships with companies that build data governance, or data security, or whatever it happens to be, because you’re adding the specific things. Now, if you happen to be in a data governance product, that’s a different story. But, you know, do the pieces that make sense for you, and clear about the borders for you. The other thing is, one of the big areas that is concerned right now is intellectual property rights, even of the models, right? So OpenAI works great. Gemini works great. All these other things work great, but what are the intellectual property rights of your company? And how do those relate, that would be an important thing  to be understood.

Maria Latushkin  21:23

Add to that, and data as well, in general, all of the data governance, the ownership of the data origination of the data, especially as data gets transformed, between the companies, they, if there is any data sharing, or data creation, between the enterprise and the startup.

Jack Berkowitz  21:41

Remember, the procurement teams are going to be separate from the technical buyer or the business buyer. And in fact, most companies keep it separate. So don’t ask the business buyer, what the prices [are], don’t agree, because your current team is gonna have a different story, they will actually have a structured set of requirements that you’re going to need to meet, or you’re going to need to at least discuss with them, whether it’s liability insurance, if you have people coming on site, or you know, all those other things that are involved in risk management. And it’s best to get a relationship with their procurement team early, you can ask for it, you can ask the business buyer or the technical buyer, “can you introduce me to procurement upfront, even in the first meeting, because everybody knows that’s going to take time?” And I would suggest you do that, because that’s the checklist.

Walter Thompson  22:34

What does that process look like for both of you? I know it can vary, because we’re talking in most cases, with regard to AI startups, this is brand new, or emerging technology in some ways. So how do you kick the tires, and what does that process look like from the inside?

Jack Berkowitz  22:49

For me, we always will assign an individual responsible to shepherd and take the steps necessary for that company to come in. Sometimes there’ll be two people, one person on technical integration, and one more on technology and business evaluation. Sometimes those would be different folks. But there is always one person who’s going to have to be responsible for overseeing it otherwise, you know, in a big company, particularly, you might have 10, 15 people involved, and it will get focused as it moves forward.

Maria Latushkin  23:26

Same principle with the one person for the same reasons. There’s always this double if somebody takes the lead, but there’s always the second person to them. So sometimes maybe there would be a business lead. And there would be the technical lead, who is the second person, but they’re lockstep or vice versa? Maybe it’s a technical solution, but then you really, really ensure that from the finance perspective, the finance leader or business lead, depending on the situation, is there. And then they are the parties that have veto rights of sorts, right? You make sure that from a legal perspective, they check all the boxes from a security perspectivel m,. So there’s, there’s this one stream that’s pushing it through shepherding it, and the other ones that get involved to make sure that there’s kind of no harm will be done, right. So from the legal security and other depending on the situation, other areas.

Jack Berkowitz  24:22

And those groups to startups may seem that they’re trying to block things, but they’re not. Everybody’s in there to move their company forward. But they’re doing their job. And I think getting warm relationships with them as you go is only a great experience because those organizations are never going away as you continue to grow.

Walter Thompson  24:46

So ballpark it for me: how likely is it that a pilot is going to turn into a long-term contract, just you know, generally speaking,

Jack Berkowitz  24:52

In my experience, it’s about 50-50, about half the time the pilots will move forward. Recently, we just had an example over the past year where we did a pilot with one company, it was very successful. But what we found out was, we weren’t ready for them. And unfortunately for them, a second company showed up that we were better positioned to be able to handle. So that company hadn’t been in the pilot, but we never even needed to do a pilot with the second company. You know, the first company  objected, “well, how can you do that if you didn’t do a pilot?” It’s like, “well, we kind of did, it was as much learning on our side, about how we need to organize and what we needed to do.” And it’s unfortunate, but, you know, that was the case.

Maria Latushkin  25:37

The really important part for startups to keep in mind is that the pilot on the buyer side is not to prove our technology, it’s to provide the business model. And most of the time, on the buyer side, they actually are expecting technology to work. There might be a pre-pilot or POC or something you do on the side, etc. But by the time you get to pilot, that’s where, especially for large companies, they expect the technology to work. And it’s for them to provide the business model to prove that it’s the pilot for that company, to see if they can roll it up. To rephrase your question, if the company gets to that stage of the pilot when the technology works, and it’s a question of the business model, and it’s a question of the user experience, or whatever else needs to happen, then I would also say it’s about 50-50. Sometimes another company shows up with a better business model, or some other circumstances change. But at that point, if it did go through pilot and pilot proved to be working well, I’d say it’s probably 50-50. It’s difficult to get to pilot, I would say that out of the number of companies that we talk to, the number of companies that actually that make it to pilot, that’s the smaller number, because very often, you see that there is not a fit, or the tech is not ready, or something else you’re able to see quickly enough before getting into the pilot.,

Jack Berkowitz  27:09

And then as we were talking earlier, the opportunity cost to take something to a pilot, it’s just, you can only handle so much as a throughput in a company at any one time. Even if it’s the biggest company, it doesn’t have infinite resources and attention and everything else. And those people are doing other jobs all at the same time. And so, you know, it limits the number of companies that can get to a true pilot. A POC is not a pilot, a project is not a pilot, a pilot is, “hey, we’re going to instrument the United States, or we’re going to instrument California,” you know, massive places. Scale.

Walter Thompson  27:51

So for runway-minded founders who are looking at their bank balance — I know there’s no single path for this, but how long between getting a yes, to go into a pilot program, to them getting some money out of the back end, realizing revenue from that pilot?

Jack Berkowitz  28:09

In my experience, we don’t really want to have pilots run that long. And so, you know, you might only see a pilot run 90 days, and if they can’t prove what it’s doing in 60 to 90 days, then we’ve got an issue. In fact, you know, well-run pilots will have almost weekly cadence. And so you know, within a few days, if it’s working, you know, it’s important to have your, your sort of first land contracts backed in parallel. In fact, a lot of procurement agencies and groups won’t allow the pilot to start without having that backend agreed. I think startups should realize that land and expand is probably going to be a better way for any company also. So if the pilot has the scope of California, but the company does business around the world, they expect that the first project is going to be California, right? Because it’s easy to just roll in. And then you know, you’ll get later contracts as it goes.

Maria Latushkin  29:18

I agree with everything. And to add to this, I would always ask to the extent you can in the beginning, what the budgeting cycles are like, what does it take in a company to get further steps because I’ve seen being in a startup, I’ve seen sometimes is that you get to verify the pilot, but it doesn’t mean that this is the time for the contract. And it might be that elapsed time when we think about runway elapsed time between pilots. A pilot can be verified within 90 days, but then there might be elapsed time to the contract may be much longer. And it will depend on a variety of factors, and every company will have its own variety of factors. So for a startup working with the company for the first time, I would find that out not to be then put in a situation where I would be really anxious.

Walter Thompson  30:10

Yeah. Awesome. Thanks. The engineers I’ve talked to — just a few so far, but it seems that many of them really don’t like coding new features for a single client. But that’s something that seems probably likely to come up during a pilot program. Maria, is that a consideration for you? And how often would you be likely to ask for something like a special feature that you knew that would benefit you, but not necessarily their entire platform?

Maria Latushkin  30:33

I try not to do that. I try to explain sometimes they would not. Sometimes they are early enough, where they have not necessarily gone through my cohort of clients, clients like me, and I would [say], “you actually should do this, because there will be more clients like me.” I would, unless this is something so specific for our business, that is without which we can’t do it. The whole idea of partnering with somebody is not to have something really esoteric that can ever be upgraded, that’s done specifically for you. It’s to actually create a platform that would be general purpose enough. That’s like, full of best practices versus something that’s very bespoke and esoteric. Of course, there are cases when we actually your business requires it to be something different. But otherwise, I wouldn’t do it.

Jack Berkowitz  31:33

I think Maria, right. Would you agree? I not only wouldn’t do it, I want them to have other clients. I want them to grow their business, we need them to be successful. We need them to grow to hundreds of clients and, and everything else. We don’t want to be the only customer because it just creates a bad situation.

Walter Thompson  31:56

Codependency is not a good thing. 

Jack Berkowitz  31:59

You know, I think it gets into the thing also, like, are you willing to take a call on behalf of a startup? Well, if it proves to be successful, and everything’s going well, yeah, because your best salesperson is going to be, you know, your early customers and you want them to have other clients, you want them to meet other clients, too. Right? You want that group of customers to be really supportive of you. Because it’s in the best interest of the customer.

