Factory Raises $50M from NEA, Sequoia Capital, NVIDIA, & JPMorgan

25 Sep 2025 · 58 min

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Podcast Episode Notes: Sourcery - Factory Raises $50M from NEA, Sequoia Capital, NVIDIA, & JPMorgan

Episode Overview

  • Title: Factory Raises $50M from NEA, Sequoia Capital, NVIDIA, & JPMorgan
  • Description: Factory has raised a $50M Series B funding round with notable investors including NEA, Sequoia Capital, NVIDIA, and JPMorgan. The company is pioneering "agent-native development" with their autonomous software engineering agents called "Droids". CEO Matan Grinberg discusses the transition from traditional coding to delegation in software development.

Key Highlights

Funding and Growth

  • Factory raised $50M in Series B funding led by:
  • NEA
  • Sequoia Capital
  • NVIDIA
  • JPMorgan
  • The round also included notable angel investors like Frank Slootman, Nikesh Arora, and Aaron Levie.
  • The funding is considered a milestone for expanding the team and enhancing growth strategies.

Transitioning Software Development

  • Matan Grinberg emphasizes a fundamental shift from developers writing code to delegating tasks through autonomous agents.
  • This transition is termed as agent-native development, which is compared to the difference between horses and automobiles in the evolution of transportation.
  • By 2024, Factory aims to scale from zero self-serve users to hundreds of thousands, particularly engaging with Fortune 500 companies.

Vision and Product - Droids

  • Factory's flagship product, the Droid, acts as a task-specific software engineering agent:
  • Capable of handling tasks like migrations, refactors, testing, documentation, and incident response.
  • Droids are designed for efficiency and to reduce mundane coding tasks, enhancing developer productivity and job satisfaction.
  • The aim is to promote a behavior change in software development, with a focus on delegation rather than mere code autocompletion.

Market Dynamics and Customer Base

  • Factory has seen rapid adoption among large enterprises that are eager to leverage new AI tools, learning from past technological shifts.
  • The company is focused on maintaining positive margins and delivering clear return on investment to enterprise clients.
  • Collaborations with major firms like EY, Nvidia, MongoDB, Zapier, Bayer, and Clari indicate strong traction and credibility in the market.

Founder’s Background

  • Matan Grinberg transitioned from a PhD in string theory at Berkeley to launching Factory, highlighting a unique journey of combining physics with practical AI applications.
  • The founding team includes Matan and Eno Reyes, who previously worked in high-profile engineering roles. Their synergy and complementary skills drive Factory’s innovation.

Company Culture and Future Vision

  • Factory promotes a culture of “create obsessed customers”, fostering deep engagement and satisfaction with their product.
  • The company values a missionary culture over a mercenary one, seeking passionate individuals who believe in the vision of transforming software engineering.

Key Takeaways

  • Factory's approach to agent-native development signifies a major shift in how software is developed, focusing on enabling developers to delegate tasks to AI agents.
  • The successful funding round positions Factory well for growth and innovation in a competitive landscape, with a strong focus on enterprise-grade solutions.
  • Matan’s journey illustrates the potential of cross-disciplinary skills—combining academic rigor from physics with practical software development to create impactful solutions.

Conclusion This episode of Sourcery provides a comprehensive insight into Factory's groundbreaking approach to software engineering, the strategic funding that will fuel its growth, and the visionary leadership behind its evolution. The conversation showcases how a blend of technology, innovation, and a strong company culture can lead to disruptive changes in the software development industry.

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Transcript

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0:00We're moving quickly from a world where developers wrote 100 % of their code to a world where developers wrote 0 % of their code. We are very happy to share that Factory has raised$50 million for our Series B, NEA, Sequoia, Abstract, JPMorgan, Microsoft, and NVIDIA. Initially, I was doing a PhD at Berkeley in string theory. The problem that I was working on at the time was about 10-dimensional gravity, which I don't know if you've noticed, we don't live in 10 dimensions. And I've been pursuing that basically for 10 years. There is a controversial topic right now, especially here in San Francisco, and it is margins.

0:33Yes. Margins in code gen companies and AI companies. Do you have good margins? Shocking to believe we have good margin. And when I say good, I don't mean not that negative. I mean positive margins. And I think a lot of that has to do with the approach that we are taking and the philosophy that we're approaching this with. We started the year with zero self-serve users and basically zero proper enterprise customers. Since then, we're now at tens of thousands in boat. In that famous Henry Ford quote, you ask people what they want, they'll say faster horses. We see the AI within the IDE as like faster horses.

1:02And the reality is there is going to be automobile and that automobile is agent native development. If you were to join any cult, what would it be?

1:18Matan, welcome to Sorcery. Thank you for having me on. It's a pleasure to be here. Well, I think we have some big news today. We do indeed. We do indeed. Yes, we are very happy to share that Factory has raised$50 million for our Series B. We have NEA, Sequoia, Abstract from the VC side of things, and then also JP Morgan, Microsoft, and NVIDIA on the more strategic side of things leading the round, which is very exciting for us. Wow, that's quite the group. Okay, so what was the process like for you in this? At Factory, we're a little bit kind of avoid thinking about fundraising too, too much because I think it's kind of just a milestone or a point for like a phase transition as a company as opposed to this.

