Building AI-native: Inside the stacks powering Cognition, Gamma, and Harvey

1. SPSpeaker0:00

   [upbeat music] Please welcome to the stage Head of Product for AI at Gamma, Deanie Fatiha; Co-founder of Cognition, Walden Yan; Head of Applied Research at Harvey, Niko Grupin; and Head of Startups and Venture Partnerships of Anthropic, Beth Robertson. [audience cheering]

2. SPSpeaker1:59

   [audience applauding] Hello, everyone. My name is Beth Robertson, and I lead the startup team here at Anthropic, and I am so excited to have all of you in the room with us today. Now, everyone in this room is working through the same architectural questions, uh, that come with building frontier AI companies. And these three humans next to me are absolutely no strangers to them, so I'm excited today to take us on a tour of how the bets that they've made and kind of some of the nuances they've had to navigate as they are building at the frontier. So before we kick things off, I'd love to invite us to just go down the line. Who are you? Introduce yourself, please. What's your day job? Uh, what does your business do? And what is one core bet that you took when founding your company?

3. SPSpeaker2:44

   Core bet. All right.

4. SPSpeaker2:45

   Yeah.

5. SPSpeaker2:45

   Well, first of all, Beth and Anthropic, thanks for having us. This is an incredible event. Uh, I'm Niko Grupin. I lead applied research at Harvey. Uh, Harvey is the generative AI platform for legal and professional services. Um, and bet, yeah, I mean, I think Harvey, and, and I would argue this is the case for most application layer companies, is really a large bet that model and model capabilities are gonna improve really rapidly, and that those capabilities are gonna generalize well to the legal vertical. Right? Like, a lot of people don't know this. When I joined Harvey, we were living and working out of an Airbnb. Uh, Gabe and Winston were using what I think we would call, like, small models now to, to essentially answer personal legal questions on Reddit.

6. SPSpeaker3:29

   Wow.

7. SPSpeaker3:29

   Right? And so it's really this wave of this, this, uh, exponential progress at the model layer that's allowed us to kind of raise the ceiling on our ambition as a company.

8. SPSpeaker3:38

   Amazing.

9. SPSpeaker3:39

   Yeah. Again, also thank you for, for having me. I'm Walden. I'm one of the co-founders of Cognition, and we build AI coding products like Devin and Windsurf. And I think the key bet that I think of when it comes to Devin was really this bet on autonomous agents.

10. SPSpeaker3:55

    Mm.

11. SPSpeaker3:56

    And this was even before we had agents to start with. So in many ways, our product didn't work when we first came up with it, but the vision of having something that didn't just write the code for you, but then actually had its own computer and would run the code and then actually pull up a desktop and test it and tell you when it isn't working and fix its issues and give you a finally working-

12. SPSpeaker4:16

    Yeah

13. SPSpeaker4:16

    ... PR at the end of it, um, very much was not possible with the set of models we had two years ago. But lots of incremental things changed and improved since then.

14. SPSpeaker4:25

    Hmm.

15. SPSpeaker4:25

    Um, I think around this time last year, you saw a lot of natively agentic models like Sonnet 3.5, 3.6 come out. That helped a lot. Computer use testing capabilities are becoming more common nowadays. And I think especially with the recent models we're seeing, there's a large h- long-horizon autonomy that's becoming-

16. SPSpeaker4:43

    Yeah. For sure

17. SPSpeaker4:44

    ... newly possible, where you can have it run on hours end, and you start to feel bottlenecked by trying to run too many agents locally. And so we see an explosion in cloud agent usage this year. I think one crazy stat we've seen as a result of new model capabilities is that our best week of twenty twenty-five, like the, the, the end of twenty twenty-five, the amount of agent usage has grown five to seven X in our customers-

18. SPSpeaker5:07

    Wow

19. SPSpeaker5:08

    ... just so far in twenty twenty-six. So it looks like it's gonna be an explosive year for cloud agents, and it's-- the model capabilities are only gonna keep growing from here.

20. SPSpeaker5:16

    Amazing. Well, we'll get back to your current bets that you're taking in a minute, but let's go down to you, Deanie.

21. SPSpeaker5:21

    Well, excited to be here. Um, first of all, uh, especially excited to be here with all of you folks. We're big Devin users. We're big Claude users.

22. SPSpeaker5:27

    Yeah.

23. SPSpeaker5:28

    We're big Gamma users. And Niko, we're gonna have to figure out how to get big on Harvey too. [laughs]

24. SPSpeaker5:31

    Get you on Harvey. Come on. Where's your GC?

25. SPSpeaker5:33

    [laughs] Um, hey, everyone, I'm Deanie Fatiha. I'm head of AI product at Gamma. Uh, Gamma is a visual communication platform for professionals. We have seventy million users and growing. Um, Gamma started with the simple observation that people like us, when we're, you know, communicating our highest stakes ideas, we're usually doing it through a visual artifact, you know. Presentations to your investors, uh, proposals to your customers, marketing sites, social posts to spread your ideas. Um, and what do we do when we have to communicate those ideas? We spend, like, ten percent of our time thinking about the core insight and ninety percent of the time on the design and the formatting and the futzing of the details. Um, Gamma's big bet was that AI-- with, with AI, that we could take away that ninety percent of the futzing that people spend their time on. You as a professional, uh, bring the core insight that only you are capable of bringing. Gamma will take it, flesh out the idea, structure the narrative, design it, and make it look beautiful so that your ideas can be cast in the best light possible.

26. SPSpeaker6:32

    Yes, and it's a beautiful experience. So thank you all for building what you've built. We love it. Um, I wanna just go back to the origin story before we kind of get to the present. Um, there was presumably a window where you just had an idea, and it was finally made possible.Talk to me about what was happening kind of in the, the ecosystem. What shifted that made it first possible for the first time for your product or service to exist? Was there a moment? What was kind of the, the moment?

27. SPSpeaker7:03

    I'm happy to, I'm happy to take the first stab at this. Um, and to be honest with you, I, I do think there was a first moment, but I think honestly with every big wave in AI progress, Gamma's had tailwinds that have, you know, also evolved our product. So, uh, Gamma actually started in 2020 before the recent AI wave really had hit and landed. Um, but when image models started to get come out and get good, and when LLM instruction tuning started changing how we interact with LLMs and what we can get out of them, that's when Gamma really had an aha moment, and that's, that's the inflection point that birthed Gamma as we know it today. Um, but over time, I mean, uh, again, like I said, tides of AI progress have evolved how we, we see and build our product. Uh, the next big thing that I think we did was when LLM tool calling started getting really good. We jumped on it. We built our first agentic experiences. Uh, to this day, editing using our agent is one of our biggest differentiators, and that happened because of the, you know, big wave in tool- LLM tool calling and, uh, agent, uh, uh, or- uh, orchestration. Uh, a, a big one for us as well was the MCP wave. Again-

28. SPSpeaker8:07

    Mm-hmm

29. SPSpeaker8:07

    ... we leaned into that early. We leaned, leaned into it heavy. It allowed us to build connectors into several other platforms. Actually, I think we built our first connector into Claude.

30. SPSpeaker8:17

    Oh, nice.

Episode duration: 28:15