Walter Thompson  32:35

So in a pilot, in a scenario like this, what are some of the most common ways where founders are their own worst enemy, where they’re sabotaging their own work or the likelihood of success without realizing it? Have you seen people doing this without realizing?

Jack Berkowitz  32:51

Well, the biggest one to me is the dive bomb, or the helicopter founder. You know, the founder who either a has the initial meeting, and then you know, it’s too important for them to go do other things than to be with you every day or, you know, checking in on the board, dive bombing, where the, you know, the the project teams meet, you know, 30 days in or 45 days in, and then the founder shows up and tells everybody that they’re doing things wrong. I think if the executive team and technical team is on a project, and they’re meeting every week, then the founders, particularly early-stage, should be in those meetings. I’ve seen this sort of helicopter or dive bomb, I don’t know what the right word is. I’ve seen it too many times over the past few years, particularly with the AI startups, to be honest with you.

Maria Latushkin  33:53

To add to this, I would also say that founders don’t listen to their customers. They missed them, they missed the opportunity, they missed the mark. And there’s always something you learn from potential customers, current customers just being good listeners. And that would be my advice to founders. So many times, over the course of my career, I would do meetings, but somebody said, “oh, the other ones showed, more promise but this one really understood my needs, and the needs of our business,” … and that would be the company that got the business. And the reverse of it is true as well. Companies that were the farm especially when it’s you know, founders are so important and founders set the tone for the company in the beginning of its journey. If they don’t listen, if they’re not in tune with the actual needs, it’s okay to say no, but it has to be an educated no, it has to be a no that comes after listening. I would say that that’s really really important as well.

Jack Berkowitz  34:58

Yeah, and you can hear the language, to follow up with Maria said, you can sometimes hear the language of a professional product manager or professional founder who says things like, “well, our customers think this. And quite frankly, you know, our customers are telling us this.” And you’re sitting across the table like, “well, I’m the customer. I’m not saying that — I’m saying something different.” And there’s a couple of big Valley FAANG companies where there’s this vocabulary that comes out of them. I don’t know where it’s come from. But it’s really bad.

Walter Thompson  35:36

I’ve literally heard product managers say things like, “customers don’t really know what they want.” So yeah, there’s a certain hubris there. My last question about pilot programs: success fee agreements, what are they, and how do they work in a pilot program to help everyone come out ahead at the end? Do either of you use them in your practice? 

Jack Berkowitz  36:03

Yeah, I’ve used them quite a bit. And so what we’ll do is, is it’s really on the later stage contracts, right, the later stage of things. And what they are, is essentially agreeing to a business objective, or a commitment to a date. And so you know, something like 75% of the money will be under a normal contract, and then there’ll be a bonus. If you hit certain joint objectives now, that means that the company — the customer — also has to be responsible for seeing through their commitments. But if that’s the case, then you can accelerate through some additional monies.

Walter Thompson  36:43

Maria, is that advice you’ve used in these contracts?

Maria Latushkin  36:44

Yeah, it’s something very similar. We’re also ensure that we talked in the beginning of what happens to the data that we exchange in artifacts, etc. In the case, in both cases, actually, whether we continue on on.

Walter Thompson  37:00

Thanks very much to both of you for the time today. I really appreciate it. It’s been a great conversation.

Maria Latushkin  37:04

Thank you. It’s a pleasure.

Jack Berkowitz  37:06

Thank you.

Walter Thompson  37:08

Thanks very much to my guests, Maria Lashutkin and Jack Berkowitz. For my next episode, I spoke to Laura Bisesto, global head of policy and privacy at Nextdoor. We talked about the regulatory landscape facing AI startups in 2024, and how small companies should start the work of developing their own ethical frameworks. We got into how startups can recognize when they need legal help, recapped some data governance best practices, and also talked about why it’s so important to create a buttoned-down process for rolling out new AI features. If you’ve listened this far, I hope you got something out of the conversation. Subscribe to Fund/Build/Scale so you’ll automatically get future episodes, and consider leaving a review. For now, you can find the FBS newsletter on Substack. The show theme was written and performed by Michael Tritter and Carlos Chairez. Michael also edited the podcast and provided additional music. Thanks very much for listening.

Fund/Build/Scale: Fundraising from Both Sides of the Table (Transcript)

Here is the full transcript of the conversation between Fund/Build/Scale podcast host Walter Thompson, MindsDB CEO and Co-founder Jorge Torres and Mayfield Partner Vijay Reddy:

Jorge Torres  00:02

We humans, we are like these pattern recognition machines. And the more you do it, the more the pattern starts to become second nature. Given that there’s so many unknowns and the journey ahead for any entrepreneur, you want to find investors that not only understand it because it just logically makes sense what you’re saying, but they understand it because they’ve walked that journey before a few times.

Walter Thompson  00:29

That was Jorge Torres, CEO and co-founder of MindsDB. Jorge and Vijay Reddy, AI startup investor at Mayfield, were the first few people I interviewed for season one. We met up at Jorge’s office in San Francisco’s Mission District on a rainy Friday afternoon in November 2023. We dived into pitch tactics and investor outreach, but we also spend time talking about the frameworks VCs use to evaluate zero-day investments, which red flags investors and founders both need to look out for, and how to find an investor you can partner with for the next decade, not just the next funding round. 

Jorge has been through the fundraising process three times and Vijay is an experienced seed investor, so I was glad to talk to them both about fundraising from both sides of the table.

Walter Thompson  01:19

Vijay and Jorge, thank you very much for being here today. So today, we’re gonna talk about fundraising from both sides of the table. Vijay, you’re an experienced investor, Jorge, you have raised, how many times?

Jorge Torres  01:54

Three times? 

Walter Thompson  01:56

We’re in a hype cycle, I don’t think that’s a controversial opinion, which means a lot of future AI founders are probably spirit feeling serious FOMO at the moment, I think. And that leads to a lot of people that just want to pitch and get out there as quickly as they can to get their company going. So before you start fundraising, I guess my first question for you, Vijay is from another early-stage AI founder. What is it that really convinces you to invest in early-stage companies? And what can founders do to get to that point?

Vijay Reddy  02:28

So I think I think it’s fundamental, right? So raising funds for an AI startup is like raising funds for any startup. Keeping AI aside, when we look at the teams, I think every fund has its own metrics, which every fund looks at it differently. For us, we start with a people-first philosophy, “is it someone we can back? Do they have the same values? And is this a team you want to go in bed with in for, like, 7 to 10 years?” And so that’s the first item we’ll look at. And we can talk about how we can screen for that. 

And second is, then we’ll look at the markets. Others look at markets first, and people next, but for us, it’s always people-first, and then we’ll look at the market; is it big and growing and a nice, attractive market to go after? And it doesn’t have to be a day zero, right? Sometimes most of our investments are day zero, there are blue ocean, there’s zero TAM, but can this become a bigger attractor? So once we have those two, then we go into the specifics of that particular company. Do they have the right technology? How good is the team? How good is the opportunity? And then we dive into the product and technology. But that’s more on the latter side after we clear the people and the markets filter.

Walter Thompson  03:54

What does that process look like for you, as far as assessing a team? How do you approach this? What are the balances used to kind of get in there and assess their appropriateness for this product or solving this problem.

Vijay Reddy  04:06

So we invest very few deals there. Very, very concentrated portfolio in the sense that every deal matters to us. So we don’t spray and pray right? For us to make a deal work, we need to make sure the team has some attributes, which we look for. It’s not just the founder, it’s the team that can come together. Do they have the product market fit? Can they attract talent? Can the founder attract talent? Does the founder understand the technology? So there’s a lot of different attributes we’ll look for in a founder. And usually in the first half hour we can get a good sense of hey, is this person in the team, someone we want to spend more time with? And when we do we tend to dig in a little bit. But for the first filter when we do talk to them and we try to meet them in person or not. We can still do the zoom thing, but we tend to spend a lot of time on the human filter. And then we spend more time on technology afterwards.

Walter Thompson  05:09

Jorge, for your perspective, what do you think a team needs before they start pitching before they put a pitch deck together? What do they actually need to have figured out before they go into the market and start asking strangers for money?