2:00you know, I feel like in some cases it's treated as like a goal in itself. Um, and for us, the reality is, uh, we hit the point where we're growing really fast on the growth and go to market side of things. Um, and we're ready to hit that phase transition and really expand the team rapidly. And so because of that, uh, you know, had a few conversations, we, we mostly knew a lot of the people that we were excited to work with anyway. Um, and you know, we were able to quickly get them involved and get us into the Series B, into that next gear. Was it fast? Was it slow? Yeah, it was pretty quick. We tried to, again, like I think even just generally for fundraising, it's ideal to time box things because we have a business to run.

2:45We have droids to ship. And so can't be spending too much time on VC coffee chats as it were. So yeah, we were pretty quick. And given the composition of the round was institutional funds and strategics, can you just talk about the strategic component? Like how did they get involved? Yeah, well, I mean, I think it's actually it's fun because it's a pretty diverse set of strategics like JPMorgan, Microsoft, NVIDIA are pretty distinct. And I think it kind of embodies the nature of what we're building at factory and how it really goes across the board, you know, down to the GPUs, to the largest engineering organizations in the world like Microsoft, to the most reputable financial institutions in the world like JPMorgan.

3:30we're working with all of them you know nvidia we obviously can work with them on a lot of different things from inference to you know having their developers actually use factory you know obviously for jp morgan it's more on the side of you know deploying factory within their teams and then microsoft again there's there's kind of a lot we can do together from going to market together with factory and then also having their developers use us so it's a pretty broad. Okay. Well, I don't normally start with like a background story question, but the founding of the company is super interesting. Your background is super interesting.

4:04And now all of a sudden you're doing co-gen. So could you go back to how this all began? Yeah. So, I guess initially I was doing a PhD at Berkeley in string theory, in particular in quantum gravity, which is really interesting, very beautiful, very beautiful mathematics, but unfortunately very, very far from reality. In particular, the problem that I was working on at the time was about 10 dimensional gravity, which I don't know if you've noticed, we don't live in 10 dimensions. It's very not related to the world that we live in. And I, I'd been pursuing that basically for 10 years. And while doing the PhD, I ended up spending a lot of time in San Francisco, a lot of time going to hackathons.

4:45And I eventually switched my area of focus from quantum gravity to AI, because I realized that I was just doing physics really because it was hard. I did end up finding it very beautiful, but I think over time, um, I was lacking that like grounding in reality. And I found that AI really satisfied that itch and in particular, what was then called program synthesis, what we now call code generation. Um, so it was really interesting that realized that research was not the best place or like research in academia was not kind of the best place to explore code generation. And ended up actually seeing, I remembered that there was this physicist that I had cited in one of my papers that I saw on YouTube on a Zoom podcast because it was during COVID.

5:31And I recognized his name from physics, but I saw he was working at Sequoia, which at the time I didn't even know what that was. And I was like, oh, like this guy seems pretty interesting. He has social skills, which is very rare for, for string theorists. I was like, you know, he might be my type of guy. Let me go and reach out and see, see what I can learn from him. So I sent him an email. He responded immediately and was like, Hey, like come down to our office tomorrow. Let's go for a walk. Um, and obviously I was super excited. So, you know, went down there, we ended up walking for three hours from three hours, three hours from Sandhill all the way to Stanford and then back.

6:05Keep in mind, I was wearing like, I don't know, some like boots or something. So like at the end of this walk, I had, you know, a lot of blisters, but, uh, it was, it was just an incredible conversation. We found out that we had a lot in common in terms of why we got into physics in the first place. Um, and then similar reasons for why I guess at the time I wanted to leave and similar reasons for him, why he did end up leaving. Um, and at the end of that conversation kind of, we got back, you know, to their office at Sandhill and he was basically like, okay, Matan, um, no matter what you should drop out of your PhD and you should do one of two things.

6:38You should either join Twitter right now because Elon just took over and you'd have to be like a badass to go and, you know, voluntarily go, you know, be hardcore and work there, or you should start a company. And I was like, oh, you know, thank you so much for the advice. You know, appreciate you taking the time. In my head, it was like, I obviously want to start a company, but I kind of didn't want to contaminate that meeting with them like a little pitch or like, oh, here's, you know, what I'm working on. So didn't do that. Coincidentally, the next day, I ended up going to this hackathon in San Francisco and reunited with this guy that I vaguely knew at Princeton.

7:09His name is Eno Reyes. He was similarly obsessed with cogeneration. And the next day he kind of put aside all of his work at the time. And we started building the first demo of what would become Factory. The next day showed it to Sean. He was like, you know, this is cool. But if you want to pitch it to Sequoia, drop out of your PhD and send me a screenshot, which I did without telling my parents, you know, the following, the following day had a, had a pitch to, to the whole partnership there, which I think would have been a lot more intimidating had I actually known much about like startups or the VC world, but I was still kind of this physicist who didn't really know too much.

7:49You know, it ended up going well. They grilled us a lot, but ended up getting some funding and then, you know, quit his job and then we started factory. Did you know who Sequoia was? I had not heard of them at the time, honestly. I think I vaguely knew just because, so I went to Princeton for undergrad and they were like, I feel like the name had come up, but like, I feel like there are so many like PE firms or financial institutions that are loosely named after plants or trees that at the time I like probably didn't know the difference. It's just another tree. Yeah. Yeah. Tree VC fund. Exactly.

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9:02With same day and even same hour liquidity, access your funds anytime. Companies like Scale AI, DoorDash, Service Titan, HIMSS, Anthropic, Flexport, Robinhood, and Plaid trust and use Brex. Start today at brex.com slash sorcery. That's B-R-E-X dot com slash sorcery. Well, you picked a good tree. Yeah, yeah. So that brings us to today. Could you share a little bit more on factory and what you're building? Yeah, so our mission is to bring autonomy to software engineering. We started, so this story, this was back in early 2023. So just a couple of months after ChatGPT came out. And our vision from day one is that software development in this world of AI is going to look very different.

9:49And what we had up until then, and even then it was still nascent, was like AI assistance. So at the time it was co-pilot. Now we have a lot more AI IDEs that are getting a lot of attention. But our goal has always been the behavior change of software development, where you go from, you know, writing lines of code yourself to delegating tasks to autonomous agents. Obviously, 2023 has been very early for that. Behavior change takes a long time, but that's been our mission since day one. Our agents, we call droids. They're task specific. And it's also part of the reason why we had the droid name is agents, especially at the time, and really still today, are kind of synonymous with like while loop.

10:33It's pretty poor quality and not actually ready for production. And so because of that, we were like, we're going to separate these out, call them droids. People really love it, which has been fun. In today's high-speed business world, staying ahead means using the smartest tools possible, including the powerful capabilities of artificial intelligence. Meet Turing Intelligence. Turing builds customizable AI systems designed to solve your mission-critical challenges, no matter your industry. From expert guidance to tailored projects, Turing helps top companies realize AI that's more capable, more adaptable, and more effective.

11:07With Turing, discover how AI can accelerate your business growth. To learn more, visit Turing.com slash sorcery, spelt S-O-U-R-C-E-R-Y. That's Turing.com slash sorcery. Okay, but like, what the f*** is a droid? Like, how does this resonate? Yes. So, so droids are basically task-specific software development agents. And the way you can kind of mentally classify it, you know, is this something that should be a separate droid or is this just one existing droid doing a particular task? Generally, you can define it by the workflow. So, you know, writing features is probably going to be one droid, the code droid, because generally the workflow of writing features looks pretty similar no matter what feature it is.

11:51You know, you're going to look at some documentation, come up with some loose plan of what it is that you want to do, and then you're going to start implementing. You might write some tests, execute the code, see if it worked and kind of iterate from there. In contrast to something like writing documentation, where when you write documentation, generally, you're not going to be, you know, going in and editing code and executing code, but you're instead going to be kind of looking through the code base more thoroughly and trying to figure out how you can consolidate it into a representation that's helpful for a human, which is also different from like incident response.

12:23Like if you have an outage that comes up in, you know, a tool like Sentry or something, the way you go and triage that and respond to that is a very different workflow where you might be looking through Slack threads or, you know, going on certain webs like platforms or applications to go and see the logging of what happened. So those loosely are the kind of different categories of a Droid. I also will say that it is time dependent because I think the way you divide up these different workflows into Droid changes as a function of how good, you know, our agentic frameworks for the droids are, but also how good, you know, models are in kind of the shape that the models take.

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13:41That's C-A-R-T-A dot com slash S-O-U-R-C-E-R-Y. We're in San Francisco. We're really close to Lucasfilms. Was there any problem with the naming there? I mean, that's pretty good branding. Yeah. So funny enough, when we first pitched to Sequoia, we pitched as the San Francisco Droid Company. Really? Yeah, that was our initial name. That's a great name. Yeah, it's a great name. But our lawyers advised us that Lucasfilm is very litigious and would probably come after us very quickly. So we were gently advised to change the name. So we're now the San Francisco AI Factory. Okay. Slightly less fun, but the product's still droids.

14:19It's still going to be a fun day when we get the cease and desist from Lucasfilm. We'll see when that happens. But what's the point of raising capital from Sequoia if you're not going to go into a lawsuit with Lucasfilm? Yeah, exactly. And also, like, I just dream of that, you know, getting George Lucas out to a coffee and try to convince him that it's okay. Like, that would just be such a good, such a good experience. So, yeah. And it's resonating well with your customers. Like they, they, they kind of, they grasp that better than maybe another like human name. So first of all, I have a lot of friends who either run or work at companies that have like human name AI agents, but it's actually insane.

14:53Like how many of these, like, you know, Steve, like whatever, these random human names running around, like, how are you supposed to know what Steve does? Like, so I think it's, it's nice to, to not, not give them human names. And also, I cannot tell you how many customers after they first try Factory will send us a meme of like, these are the droids we're looking for. Or like, I speak for the droids. So it's pretty fun. I think there's probably a high overlap of Star Wars fans and software developers. So I would imagine. I would imagine. That's good. I think that makes sense. I mean, I'm obviously like a brand nerd.

15:26Like, I love merch. I love all that stuff. And it seems like you're speaking more to the language of your customers, which makes sense. you're not getting another like random human name in there. Like it's distinctive, it's branding, it's like good for you. It's authentic, which is good. Um, I think like taking a step back, let's talk about the overall evolution of this environment from the macro level. So like who were the early players in this and how has this like evolved to today? Because it's super competitive now, but like, how did we get here? In the very early stages, it was basically, at least for coding, it was basically Copilot and a couple other startups.