Jorge Torres  05:21

Yeah, I think it’s to understand that, at the end, it’s  a risk decision, the one that the investors are making, and frankly, speaking, the decision that as an entrepreneur anyone should be making, it’s being able to understand that you’re taking risk, and then you’re taking an opportunity as well. So the most ideal situation is that you are building something that has, or you’re about to embark into something that has a great deal of an opportunity, and then that you’ve thought of all the possible risks that you can control. And therefore, when you present this to the investor, you’re actually tackling the risks that are in their mind. And I think that risks for investors change over the life span of a company. When you’re starting, you have so very little data that the risks are more about, is this group of founders capable of executing what they’re kind of like about to jump into. And I think that that’s something to to your point like that, that human assessment is the most important assessment that they can be making, because companies that die, I think you guys have been doing this for such a long time that you know, that the chances of a company not surviving, because the founder is not being the right fit for the problem for the execution or even within them are very important risks. 

So founder risks in terms of like, are the founders, the right people for doing this, the founders being able to execute because they work well, they don’t have redundancies, you know, like, you can try to understand that this decision from a risk point of view, then when you pitch it, you have to kind of understand that you have that part covered as well. And be honest to yourself as a founder, like, am I going to be in this company for the next 10 years? Can I dedicate, like sleepless nights because it’s going to be hard to be here for 10-15 years? And if the answer is yes, then you know that you can articulate this: Do I have the expertise or the talent to bring people that will bring the expertise I don’t have. So those are the things that I think is one of the buckets. 

But I think that before you even get to the bucket, there is something that is defined not necessarily by you as a founder. And it’s more as, there must be a problem that is so large, so, so, so large, that it must be obvious to you, because you want to dedicate your life to this thing. But it must be obvious when you articulate it as well, it has to make sense to the people you talk to about it, what you’re doing here is you’re telling “look, it doesn’t matter how inexperience I may be because I’m just starting, you know, you have to build the experience in this. But the market is so large that even if I’m not performing 100%, on the solution that needs to get to market, I will iterate fast enough, where I will have enough times to iterate that I will capture a significant percentage of this market.”

Yeah, so this is a market risk. If it doesn’t make sense, from the point of view of an investor, that you’re going to build a business that at least sells $100 million, then all of a sudden the market is not worthwhile the risk. So for an investor that math seems to be very simple. And if you can answer those three things, effectively at the very early stage, then not only two things are going to happen. The first one is you’re going to meet investors that will definitely ride the wave with you because they will likely want to also participate in the solution of that problem. But you will be jumping into something with the right answers. I think that a lot of entrepreneurs, we jump into this thing because we want to be entrepreneurs because it’s an attractive profession to have. But not being clear about these two or three, like specific questions that you should ask yourself and have a very, very concise answer to. It’s a mistake that many of us make, and then until you figure that out, is going to be really hard to make progress.

Walter Thompson  09:36

Following up on that. So just tangibly, Vijay, if I only had — if I was at the ideation stage and didn’t have a demo, and didn’t have customers and only had slides and an idea to share with you would that be enough to pitch you, or do you want to see more concrete things you can investigate before you make a decision?

Vijay Reddy  09:59

I think every VC wants to see as much data as they can have in a given stage to make a decision, right, the more data is good, right? So for late-stage VC, you look at the financial metrics at a cold market, we have a lot more information. at the seed stage, we tend to invest most, a lot of our deals are at PowerPoint stage. And the question going back to Jorge’s is like what are we underwriting, right? There’s people-risk, market-risk, progress and technology risk, go to market risk. So we tend to see how much we can de-risk at any given stage and the valuation and the resources are kind of going hand-in-hand with kind of going back to the risk analogy here, right. So we tend to take less risk on people and market, because that’s fundamental to what we master. 

So if a team is good, if you have a good sense of the market, those are two things we can telll right at the earliest stages. But we’ll have to take product risk, go-to-market risk, we help with idea-market fit, we help with product, we help with hiring and recruiting. So those are risks we’re willing to take at the seed stage. And so we are more than happy, and in fact, we would encourage founders, even if they don’t have a fully structured plan, to work with us. And we can help shape and dive at the seed stage. And that’s part of being a board member and almost every deal, we do take board seats. So we kind of enjoy that part of the journey. So we would typically encourage founders to come in and brainstorm with us even if they don’t have everything set in stone.

Walter Thompson  11:38

I know somebody who’s building now, and she doesn’t even have a front end for the demo, because she has no designer. So she’s trying to hack it herself. But it sounds like you’re saying that that shouldn’t be a blocker or someone as far as like, they could still come to you. And you’ll ideate together I suppose.

Vijay Reddy  11:50

Yeah, I think for the right things, though, right. So we don’t have the bandwidth. Again. There’s hundreds of hackathons, there’s dozens of startups, we can spend time with every one of them. But for special teams, we call it “n-of-one” teams where you have a special sauce, which you know, either, you know the market really, really well. Either you’ve been involved with companies in the space before, or your the world’s leading expert in that particular space. So hat’s how we look at the n-of-one teams. And if we’re building something very unique, very special, and you have a differentiated way of going to market. That’s what we would like to spend more time on just given that this number of hours today.

Walter Thompson  13:52

I want to keep the conversation positive because this is a hard thing to do, starting up a company. But what are some red flags that you see at that early stage that tell you early on, “this is not the right team, this is not the right person.” Generally speaking, what are just the typical red flags that are an easy no?

Vijay Reddy  14:12

So there’s quite a few of them, right? And sometimes it’s obvious, sometimes it’s not obvious. So there are things which have made them successful in their own fields, which might not translate very well to being a founder. Right? So to give an example, if you don’t know who your buyer persona, or who you’re selling to, that’s an open question. And that’s something you can diligence before you don’t have to build a product for that. You just need to have empathy for a customer and should know what you’re trying to build. Right. There are many founders who really liked the technology but haven’t thought about the business plan. They’re extremely — we call them “brilliant jerks” at large companies that are extremely good at individual contribution, but that’s not a good skill set to start a company. There are some founders who don’t know who the competition is. And these are things which you could have done homework before. So there’s a lot of this nuanced way of how, as, as investors, we’ve seen so many companies, and we tend to pick up on those if not any homework or not in a good listener, right. And sometimes we meet people across different areas, a spectrum. But in most cases, we tend to look for outliers, right? So if you’re brilliant at something, and if you can go build a team, which is very differentiated, and those are things to look for, so we’re still looking for people who are exceptional in some category.

Walter Thompson  15:45

So flipping that a little bit, as a founder, what are some red flags that as a founder make you not want to work with an investor?

Jorge Torres  15:55

I think that now after doing this for some time, for us, what has worked is to look for investors that have done investments that can add value, because of the experience that we had before. For example, we humans, we are like these pattern recognition machines, and the more you do it, the more the pattern starts to become a second nature. Given that there are so many unknowns, and the journey ahead, for any entrapreneur, you want to find investors that not only understand it, because it just logically makes sense what you’re saying, but they understand it because they’ve walked that journey before a few times. And this type of investor will also get very excited about what you’re doing, because they know it, the more an investor knows an industry, the more there is this affinity, this click that happens when you meet them. 

And when that click doesn’t happen, you have to ask yourself, “is it because there is no experience from the other side in what I’m doing?” And therefore, you should be cognizant that every minute that you have in the day is a minute that you’re not going to be able to take back. So every minute that you’re talking to the wrong investor, you’re just barking up the wrong tree. So understanding the people that have the experience, to guide you through the challenges ahead, is what you should be looking to. And therefore when you meet people, and you’re just essentially realizing very quickly that they just don’t have the experience on the industry that you’re about to jump into, or that you have been working on, then you’re probably you know, all money is green as people say, but you need to guarantee that money comes with a lot of value. 

And that has been the trick for MindsDB; like, when we have gone fundraising, after we understood that there are investors that have done very similar investments to what you’re doing. And they’ve had incredible amounts of value, like 30 minutes talking to them will be six months of you like spinning wheels. That’s what we want. And when it’s the opposite, it’s more like, “I don’t really know what he’s talking about. But you know, seems like the market is moving that direction. So I’m gonna throw money this way. It’s okay to add investors, depending on the value that they add. They may add network, but you don’t want to make them the main investor. 

Walter Thompson  18:18

Unike Vijay, most VCs are not former R&D engineers, right. But with a lot of experience, technically. And so I imagine there’s a lot of investor education involved with trying to get an AI startup funded. Is that something you had to do? How much did you have to work to educate investors about the value of what you’re trying to produce? Or did you just find investors who understood immediately?

Jorge Torres  18:43

I think that it only got really well for us, like everything started to get crystal clear once we started talking to investors, where we were speaking the same language. And then once you do it a few times, you learn very quickly to make that discrimination. That doesn’t mean that other investors that don’t really have the experience on their bags are not valuable. I think that you can then strategize how you build around a little bit differently, you first find these people that they’re just going to add a lot of value on top of the money because of the experience that they have. And then you’re going to build relationships with people that make them useful down the line. Yeah. And then when it comes to making the decision of who you bring into the round, then you pick the best of the best.

Walter Thompson  19:39

Everyone always wants to know about pitch deck how-tos or a magic formula for what needs to be on a certain slide and so on and so forth. But it seems like what Vijay was saying before is that getting funding for an AI startup is more or less the same as a startup; there’s some specific problems you have to solve and address and think about it. So, if I asked which slides are most important than an AI pitch deck, how would you answer that?

Vijay Reddy  20:07

I think it depends on what kind of industry they are after, right. It’s enterprise sales, open source. So some caveat in that with a more generic answer. But we would like to see the team and the market first, defend the center, if it’s the right team, going after the right market, and then trying to understand a little bit more about like, Who is the person you’re gonna sell to? Or what do they care about, I think then product, and then you go into the tech, and then finally, the competition everything else afterwards, right. But a lot of times people spend the first 10 slides on technology. And that’s really interesting, but as a secondary effect. First try to understand like, do people care? Will they pay for this and does it work? I think going through the sequence, and then talking about the AI would be really helpful. But if you’re an AI specific company, and they see too much of like the AI upfront, and that’s good, but usually ask the question like,”how is AI helpful?” Like it’s a tool in the toolbox? It’s not the and not.

Walter Thompson  21:20

A lot of founders I’ve talked to seem to have a lot of mental blocks or cognitive dissonance around calculating their total addressable market. For an AI startup, is there anything different or special about calculating TAM? Or is it still the same kind of traditional bottom up approach?

Vijay Reddy  21:37

I think a lot of times TAMs don’t exist in some use cases, right? I think you need to figure out, what can the TAM be if the market forces align right, I think, said a lot of cases when you look at the translation market, we’re just talking about this before, the software market for translation is not that big. But then if you take the human capital market, it is a $20 to $30 billion market. So then given the time very differently, than if we’re selling a software into translation company, right? So knowing who you’re selling to and how we can charge for it will help you address the TAM for a founder, a first-time founder. But for us, I think large markets, which are attractive and can support margins tend to have better outcomes then maybe larger markets don’t have margins or small markets which can go into large markets. So there’s some markets we stay away from because it doesn’t fit the profile for us. But when looking at a TAM, it’s good to do a bottoms-up and a top-down and just extrapolate to see what makes sense. What doesn’t make sense.

Walter Thompson  22:39

Jorge, if you were doing a pitch deck today, and you are a first timer working on your TAM slide, who would you show it to before you showed it to Vijay? To check your math and make sure you weren’t just totally, you know, out over your skis?

Jorge Torres  22:53

So as many people as possible. I think that is more than the order in which you show it to people. I think that investors, also their time is money, right? Like the amount of time that you haven’t days limited. And you don’t have that many kind of second, third choice, or shots with them. So what you want to do is you want to identify what are your most ideal investors, and save that to, once you’ve had feedback from the people that you know are not necessarily your most ideal investors, but they can give you feedback on those very initial things. Because every investor will know, if you’re far away from something that makes sense. If you’re close to something that makes sense. So, to be more precise, don’t wait too long to show it to an investor. It’s just that there are so many investors out there. And you can always strike and start with or like, well, here, I’m just spinning wheels to understand, you know, where the traction is happening.

Walter Thompson  24:02

In an idea-stage startup, there’s no social proof to validate your idea. We touched on this a little bit as I suppose but like, can you give some granular specifics as far as what are those tangibles? Like what do they look like when they’re actually like, oh, there’s a market exists for this, like, “even though I don’t know what the TAM is?” Like, what would that look like for you exactly as an investor?

Vijay Reddy  24:26

At this stage, in our AI Start seed fund, we don’t have Gartner top-right quadrant startups. There’s no Gartner quadrant in most of them, right? We don’t have in some cases, the TAM is not defined yet. The categories are not defined yet. And so what we tend to look for is, is there a buyer out there or customer enterprise, who has a really strong pain point, not a nice-to-have, a must-have and is the startup solving them? And we tend to usually do when you do reference calls, we tend to not look at how much revenue if the customer is charging or what the sales cycles are, but it’s more like, how big a pain point was that, and —

Walter Thompson  25:09

— this is the painkiller/vitamin mindset.

Vijay Reddy  25:13

That’s right. And also, how valuable is it for that particular user? So I think narrowing down on who your target buyer persona is, and then finding so much value, not one and a half x, but 10x. So there’s some, there’s lots of founders who really hone in on that and build a 10x better product. And that’s a good validation for us. And if it’s a larger company, and they see a 10x value, that’s even better.

Walter Thompson  25:44

It seems as though major AI players are commoditizing different products quickly, if OpenAI updates their product roadmap, that could create an extinction level event for the wrong startup. How are founders dressing this?

Vijay Reddy  25:56

So I think that’s recently, we’ve seen some companies where they’re trying to build products, which are built on top of other companies’ product lines, and there’s not enough differentiation if that company they’re relying on actually builds that. So for example, if you look at Slack, or Zoom, they have mass market reach. And so they have distribution. And they have data on which the startup is supposedly building a differentiated product. Now, the question you ask yourself is what happens if the companies that you’re relying on add a feature which, which is makes logical sense for them, right, and, and each time Microsoft comes up with a different feature, or Slack or Zoom, a lot of companies have to pivot really quickly, which you could have avoided, if you knew that you were in the line of fire. 

And so I think some founders are really good at understanding that “my core strength is in understanding the customer side of things, and I want to go and use this product in a very differentiated setting,” that’s okay. But if we’re just building a consumer product to go against Microsoft Word, using an AI bot, and if Microsoft adds that feature within the core product, your business has an extinction-level thing. So lots of founders are very good, I think, as Jorge mentioned, we know startups pivot, and that’s one of the things we’ll look at is how, how savvy are they to see market forces and then pivot their business? Well Ahead before they install it.

Walter Thompson  27:47

So if you are an early-stage, if you’re a seed stage idea-stage AI startup, how do you dig a strategic mountain at that point?

Jorge Torres  27:55

I think that the earlier you are, you shouldn’t be bought into a solution that strongly, because the solution is likely going to change, such as your understanding of the problem. I think that therefore, it is more important to be focusing on, “is this the right problem to be solving?” Moat is something that starts coming once you get enough data about the problem to then understand, okay, “what are the players that are working on this problem? And how am I going to identify Is there a cap here that I can get into, and that can be first player? And if I’m not the first player, then how are the people solving it inefficient, and I can solve it 10 times better, 100 times better?”

But if you don’t do that exercise in that order, you may be at the risk of solving a problem that either is not that big, a problem that already has players that can again turn you into an obsolete feature if you if you don’t do all this exercise in this kind of order. So the problem is the most important thing at the very early stage. Moat comes when you understand the problem, and you understand the players of the problem and their solutions. And then you understand the gaps. And if there’s a gap that allows you to be the first player, then your moat is to be always on the forefront. And if there is no gap, but there is just like, very, very bad solutions to the problem, then your moat is that you’re 10 times better or 100 times better than what is there to solve a problem.

Walter Thompson  29:51

Are technical founders better off with a nontechnical partner?

Jorge Torres  29:56

100%. I think that you will soon realize that a company is a symphony of many different instruments. You don’t go to a symphony to hear just one single instrument played by 20 people, you want to guarantee that even if there’s like people that have the same instrument that they’re playing different parts, but at some point, you need to add other instruments. Being very aware that a business is a combination of reading the market, going after that market, and then being able to build a product that can deliver. It’s a good recipe for success. 