16:03And in the early days, I think most of the kind of first past use cases were all just different kind of variations on an IDE extension or kind of a fork of like a VS Code IDE and making it a little bit more native to some of the new models that are coming out and some of the new interactions that are emerging. And I think over time, we're seeing slowly this transition. And this is partly due to behavior change and the way people think about these tools changing, partly due to the model capabilities growing. But we're now seeing a little bit more on the what we call delegation side of things. So instead of thinking about it as like, here's a task that I'm working on and I want to do it faster as I'm like serially going through the steps of this process.

16:50Now you're starting to see a little bit more in the way of like people shifting to here are the 10 tasks I need to work on. I'm going to now work on these in parallel. So I'm going to delegate that task to this agent, that task to that agent, and I can kind of go and monitor and see how they're doing. Or, you know, something that we see our customers do with our review droid is I'm going to set up this automation so that every PR that comes in, it's going to get reviewed by the review droid, which is going to look out for these certain things that are custom to how our org works or this particular repo or this particular team.

17:23So you're seeing now, like in the last probably six months, people go from like this AI assistance, autocomplete to instead what we call this more agent native approach, which is how can I get more leverage by getting agents to autonomously go and do things so that I can have time for higher leverage tasks? How do you think this is going to change the role of a developer in the next five years? This is a great question. So it really upsets me when people kind of, and they do this for fundraising reasons, but people often go out and say like, developers are done, like use like insert name of our company instead, because like, you know, software developers are cooked.

18:02Tell your kids not to study computer science. Yeah. Like, I think not only is that like bad for the space, it's also just false. because the reality is as you have better and more capable agents for implementing code, what you decide to actually have it implement matters more and more. And the way you actually structure the product that you're building or the systems that you're building become more and more important. And at the same time, also having really good verification and validation becomes more important because if you think of software development as like a pipeline, having agents or these, you know, LLMs to generate code, it blasts open the implementation or the coding part.

18:42But if you're doing nothing to the other parts of the pipeline, you're not actually having any end-to-end speed up. So concretely, what that looks like is, you know, suppose you deploy coding agents into a company that has really poor testing and monitoring. And so now you give these agents to everyone, they're now doing, you know, 10 droids in parallel, like writing all this code, but that code needs to get reviewed before it gets pushed into production. And so you now have this new bottleneck, which is these human engineers have to go in and review code for hours and hours and hours, which if you ask any engineer, that's like absolute hell.

19:16And so I think the important thing to consider is how do you increase that implementation part of the pipeline, but also increase the bandwidth of the validation and verification. And so while there's less emphasis on coding, there's a lot more emphasis now on planning and scoping, like the things that you actually do want to build. And then also setting up your engineering environment such that the agents are set up for success so they can execute their own, you know, whatever features that they've been building. They can go and triage if certain things aren't working. They're very clear monitoring and observability into like the status of all systems so that they kind of have eyes and ears to see and they're not just shipping AI generated code into production.

19:56How do you see this changing team composition though, right? Like some of your customers, I'm assuming because they're strategic investors are customers, but like you're seeing this from like really, really high enterprise levels, but I'm sure you also have like some more smaller, like startup companies. So like, how do you see that changing the composition? Yeah. I think anyone who is giving you certainty on this answer is lying. I think it is unclear to me, um, what these roles will be called. You know, some people say like AI engineer or like, you know, they're IC engineers, they're product managers, there are engineering managers.

20:28I think with these tools, some of these roles get smeared a bit because if you're a very systems oriented PM, this allows you to write a lot more code. Um, but you know, you're still thinking about the right things. And I think that's going to make you high leverage. Similarly, if you're a product minded, I see this will also help you. I think it allows you as that IC to become a little bit more of a PM as well. Um, or even like an engineering manager, because now you can delegate these tasks. So the answer is, I don't know what the names of these roles will change to, but I do know that the people with really good systems thinking, people who really understand how product interacts with business goals and infra goals like reliability, latency, what the customers say they want versus what they actually want versus the way you want to position in terms of marketing, you'll be able to ship whatever features you want, but the humans will still need to go in and synthesize what features should we actually ship.

21:26Just because we can ship everything doesn't mean we should. And I think having really good humans with taste about what to ship is going to be all the more important. And at the end of the day, the best engineers have always been the one with the best systems thinking, best way to think around these constraints. And so I think it will elevate the best engineers. Is this making their jobs more fun, more attractive? Is this helping the role? There are some developers who enjoy some of the things that will now be automated. But I think at the end of the day, having high leverage for most people feels good and is like addicting.

22:00And a world where you don't need to do migrations as often or spend time on refactors is a world where developers are a lot happier because they get to do higher leverage things. So most of our users end up being very, very happy about the things they no longer have to do. So let's get into numbers if we can. I want to talk about your growth. Yeah. If you could share, like, what kind of growth have you experienced since the beginning of the company? Like, what are you seeing now? Yeah. So I guess loosely we can describe our trajectory. So we started in 2023. I would say 2023 was really all about building the team for us, building that early team.