And also, it’s a good recipe to understand that maybe those were there is a team and  one person has tendencies to be more driven for business-like operations, and then someone that has a tendency to be more technical, and to put together a solution — these stories can repeat themselves, like Apple is one great example of those, but you keep seeing very successful companies. And even if it’s not out of the founder’s states, you will assume that very early, these teams add someone who will complement one or the other.

Walter Thompson  31:15

Based on your own personal experience, what you’re seeing anecdotally, around how long is the typical fundraising journey these days from going out into the world with a pitch deck and then going home celebrating over a term sheet? What are we seeing as far as average timeline, roughly? Or is there an average?

Vijay Reddy  31:32

I think it’s a very wide range, right? Some companies can raise quickly, if they meet the right co-founder, they have product- market fit or idea-market fit, it’s fairly quick. In some cases, it’s longer, I think it’s, it’s less of a concern, if it takes a longer time, it’s finding the right partner that is more important. So even if it takes you longer, I would suggest looking for the right partner. And when I mean partner, it’s not the fund: it’s the actual people within the fund also. And it’s a huge range. within larger and larger quantities, this is people who will probably want to partner with these people who have completely different philosophies. So let’s say, trying to find the right person within that fund is as important as finding the raising fund itself. So it’s not a race in many ways, but at the seed stage, find the first set of founders who could be who have your back end have the same shared values.

Jorge Torres  32:38

Yeah, I think that one story that’s almost telling me that I think that is relevant here is for an investor, the clock’s start ticking from the moment that they make the investments. So it doesn’t really matter what happened before. In the sense of, if it took you some time to get to that point where you’re ready. The investor only cares like you’re ready now. And from now on, the clock is ticking. Therefore, what they’ve been looking at is more like, what is the vectors of growth that have accelerated in the past few months? If it took you something before that, a while even to figure this out, it doesn’t really matter that much, because their capital was not ever, like waiting there for something to happen. Therefore, my observations are these deals tend to happen very quickly once things are starting to move very quickly in one vector of growth in your company, because all of a sudden, there’s an inflection point. That means that you figured out something that makes your opportunity less risky. And therefore, when an investor sees this, they also understand that the opportunity for them has a limited window of time, because if they don’t get it, someone else will. And that’s the best type of view. An investor doesn’t want to be the only investor interested in a company, because you rarely find gold that nobody else sees.

Walter Thompson  34:05

And last question: I guess typically, for let’s say, a B2B SaaS startup, maybe 18 to 24 months of runway is the recommendation. If you were launching an AI startup today, in November of 2023, how much runway would you want after you closed your first round of funding?

Jorge Torres  34:24

I think that for me, it’s important to translate that into risk. So if you think that being concerned about money will deter you from making the right decisions, then you need to raise for the path of money that will guarantee that you can operate mentally. I think that there are entrepreneurs who are okay with 12-month runways and they’re cool as a cucumber. There are other people that cannot operate very well when that stress is upon them. So as a decision of risk, is more of, what will guarantee that you can succeed, if where you succeeding is, “I’m okay, so long, I have 12 months of runway, I’m okay, so I’m gonna have 24 months of runway.” 

And I think that that defines the behavior of a company, you start raising when you’re getting closer to that length. It is important that any round that you raise, in my opinion, has to be raised because of an opportunity, not because of necessity — it never goes well. So you have to guarantee that that timeframe that you have, is not putting you in the necessity for your own personal thing. Again, there are people who are okay, with very short runways, they manage to do it. And that’s fine. There are people that are not. So it just really depends on how you can operate a team. And again, when you’re early on, you may be okay with this, like six months, 12 months, 24 months. But as you start to have other people on your team, it is very important for them to know, “well, if I’m going to join six months on the road, I don’t want to be sweating bullets with you.” So different stages of a company also make that difference. And it’s important to be well capitalized, because it gives the people are going to join you that have the option to join somewhere else as well great awareness that they’re not going to be stressed for that that thing that is not the thing that they signed up for.

Vijay Reddy  36:25

The best time to raise capital is when you don’t need the money, and so at the seed stage, there’s this is notion from founders and VCs, that there’s a clock, it’s get 24 months and keep raising. It’s not right, I think, at the seed stage, you’re building a team, you’re getting a product to GA, you’re selling your first set of products to a customer, and then you realize maybe you have to pivot, right. And so you have to plan for that. You don’t want to learn from the get-go because you have an 18-month clock. But you have to plan appropriately to the risk you’re taking. And most founders don’t realize how many times you have to pivot before you get to a product-market fit, and that’s okay. So I think having enough capital to make those pivots, and not having to worry about doing bridges — it always takes longer than you think, to go get that first product-market fit. So I think having enough buffer and not being forced to go raise because your peers are going and raising at a faster cadence and usually see this. There’s three or four companies. This seems like a race, that if I raise quickly, and I keep going, I can grow faster. But you might be growing faster in the wrong direction and maybe going after the wrong customer persona. So I think being deliberate about which market you’re going first and then trying to add fuel to the fire once you know, it’s actually a better approach than just raising because you can.

Walter Thompson  37:59

Vijay, Jorge, thank you for a fantastic conversation. I really appreciate your time.

Vijay Reddy  38:03

Thanks for having me.

Jorge Torres

Thank you.

Walter Thompson  38:08

I’ll be right back with some show notes after a word from our sponsors. 

For the next episode, “Breaking into enterprise sales,” I interviewed Maria Latushkin, GVP of Technology & Engineering at Albertsons, and Jack Berkowitz, Chief Data Officer at Securiti. 

Maria and Jack are experts in enterprise sales. Both of them have years of experience working inside early-stage startups and buying software for Fortune 250 companies. 

 

What My Sports Movie Heroes Have Taught Me About Teamwork and Life

83 movie poster horizontal

As we get ready with the popcorn to watch the red carpet and the Oscars, where Oppenheimer is going in for the win, I got to thinking about sports movie heroes who have inspired me. Besides the hockey coach of Chak De! India, some include the boxer from Rocky (Eye of the Tiger is my anthem song); the father of Serena and Venus Williams from King Richard (Serena and I served on the Poshmark board together); Michael Jordan from The Last Dance (I’m a huge Warriors fan who had the honor of hosting Steve Kerr for a fireside chat); and of course 83, a movie about my favorite sport, cricket, which tells the story of how captain Kapil Dev led India’s team to their first World Cup win in 1983. The movie captures that experience, and having enjoyed the privilege of meeting him and becoming an ongoing friend with weekly interactions since then, here are some learnings from the movie but also from my personal interactions with Kapil.

Kapil Dev Navin Chaddha cropped image

Serena Williams Navin Chaddha cropped image

Steve Kerr Navin Chaddha cropped image

First off, for those who don’t know cricket, it’s similar to baseball in that you have players who specialize as batsman (hitter) or bowler (pitcher) and everyone is a fielder. The main difference is that the game used to be played over five days which has now evolved into one day and half day matches. 

  • Kapil sets the bar high by announcing at the first press conference in England that they have come to win the World Cup, a feat that seemed impossible given their underdog status, lack of funding, and the demotivating racial discrimination by the Western media who mocked them as having come for a paid vacation;
  • Kapil creates a confidence cult for the team by repeatedly saying if you taste success once, the tongue will ask for more, and reminding everyone all the time that we are here to win;
  • He was empathetic to teammates for example to one whose fiancee had broken up with him minutes before an important game;
  • He leads from the front and plunges in as a batsman when needed (goes on to score a record 175 runs while his strength is as a bowler);
  • He takes the critical catch of the world’s best batsman in the final which clinches the championship – but the enduring image is that of the team win;
  • He was captain cool who kept his calm demeanor amidst unfavorable circumstances and always demonstrated a fighting spirit to win against all odds;
  • He is an unapologetically authentic leader who always demonstrated humility (he allowed his team members to make fun of his heavily accented and broken English in the movie) and having met him in small and large gatherings, I know that he brings his natural self to every interaction;
  • He created a safe, friendly and fun atmosphere in the players room off the field. The team used to banter, make fun of each other, but be supportive of one another which allowed them to be friends on and off the field and share their personal problems openly;
  • He was always approachable as any player on the field could go up to him and offer advice and he would listen;
  • He had great ability to handle criticism and did not react to reporters or fans. He advised his team members to be calm, not react and the let their play in the game to do the talking (i.e. demonstrate results);
  • He is dedicated to helping others – twenty years ago, Kapil founded Khushi, a nonprofit that helps children stay in school, which has transformed the lives of 1.5 million women and children.

Fund/Build/Scale: Tapping into the AI Developer Community (Transcript)

Here is the transcript of the conversation between Fund/Build/Scale podcast host Walter Thompson and Ozzy Johnson, Director of Solutions Engineering at NVIDIA:

Ozzy Johnson: Some things we’ve talked about a bit earlier is how you don’t necessarily need to be a fully technical founder. You don’t need to have that background because AI is enabling so much in the way of, again, anyone who can solve problems. Anyone who can think in a structured way can be to some degree, a developer.

Walter Thompson: That’s Ozzy Johnson, Director of Solutions Engineering at NVIDIA. In his role, he’s a bridge between the company’s internal product teams and its global developer community. The team he leads also offers technical guidance to NVIDIA’s Inception program for startups. 

We talked over Zoom about where early-stage AI founders need the most help and how people from academic and research backgrounds more easily shift to an entrepreneurial mindset. And we also spent some time exploring strategies for nurturing a successful AI developer community. He also shared some thoughts about balancing initial spending, with the need to drive early growth, and which trait successful AI founders have in common. (Spoiler: they aren’t all developers.)

Welcome back to Fund/Build/Scale. I’m Walter Thompson. I am talking today with Ozzy Johnson. He’s Director of Solutions Engineering at NVIDIA. Ozzy, thanks for being here. 

Ozzy Johnson: Thank you. Glad to be here. Looking forward to it. 

Walter Thompson: Based on what you’re seeing: developers who are trying to turn themselves into early-stage AI founders, where does that cohort need the most help initially?

Ozzy Johnson: The thing I think about most there is really a notion called fundamentals. I see when a lot of people are founding, they get really, really determined, really focused on a vision, or maybe a particular clever idea that they miss out on these fundamental habits that are required to get there — how to really execute how to create a valuable, saleable, differentiated product. 

And a bunch of that is, in a way, is not exactly the fun part. It’s not the visionary work, it’s just sort of showing up. And in doing what can sometimes feel like mundane iteration day after day to get gradually better, that’s actually going to get you to that goal to to realize that vision. 

Walter Thompson: Do you meet many founders who are not developers? I mean, it’s one thing to contribute to a project, but transforming that into a profitable business is something else entirely. So how hard is it to make that transition? And how do you see people making that shift in mindset?

Ozzy Johnson: Yeah, yeah. So I do, I do definitely see founders, who are not developers, you know, the very typical classic founding duo, CTO, CEO, CEO may not be a developer, sometimes they are. I think, though, in modern times, this is increasingly rare. You know, code generation has made development extremely accessible. And it’s really a matter of just having structured thinking and problem-solving more than knowing a specific language or framework. Really, the transition from taking a project to a product can be quite hard, but I don’t think it has to be. 

I think the fundamental difference there is that when you’re defining a project, you’re essentially finding your own criteria for success. It’s like, what do you want to do? What is your vision, whereas a product success is absolutely and ultimately determined by the market. So those are a bunch of factors and things that you can’t control the chapter, observe the chapter, listen to and adapt. 

Walter Thompson: So, from your perspective, you’re saying you don’t need a deep bench of AI machine learning talent on board to put together an idea and approach an investor?

Ozzy Johnson: No, I don’t, I don’t think you do. But you do need to build something, right? I tie back to what I was saying earlier about good ideas, that you’re not likely to be particularly popular if you’ve got the idea. and you’re looking for folks to realize that the world is full of good ideas. The multiplier that really makes something successful is the execution. 

So at the very least, you know, with these enabling technologies, you know, go out there, prototype it, build it, demonstrate what it is, and then, you know, use that to recruit the folks that can refine it, they can scale it, they can extend it. I don’t think there’s, there’s much of any reason in 2024, for not being able to rapidly get to that prototype, you know, that’s not necessarily going to be your saleable, you know, scaled production product. But, you know, you should be able to build something.

Walter Thompson: Most of the founders I’ve come across so far since starting this project are coming out of academia and research, which means they don’t have a lot of fluency with bizdev, and sales and marketing, or building a brand. But VCs tend to say the best storyteller on the founding team is the de facto salesperson. What’s your perspective on this?

Ozzy Johnson: I actually really strongly agree with the spirit there, right? I think that having a story is absolutely essential, and being able to tell that story really concisely, in a way that resonates with, frankly, different audiences and people is essential. You need to be able to tell that story, both to folks who are potentially going to invest in you, you need to be able to tell it to your customers, and depending on who your customers are, you might need to be able to tell it to line of business leaders, an executive, an engineer, you know, a practitioner, an end user. 

So you have to be able to just be really dynamic. For that reason, I think the person who can really weave and refine that story doesn’t necessarily have to be the one who goes around telling it. And ultimately, with all of this landing, whether that’s landing your funding, landing your customers, is something that involves a lot more than just creating or just telling the story. So kind of overall, that story is absolutely necessary, but it’s not sufficient.

Walter Thompson: Which leads into my next question: if you don’t have that skill set on the team, where do you start looking? I mean, you can always look on LinkedIn to find somebody who has experience with enterprise sales. But that seems like a really general approach.

Ozzy Johnson: Let’s sort of take that in two parts, right? Where to find people initially, yeah, it absolutely could be a developer community. But I would kind of warn against going and treating that like, you know, a direct recruitment effort or job postings, unless, of course, you know, it’s a community that kind of welcomes that sort of thing. There are places that do monthly or weekly threads about, you know, looking for help, right, trying to, for exactly this purpose. But if you’re not dealing with that, and say, you are like a non-or less technical founder, and you’re looking to pull people in, or the other way around, go be part of a community just have conversations. 

I think it’s really a common mistake to think about. Recruiting and building a company is something that’s transactional. When you’re joining a company, when you’re creating a team, particularly a startup, you know, it’s not a transaction, it really is a collective relationship. And it’s a journey: you want to know the people that you’re going on with, you don’t want [someone] who just responded to an ad. The kind of second part of that is that there’s real discipline in, say, enterprise sales is very different from, you know, going and marketing a product that is looking to scale and be direct-to-consumer. 

That’s really a matter of timing of knowing if that is the market you’re going after, and if you’re ready to do that, you really want to try to bring in the folks that have done it before. But even in that case, again, you know, you don’t want to make a transactional, you want to try to have that conversation, start that relationship, and grow from there.

Walter Thompson: Pretty much everyone I’ve talked to has emphasized how critical it is to start digging a moat early. but is there such a thing as doing that too soon? From the outside, it seems likely that a team will need to pivot at some point, or maybe not pivot, but continually iterate. So can you carve too deep a moat too soon?

Ozzy Johnson: I think it depends on the type of moat, right? Like some of it is just implicit, right? You can’t, you can’t leverage something that is built on you know, locked in or network effects until you’ve got the user base to really support that, otherwise, you’re just adding friction to growing it in the first place. So to kind of run with the notion, if you’re digging the moat before the castle was built, it’s just putting you on an island. That may not be that interesting to begin with, and this whole thought I really tie back to a bit of what we were talking about earlier with fundamentals and storytelling. If you know why you’re doing something, what sort of information went into those decisions, how you’re different, and really what you expect to happen, then you’ve really got everything that you need to know, not just to start, but to kind of, you know, feather the throttle there. 

So, yes, start digging early, and speed up, slow down, or change the route based on that new information. And that sort of loop is what I am talking about when, when I’m saying fundamentals — just sort of day after day. What are we doing? Why are we doing it? How are we different? Do we need to speed up? Do we need to slow down? Do we need to change course? If you’re doing that, I think your moat is going to be fine.

Walter Thompson: Given that we’re in the midst of this hype cycle, do you think enough people are really spending enough time with the customer discovery process? Or are they just kind of rushing so they can bring something to market because technology moves so quickly? Is that OK, or is that a problem?

Ozzy Johnson: So I think it is fundamentally a problem, if it’s something that you’re that you’re not doing. I think when things are moving fast, you do kind of have to, you know, keep your head on a swivel, right? You need those loops to be to be short, or at least short or shorter. But I do think this is something that can be missed, to literally just talk to people and understand where they’re challenged. 