22:352024 was all about building the product. And 2025 has been all about really growing in terms of users and enterprise customers. Um, so we started the year with basically, so we didn't have a self-serve offering. So there were zero self-serve users and basically zero proper enterprise customers. Um, and since then we're now at tens of thousands in both, um, which is pretty exciting. Um, and hopefully, you know, by the time we release this, it'll be hundreds of thousands in both. Um, but I think the biggest thing has been seeing how quickly in particular the large enterprises take up these new tools because generally they move slower.

23:19But what's been interesting now is seeing that they're actually, I think partly because they're burned from like a lot of these large enterprises were late to mobile or late to cloud. And so they're like, we are not going to be late to this one. And seeing the speed with which they adopt this agent native development has been really, really interesting. It's also cool because, you know, if you're a firm with 10 ,000 engineers, you kind of have the most to gain or lose by adopting this quickly or not. Um, and so obviously, so it's been less surprising seeing, you know, some mid-market companies take this up because they're the ones, you know, where they might be based in SF and are, you know, thinking about every single tool that comes out.

23:53Um, but seeing some of these massive organizations, uh, drive adoption very quickly has been really eyeopening. Apart from hitting hundreds of thousands, like how are you thinking about milestones and what you want to hit, especially with this new funding? Like what are your goals? Yeah. I mean, I think, you know, one of the big things is reaching just a lot more of the, there's kind of a huge chunk of developers who are in these large enterprises who are stuck with very tedious, very kind of soul crushing work in like migrations, refactors, modernizations. and there's a lot of low-hanging fruit in terms of alpha there because there are orgs that we work with that have like, you know, migrations that are supposed to take a year that have been in the backlog for three years and they're holding back the business, it's holding back the engineers, it's holding back their customers and reaching more of these, I think is just, aside from the economics of it and the fact that it's good for factory, it's also just so satisfying seeing the look on developers' faces when it's like, oh my God, that nightmare migration that we've been putting off for years with droids, we got it done in like two weeks.

24:57Um, so reaching more of those, um, we're working with a lot of the fortune 500 and so kind of continuing that and really becoming a standard there, I think is something that's, that's pretty important for us. Um, yeah, those are, those are some things that are top of mind. Can you share some of your customers? Yeah. Um, so a lot of them are, uh, you know, the one downside about working with large enterprises is they're a little bit less, uh, you know, quick to, to do the kind of publicity about us working together. So you don't want to name every single one of them? So maybe not every single one, but I think one that has been particularly exciting and was also, if you told me this two years ago, I would not have believed it, but, uh, EY, Ernst & Young, one of the, you know, big four accounting firms, uh, is deploying droids, uh, org wide globally.

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25:41Um, and the speed with which they're adopting is crazy to me. like they're adopting like a startup, which is wild because my understanding, and I bet if you asked anyone, it would be like, no, those, you know, those firms, maybe 10 years from now, they would do it. But seeing the speed that they're, that they're adopting is really exciting. We're also working with them and some of the big three consulting firms as well, going client facing, which I think is cool because it's a, it's another way that we can hit just more users faster. Do you have any partnerships? Like, how do you think about go-to-market was, how is that structured?

26:14A lot of the partnerships that we pursue on the go-to-market side are with, you know, the big cloud providers. But also I think there's a really something that factory has that not a lot of others do is the focus on the enterprise grade security. You know, I can't tell you how many CTOs or VPs of engineering have mentioned that these co-generation tools feel like they're giving toddlers machine guns. What? Which, you know, all that. And maybe it's not a very respectful way of saying that, you know, they're concerned about, you know, if you have an org of 100 ,000 engineers and you give them all this ability to start producing hundreds of PRs, it's concerning of like what's going to happen to our code quality.

26:51Are we going to have some massive incident in production because we were a little bit too eager to throw these things in without proper security considerations? and so we're working with some of the biggest like security dev tooling companies on having it's kind of you know two different things that we're doing so one offering that we have is basically ensuring with some static checks that every PR produced by a droid passes whatever existing security rules they have within the org but then also there are a lot of tools that will go in and measure within your code base here are all your vulnerabilities we can actually have a droid go in and solve each one of those as they emerge, which is kind of a nice partnership that we have because it makes sense for both, you know, the security companies as well as for us.

27:37Is there one key component that people are looking to optimize the most? Like what is the, how do you measure success? Yeah. So, and I think the org that we're working closest on this with is Snyk. And something that a lot of people are concerned about is basically like, there's kind of this duality between like what the CTO wants and the CISO wants. because the CTO is like, we want to adopt AI. We want to adopt agents. We want to do this agent native development. And then the CISO is like, what the hell is all this code that's going to be coming into our code base? How do we know it's going to be good?

28:07How do we know it's going to be like compliant with all these regulations that we have? And this is kind of a balance that right now there's been no answer. Like most of the people that have been doing it have kind of just been YOLOing and just like throwing the tools in. Some of the tools out there even have like YOLO mode, which I think to an enterprise customer is not exactly what they want to hear. And so figuring out how we can increase the leverage of all their developers while also keeping in mind the importance of the security and integrity of their systems is something that we care a lot about.

28:41I mean, you're particularly new to this as a founder. You were getting a PhD and you were pretty much like studying string theory. Now you're selling to customers some really big names. Was there any sort of emotional experience that you had? Maybe it was like your first customer or second, but like, was there any particular moment? Yeah. So yeah, I think there's one that comes to mind was, so I mentioned that 2024 was kind of a year where we really built out the product. Along the way, there was just like a lot of, you know, we had some ideas. We realized that we were too early in terms of people's behavior, because there are kind of two things you have to balance.

29:16Like what can the product do? And what are people, like how much are they willing to change their behavior and kind of lean in to adopt some new interaction pattern. And some of our earlier iterations just like, weren't quite hitting right. Um, which was obviously very frustrating. Um, and I think the big thing was, um, in January of this year, there was this one customer that we had initially done a 30 day pilot. We'd extended it another 30 days and another 30 days. Cause we just weren't quite hitting the mark. And then the first version of like the factory that exists now, um we finally had it and delivered it to them um it was way worse than it is you know barely functional but it was like a beta version that was actually working and um you know we had like one week left in the pilot and then uh I had a sync up call with our champion just to get a sense of like you know the 90 days is up they're not going to do any more extensions and we had to you know figure out if we're going to proceed or not and so he's like hey Matan um you know I just spoke with our CTO and he was, you know, trying to get a sense of like, Hey, like, what are we doing here?

30:21Like we need to, you know, and if it's, if it's not going anywhere. Um, but you know, since you gave us beta access last week, this is, I finally realized like, this is the factory that I was envisioning when you first pitched me three months ago. Like, this is what I've been waiting for this whole time. And so our CTO asked like, Hey, you know, would you rather I hire a junior developer for you? Or would you rather we procure this and, you know, give it org wide or we procure this and you are the only person that uses it. Like if we procure this and you're the only person that using that uses it, is it still worth it?

30:54Um, and he was like, and Matan, I wanted to let you know that I told him that we need to procure a factory. Um, and I remember just like, you know, ear to ear grin, like smiling immediately. Like when the call ends, I like run into the main room and I'm like cheering with the whole team and we're all like celebrating tears, like streaming down my eyes. It was, uh, that was truly one of the most satisfying, uh, moments ever. Cause it was like two years in, um, and we hadn't really gotten that developer obsession until that moment. Um, and yeah, I mean, that was, that was incredible. Wow. Yeah. You created like real, real value and affinity for someone that they stuck around that long to see the vision through.

31:36And then so quickly they started doing like org wide deployment. and they did a big hackathon with their whole team. They were sharing about it. We ended up like, the guy was based in Australia. Like we flew him out. You know, we had a great time. Yeah, we're still in touch. I think moments like that are just so special and I think so memorable. Things like that are what make all of the grueling nights and very, you know, opposite end of the spectrum of emotions. It makes it all worth it. Next time, go to Australia. Yeah, honestly. Yeah, I've never been. It'll be fun. It's a good excuse. Yeah, yeah.

32:07So I want to shift into the business of this, particularly the business model and pricing. Let's start with pricing. So how do you package this for your customers? You obviously have a smaller tier option and then enterprise. So how does this work? Yeah. So for the, for the team's plan it's$40 a month. You know, it's relatively self explanatory there. And we have a free trial just to, you know, make sure that, you know, new people can go in and get a sense of what this kind of new paradigm looks like. for enterprises, we do usage-based. And I think the important thing there is we're well past the like seat-based world.

32:42It also just makes no sense because if you do seat-based with agents, they're going to play this game of like, oh, well, I don't know if this is an active seat. So I don't know if I should take it. People are maybe more reluctant to adopt AI. We'll just be like, no, no, no. I'm going to stay in Vim and Emacs. Like, I don't want to use all that fancy stuff, which is kind of counter to what we want to do. Like we want to work with them. We want to align our incentives such that the more they use droids, the more value they get. And we both want that outcome. Um, and so, you know, because of that, we're usage-based and, um, I think it's also very helpful to drive that adoption, which is something that's kind of underrated in terms of how the companies that are building these tools, I think, talk about what they're doing because half the battle is having the best product.

33:28I think that's, that's really important. But the other half of the battle is how do you actually get developers to change how it is that they build to go and build in this new way? And for us, it's this agent native way, having their primitive kind of fundamental step of software development change from me writing a line of code to delegating a task to an agent that requires a kind of mentality shift. and if we can do that by saying, hey, you know, go try it once. It's usage-based. Just send one, you know, send one, delegate one task to an agency if you like it. We find that that's a lot more inviting.

34:04People can then record a video, share it with their team. Then another random person will try it once. And we also find that within the enterprise, when someone sends like one delegation, the retention at the 10th week ends up being 85%. So even though there is this big behavior change and we're not an IDE. Like we're kind of separated from that with this new interaction pattern. Despite that, it's like once they try it once and see what this delegation can provide them, they end up being pretty hooked. Sticky. Yes, indeed. Yeah, it was not like that in 2024. Times have changed. Yes, indeed. And the product's gotten better.

34:41Yeah. There is a controversial topic right now, especially here in San Francisco, the like AI capital of the world. Yeah. And it is margins. Yes. Margins in code gen companies and AI companies. How do you think about margins within this? Are they good? Do you have good margins? We have good margins, which is shocking, shocking to believe we have good margin. And when I say good, I don't mean not that negative. I mean, positive margins. And I think a lot of that has to do with kind of the approach that we are taking and the philosophy that we're approaching this with, which is it's not about like, you know, reselling LLM usage and like in a very familiar package, it's about this behavior change, this move towards this agent native development.