One of the things that I think about a lot with this is very often the thing that is most valuable, that is most saleable to folks, the things they will buy? It’s not the things that they are not doing now that you are potentially going to introduce them to. It’s the things that they have to do that they are doing now, but they find kind of miserable, or are so important that in a way they can afford to do them well or not do them well. They can afford to, you know, do this with people in a way that’s really arduous. It’s really manual. 

And if you’re finding a problem like that, you’re solving it, you’re making it better, you have you have gold there. If you’re not talking to folks, you don’t you don’t know what they’re really, really doing. And you could be solving a problem that feels interesting and feels clever to you. But isn’t actually something that anybody is looking for or isn’t necessarily going to benefit from.

Walter Thompson: Personnel costs in an AI startup seem like they’re usually the largest expense. But R&D is pretty expensive, as you know. Investors and founders, they both want to scale quickly, but can you share some advice and how to balance initial spending while driving early growth? My sense is that a lot of founders were really happy to spend on tech, but less so on software, like you know, people, that kind of thing.

Ozzy Johnson: This is a huge topic. So I’m going to try to take just a small piece of it or a few aspects, right, but what I would prioritize is what I think is kind of most important here. So kind of the first part of this, the I would say just practice looking through or looking at costs through several lenses, I think it’s really easy to fall into a mindset, that one category of costs is good or bad, or strictly preferable to another.

For example, it definitely resonates with what you say there about a lot of attention being put on personnel costs, but a true gem of a person is going to return a huge multiple. So, right, you want those folks you want to spend on them. The second part of this is really putting your resources, whether they’re direct or indirect costs, into what I call saleable differentiation, like, really, how are you different? What can you sell, as opposed to say, plumbing or things that could be real commodities there. And that can also be really about enablement, as well, to tie it back to the first point, it’s one thing to have a gem of a person, but you might need structure around them, you need to enable them, you need the infrastructure that’s actually going to get the most out of what they’re capable of. 

And this too kind of goes back to the same big idea earlier, that it isn’t just about the idea. It’s also about the execution there. So yeah, I’d say, always just look at these things, not as buckets, but as an overall number. And what is that number turning into, in terms of value, you can sell, if you can’t tie those things into some expected value for your product for your growth in a relatively direct way you really shouldn’t be doing.

Walter Thompson: What are some of the top traits — it’s a hard question to answer I know, because there’s no checklists for who is a good AI founder. But if we were looking back at founders who you’ve come across who successfully launched their own open source projects, whether they are independent or VC-backed, what do they all have in common? Is there a common thread that connects these people?

Ozzy Johnson: I would certainly say there’s some, I don’t know if it would necessarily be specific to open-source projects, but just sort of successfully founding in general, I do think you have to have a certain amount of hubris and kind of unrealistic belief in yourself, right? Because you are doing something that is necessarily hard, you’re doing something that’s truly innovative, it’s not something that has been done before. 

So that’s almost like a bit of a baseline there to have that. Confidence, though, again, that’s one of the things that is common, and I think necessary, but it’s not enough. Because if you are going directly at some goal, not necessarily executing, it’s not enough just to be motivated. So these folks also are going to be intensely reflective, right? Because this is getting into that iterative loop that you need to succeed. And it’s also the point where you might need to pivot in terms of your product, or that you might need a different team, because the folks who can build the thing, initially are not necessarily the ones who can sustain it or accelerate it. So I’d say it’s, it is a really important balance of confidence, and reflection, and agility there, right? Those, those are probably the three things.

Walter Thompson: Given where we are in this hype cycle, are you seeing people just kind of launch interesting projects to put themselves on the map? And is that a viable strategy?

Ozzy Johnson: Say it’s viable, but it’s not really sensible, right? If something’s viable, it can work, but generally the thing that or at least the way I try to think about this, I want to do the thing that is most likely to give myself the best chance of success. So, you know, really creating a project for the purpose of getting on the map is like, what’s the goal there? Wouldn’t it be far more efficient or just more sensible to make a real product that solves a real problem? 

If you’re making a product for press or for notice — if that’s the goal that’s driving it, I just have to question whether that is really going to be representative and useful. Why not spend that time literally solving someone’s problem? And right there, you’ve potentially got your first hook for your first product. 

Walter Thompson: What is your role with NVIDIA’s Inception program? Give us a brief overview.

Ozzy Johnson: My team sits here in developer programs. Inception is one of the major parts of the dev program, essentially, it is our strategy for startups. So the way my team works with Inception is really learning from what’s out there in the market by working with startups, if there is something that many startups are trying to do, we want to learn from that. 

We want to understand, you know, what is difficult to adopt, what is really resonating with them, what’s going to help them build the next thing, because ideally, we want certainly all the most successful startups to be building on our platforms to be using our stack. And really, the best way to do that is ensure that they all are. And the way we can do that is to know what they need to have those things ready. And to support them in a way that really scales and again, provides value. So yeah, it’s a whole loop we learned and we try to then provide examples.

Walter Thompson: I’ve talked to a couple of people who are students at this point who are interested in starting up. And one of the things that they’ve come back to me and said a couple of times is that they’re looking for a place where they can see what other people are working on and share what they’re working on, but in a kind of a non-competitive environment. Is that any aspect of what you’re offering?

Ozzy Johnson: There’s certainly places for that, you know, also in our developer program is access to our community forums, there’s all sorts of discussion there. Through Inception, we do highlight the work of our members, we’re always welcoming folks who want to talk about their solutions, built with our tools, built with our products, [they] can publish those things through some of our blog platforms. And that is a really great way to do that, it gets you to a large audience. And then, of course, the folks that are consuming it are seeing how, you know, others have been successful. 

We also organize a certain number of community events as well. Generally, we might be talking about a particular technology there that is new for us that we think may be helpful, interesting, etcetera. But it’s also time for folks to just mingle, share experiences, you know, talk with folks from my team, potentially others who are in attendance. So, yeah, this is absolutely one of the things that the program facilitates.

Walter Thompson: Does this also include, I mean, just not to be mercenary, but can you facilitate connections with investors or help someone connect with a potential customer?

Ozzy Johnson: Yeah, absolutely. So both connections to investors, sort of mutual matchmaking is absolutely part of the program, we call this Inception Capital Connect. Connecting to customers is as well, but the way we really think of this is just the general category of go-to-market help. So it would be doing this through visibility, right? This is being featured in a blog, or things of that sort. It can be much more direct. But that really depends on the product, on the needs. 

And really the best thing anyone who is in the program can do for that is to really keep us informed. What are you doing? What does your product do? So that you’re on the radar, so that when we are talking with, say, you know, an enterprise company, or perhaps another startup, we’re able to say, “hey, actually, these folks over here do exactly what you need.” So let’s make that introduction.

Walter Thompson: Which leads to my next question, which is about actually landing those customers landing your first enterprise customers, it’s got to be really exciting. But it also comes with, you know, some liabilities and some opportunity costs. What are some of the downsides of working with a big company? And how can AI founders mitigate them?

Ozzy Johnson: The challenge with working with a big company is really, they’re kind of, I wouldn’t say special, but specific expectations. When you work within an enterprise or say, a consumer product. One, just the start, they tend to have a lot more stakeholders in the room, because you’re not just talking to, you know, maybe a practitioner that can work with total autonomy, you also need to convince the manager, you might need to convince a chief architect and executive, etc. 

So that is where to tie this back to what we talked about storytelling, you need to be able to tell your story to everybody, you need to be able to present your product in a way that resonates with the different wants, needs and goals have all of those folks, and you likely need to do it in a way that that will work, when they’re all in the same room together. Without making one or the other feel any more or any less important, then once you’re working with them, you know, there’s a big challenge with an enterprise, they may have feature requests, there may be things that they expect that they need. And it can be really tough to pick exactly how far you’re willing to go, to land the deal, without letting the company essentially dictate your roadmap. 

And this, I think, is a really high power skill of a good founder or a great product leader — to be able to understand that a certain amount of this information or what you’re getting from this company, may be gold, right? Because if they are in a particular space, whether it’s, you know, maybe they’re in finance, HLS or something else, very likely the things they are asking for are going to be representative of folks in that industry of that size. And it’s a great thing if you’re building to features or expectations that are then going to be saleable to the next two or three folks that fit that pattern. 