35:25And when you do that, and when you're focused on delegating these tasks, the ROI is that much more clear to these enterprise buyers. And when the ROI is clear, like, I don't need to do this migration anymore. I don't need to do this refactor. You know, you're kind of able to structure these things such that you're not kind of subsidizing their token usage, but instead you're providing leverage for their developers, which obviously, you know, as an, as a enterprise, you value a lot and they'll pay accordingly. The pushback on this is that sales and marketing spend is super heavy. It's a super competitive environment.

35:59Not going to lie. I saw some billboards around the city. Yes, that's right. And they had to do with droids. They did indeed. So how does this fit in? Yeah, well, so I guess, first of all, the initial, the first billboards that we put up were free courtesy of our friends at Brex because of the points that we had, which was a really good proving point of that as a way of demand generation because we got some ridiculous leads. And then the ROI calculus changed and it went from, wait, this is so cool that Brex allows us to do this. Like, that's fun. Like, you know, send it to my mom to wait. This is actually a serious channel for us to find new customers.

36:37Also to re-engage like, you know, pipeline that maybe slowed down. I cannot tell you how many texts I got from like CTOs and VPs of engineering, like one hand on the wheel, one hand like photo of the billboard. So the ROI on that makes a lot of sense for us now. I saw one touching grass. I saw one with fire in a coffee cup. Yeah. Droids trip software while you sip coffee. Exactly. But we do love Brex, by the way. Rex is the billboard capital of the world for AI companies. We're moving quickly from a world where developers wrote 100 % of their code to a world where developers will write 0 % of their code.

37:17But most of the existing tools that are kind of in the ether and in the mind space are like retrofitting AI to the IDE. And we see that as, you know, in that famous Henry Ford quote, you ask people what they want, they'll say faster horses. We see the AI within the IDE as like faster horses. And the reality is in this like paradigm shift that we're going through, there is going to be behavior change. That behavior change is going to be the automobile and that automobile is agent native development. You're not going to be writing lines of code yourself. You're going to be packaging up tasks for your agents.

37:52You're going to be delegating it to them. And the success will be judged by how well you scoped it and how well you set up the validation and verification criteria in a similar way to, you know, taking a horse on a, on a mud road works fine. If you take a Model T on there, it might not do so well. And so it's worth investing some resources in paving your roads, setting up some gas stations. It's kind of analogous with what we're doing with some of these enterprises. The competition is really hot. We talked about that throughout the conversation a little bit, but in different ways. So you went, you have a good branding style droids, you have billboards, but you have another differentiation and that's your agnostic.

38:32So could you explain the different buckets in which you're agnostic and why this is important? Yeah, absolutely. So something that's really important for developers, especially as they're learning this behavior change is understanding how the models work. And there are a lot of tools out there that'll kind of say, we're going to figure out what the best models are. Like you as a developer, you don't get to see it. You just use our tool. We're model agnostic because A, that teaches developers, you know, how the different models behave and it gets them kind of aware of the different, you know, flavors or personality traits that these models have, gets them familiar with tokens and what that means in terms of the fidelity of each, you know, model call and that sort of thing.

39:09So we're model agnostic. That also helps for the enterprise because there are some enterprises that have special agreements with Azure or with AWS or with Anthropic directly or with OpenAI. And so allowing that to be kind of custom to whatever their existing setup is, is very helpful for them. We're also surface agnostic. And so, you know, there are some tools again that are like, you must use us in the IDE or you must use us in terminal or in a web app. Instead, our approach is we're asking a lot of developers to change their behavior. And so accordingly, we need to meet them where they are. And just how if you're working with a colleague, you wouldn't only ever interact with them on Slack or only ever interact with them on your browser.

39:48Similarly with droids, you should be able to delegate a task to a droid wherever you are, whether that's in your terminal, in your IDE, in a web app, in Slack, in linear. And so accordingly, you know, the droids are kind of ubiquitous. So wherever you're working, you can go and delegate to them. Cooperation compared to competition. That's what you're going for. Yes, exactly. We haven't talked about your team yet. I want to talk about your co-founder. You guys came together pretty quickly. Yeah. Could you break down that story a little bit more and tell us about him? Eno and I, we both went to Princeton together and weirdly we had like 150 mutual friends, but we were a year apart, 150 mutual friends, somehow never had a one-on-one conversation.

40:28Like if you had asked us, you know, way back when, like who the other was, we could probably give you a loose guidance, but we never like really spent one-on-one time together. And, you know, at that hackathon that I mentioned, we kind of saw each other from across the room and it was like, I know you. And, you know, we started talking and I joke that it was intellectual love at first sight because we started, we started talking that day and And legitimately, there's not been a single day since that we haven't been just like incessantly texting each other about, you know, coding and maybe some other things as well.

40:59But the next literally the next day we got we got together for coffee, talked about kind of doing this more formally together and then just got to work building, you know, that demo that we ended up presenting. Eno is so far and away the best engineer I've ever met in my life. It is crazy. Not only, you know, just in terms of technical ability or ability to, you know, go from working at Microsoft and Hugging Face to now like running 25 person engineering and product team at a factory. But he also is really good at behavior change, which is what we're providing to our customers. And the reason is when I first met him, it was only a couple months after ChatGPT came out.