At the same time, if it’s not saleable. If you can’t scale that, then you’re sort of putting yourself potentially in a world of hurt. So yeah, I’d say those are things to really be aware of. It really is different messaging, you need to have a clear and different story than you would otherwise. And yet there’s a lot to learn, but you have to be really protective of your own resources and your own roadmap when you’re doing that.

Walter Thompson: This is a transformational moment in tech that’s really lowering barriers for people who want to build something. From your perspective, what is this opening up with regard to expanding and diversifying the developer community?

Ozzy Johnson: Yeah, I think that’s a great question. And I think you’re exactly right. And that’s kind of the core point that it is lowering barriers. One of the things we’ve talked about a bit earlier, is how you don’t necessarily need to be a fully technical founder, you don’t need to have that background. Because AI is enabling so much in the way of, again, anyone who can solve problems, anyone who can think in a structured way can be to some degree, a developer. It really is democratizing access to information, generation of code, etcetera, etcetera. 

What’s really exciting, what’s really great about this, to me, is basically, if you are a subject matter expert in something — whatever background you’re coming from, whatever that expertise is — you now have this opportunity to build something, potentially just starting with a team of one by yourself. And this isn’t a thing that we really had before, you needed to have a certain kind of pedigree, you needed to speak the language of code to do this. But now, it’s really anyone who has experience, an idea and a will to do that now has an avenue to do so. 

And with the tools that are out there, you can do so really quickly, not at a huge cost. And what I think we’ll see come of that is just a huge increase in the diversity of people who are starting things who are building things, and frankly, of the solutions that are available. Some of the things that are most interesting to me to see come out of the current kind of revolution with generative applications are things that really help people who may have been previously underserved in ways that are kind of invisible, right? If you have tools that help you communicate better, help you phrase or rephrase or change your tone, or that you can self educate with, that is like truly kind of democratizing our future in a way. So, absolutely: I’m extremely optimistic and have really high hopes for what this is opening up for the future.

Walter Thompson: My final question, do you have any advice for someone who is interviewing for a job with an AI startup in 2024? If you were sitting across the desk during the interview process? What kind of questions would you ask the CEO to make sure this company was on the right track? And was something you wanted to take a bet on?

Ozzy Johnson: Yeah, that is a great question. Probably the biggest, biggest thing, asking back if it is a startup is, first I want to hear the story. Right, exactly. “What is it? Why is it? What are we doing here?” Very often, there are folks who can speak to this. And in a way that sounds good. But it’s like, “why is someone literally going to buy this product? How is it truly different? Is it better than what exists? And then as an extension of that? Where are we headed? What’s the goal?”

You know, it’s one thing if we’re saying “yes, this is how big we think we’re going to be, this is how we’re trying to exit, this is who we think is going to require us?” It’s another? If someone is saying, “well, yeah, this is my vision,” because vision is something that will necessarily change and can really only be understood by the person who has it. 

So I’d be looking for real concrete direction and goals. And, “how are we different? Where are we headed? How is this different?” Essentially, just play me the movie of how this is all going to work and where I fit into it. “What is my role in making that successful?” That’d be the core.

Walter Thompson: Ozzy, thanks very much for a great conversation. I really appreciate the time.

Ozzy Johnson: Yeah, thank you. It was wide-ranging. Interesting. You really made me think in several places. I hope somebody benefits from it.

Walter Thompson: I’m sure they will. Thanks again. Take care.

Ozzy Johnson: All right, thank you.

Walter Thompson: I’ll be right back with some show notes after a word from our sponsors. 

Thanks again to my guest, Ozzy Johnson, Director of Solutions Engineering and Nvidia. For my next episode, fundraising from both sides of the table, I interviewed Jorge Torres, CEO and co-founder of MindsDB and Vijay Reddy, AI Start investor at Mayfield. 

If you’ve listened this far, I hope you got something out of the conversation. Subscribe to Fund/Build/Scale so you’ll automatically get future episodes, and consider leaving a review. For now, you can find the Fund/Build/Scale newsletter on Substack

The show theme was written and performed by Michael Tritter and Carlos Chairez. Michael also edited the podcast and provided additional music. Thanks very much for listening.

This transcript was edited for space and clarity.

Cognition-as-a-Service (CaaS): The Rise of Digital Assistants & Co-Workers

When I observed that AI+Human=Human Squared back in September of 2023, I did not predict the velocity of that change. At Mayfield, in January 2024, we shared our investing focus on the cognitive plumbing layer (middleware, data, models, cognitive cloud infra) as a rich area of opportunity for startup innovation. However, I think the industry is going into a deeper sea change — the era of Cognition-as-a-Service (CaaS) — which follows the mega waves of IaaS (Infrastructure-as-a-Service), PaaS (Platform-as-a-Service) and SaaS (Software-as-a-Service).

Cognitive Plumbing tech stack IaaS CaaS

Every day, we are seeing AI elevate our lives by automating our daily tasks and augmenting our capabilities. I am bullish about the concept of digital assistants or co-workers, intelligent pieces of software (which are built using Large Language Models) that humans interact with using English or their native language that research, plan and take action to complete daily tasks.  

In business, digital assistants are going beyond content creation and code generation to fundamentally transform essential enterprise workflows. Our company Sema4 has developed an automation-as-code platform that builds digital assistants that go all the way from intent to action. For example, a bank manager can go beyond simply chatting with an LLM (if they have implemented one) on what to do in the case of a fraud alert to actually taking action on blocking the transaction and sending the customer the recording and remediation forms. It’s a matter of time before digital assistants for every persona are available, creating a cadre of digital co-workers who work alongside humans to not only automate mundane tasks, but to also complete high-level intelligent tasks that could only be done by humans. 

On a consumer level, whimsical examples of assistants that sort your laundry or design stickers are being discussed. I would love to see one that simplifies my travel — finds me that perfect beach to vacation at as a group of 7 including our pet Labradoodle Toby, books my hotel and flight, remembers to ask if I need a car or two, records and communicates my diet preferences, checks me into my flight, and delivers my boarding pass. 

I see a future where every persona gets a digital co-worker, enabling humans to behave like superhumans.

Learnings from Leaders: Satya Nadella/Microsoft

Navin Chaddha Satya Nadella

In 2013, I had the honor of hosting a TIECON keynote conversation with Satya Nadella, CEO of Microsoft. I was reminded of this chat as I get ready to host a conversation on May 2 with another great leader I admire, Jensen Huang, founder and CEO of NVIDIA. He is an amazing leader of one of the most significant companies of our time, a founder who discusses his 30-year journey with unshackled honesty, and as I have personally experienced, a consummate host. We plan to chat about what the world will look like in the future with GenAI, learnings from his journey, and our shared experience as immigrants.

Satya and I worked together at Microsoft in the late 1990s when it acquired my first company VXtreme, which pioneered video streaming over the Internet and grew into Windows Media. When I chatted with Satya in 2013, he was the President of the Server and Tools division that put Azure on the map.  Many themes from my conversation with Satya are still relevant today as he continues to lead the most valuable company in the world (market cap of over $3 trillion) and at the forefront of the GenAI era.

Keeping his eye on the prize: As we discussed trends such as consumerization of IT, the rise of clouds, and unleashing the power of data, Satya’s excitement was palpable and it was clear that he was watching where the puck goes.

Valuing community: His comments on how game and other developers are going beyond product to help with marketing and design illustrated his view on the power of individuals to influence trends.

Being founder friendly: His comments on how startups can align with Microsoft to benefit from distribution, how founders of acquired companies can bring their risk taking mindset to grow into leaders at Microsoft, and how Microsoft wanted to stay close to Silicon Valley presaged his partnership with Sam Altman, the legendary AI founder of our age.

Having clarity and humility as a leader: His comments on how once you stop learning you stop doing anything useful; how concept, capabilities and culture have to be in lock step for companies to thrive; and how when he complained about his first review, his boss told him how careers can be short-term inefficient and long-term efficient.

Bringing his whole self to work: His open discussion of how being a parent to special needs children has given him perspective and helped shape his attitude which is reflected in how everyone who interacts with him remarks on his empathy.

His final advice to founders was to take advantage of the cloud renaissance to Be Bold – a motto that is even more relevant today as founders soar to great heights in our Human Squared era of AI!

Watch the full video on YouTube.