41:38Most of the tools that we know now were not out. Most people didn't really change the way that they build software. but immediately I remember like working next to him he had you know chat gbt up and his ide up and he was doing all these interesting things of like how to make it more efficient to um you know get the relevant context in we ended up playing this game of like you know if you're not allowed to write a single line of code how accurately can you get chat gbt to uh you know get exactly what it is that you want and obviously that entailed you know pasting in the code running the code and pasting in the output.

42:10And obviously that is now what an agentic framework is. But he is just like any new AI tool, even outside of coding, like any new product, AI productivity tool, he is so good at adopting it the second it comes out, which I think is a nice compliment because I'm the most like routine and habitual person. Like I literally the exact same thing every day. I have the exact same like wake up time, all that. And so I think that balance is very fun between us. That's great. You have a true founder, co-founder love story. Yep. Yep. You're proud of it. Very much so. Okay. So how, how big is the team to date?

42:46How, how big have you scaled to? Yeah, we're, we're around 35 right now. Um, and, uh, you know, we started the year at like 15. So. Okay. Yeah. Doubling. Yeah. Should be ending the year at like 50 to 60. Nice. Good scale. Yeah. How are you thinking about composition? Like who, who's part of the team now? What are you looking to hire out for? Yeah. So big thing now is like, you know, obviously we're always in the business of hiring killer engineers. I think something that I've seen in some of the other players in the space is treating go to market as a little bit of second class, which I think there's a very fine line of like engineering is an art that deserves a lot of respect.

43:28But I think in some instances, I've seen some organizations kind of structured that, you know, these are tools built by engineers for engineers. And so it kind of puts them above. And then there's like everyone else. I think for us, something that's really core to the way that we work at factory, you know, we have an operating principle that's built together. And something that's important is anytime, you know, engineering and product ships a feature, salespeople say we, anytime sales close the deal, engineers say we. And I think it's really important because you can't drive behavior change, a 10 ,000 person org, just by having, the best product with the best features.

44:02You do need people to go in and drive that adoption with this go-to-market motion, getting the buyer and the champion and figuring out who the influencers in the organization are. And having a respect for that, I think is really important if you do want to scale to the degree that we're targeting. And so, yeah, for us, building our go-to-market is very top of mind. We're also across the board very much of the opinion that we would rather have one person that can do the job of two, but pay them like they're three. Right. So I think, you know, maintaining that density is really important for us.

44:39Are there any other principles that you've set within the culture? We have a lot of good operating principles, maybe one that I think is worth calling out. So obviously there's the famous Jeff Bezos, Amazon customer obsession. We have a little a bit of a slant on that, which our operating principle is create obsessed customers. It's not enough to be customer obsessed because that's a one way street. You could be obsessed with them and they want nothing to do with you, right? So our goal is really to build something so great and give them such a good experience that they become obsessed with us.

45:15And obviously the only way you can do it, it's table stakes to be customer obsessed. You also need to drive the output, which is them becoming obsessed with factory and what it is that we're delivering to them. Build a cult. Exactly. If you were to join any cult, what would it be? Honestly, I think the flat earthers seem like a, they're a pretty peaceful bunch. They like, there's so many funny videos of the flat earthers, like doing the experiments to test, to prove that it's a flat earth. And like the experiment obviously shows that it's round. And then they're kind of just like standing there and it's kind of like the office where it's just like, and it just cuts.

45:49I feel like it could be fun spending some time with them. flat earthers that's good yeah i haven't heard that one what about you i go between two um i think it would be fun to be like at a furry convention for a day i just think that's an interesting culture that would be that would be wild wild yeah and then the other one is like there's this one video of like this emo group underneath this bridge like doing this like rave dance thing to like mariah's carries like all i want for christ i think about this a lot clearly yeah all i want for christmas and i'm like thinking what would it be like to be like super emo for a day like what i feel like this is your halloween costume like you have to do it i think i should yeah but like what what do you think they talk about like it's just a normal group is it what's the difference between emo and goth i feel like in my head they're the same is it the same okay it's the same thing okay yeah i don't know i'm not sure we have to we have to find out well i don't know if there's an sf emo scene i feel like la would have it for sure i like SF definitely has it.

46:53I feel like SF definitely the furries. I don't know about that. I feel like emo is more LA, but. Maybe emo is like, I don't know. Maybe is that, is that, could that be more South Bay or is that more like East Bay? Like South Bay, like the kids of like the tech execs who are there. He's just like, it's not a phase mom. Not English, you know, really passionate. Yeah. Anyways, I don't know why that went that way. You're building a cult. This is exciting. Yes. Okay. As you build out your cult, I have to ask, are you at a stage? Okay. You're at a stage where you could probably choose between two things.

47:32If you had to pick, would you hire a mercenary or a missionary? Always has to be missionaries. I think it is like the most precious commodity in a startup is the people who are genuinely obsessed and passionate. I'd like to think everyone we have is a missionary. I think the thing that kind of keeps me up at night is like, how do I make sure as we go from 50 to 100 to 500? How do I make sure that we maintain that? Obviously, knowing the reality is like eventually you will have mercenaries. But I think the companies that do a really good job of maintaining that high missionary to mercenary ratio as they scale are the companies that end up doing the best.

48:14We already brought up Brex, but I have to ask the Brex performance question. Brex is all about spending smarter, moving faster and they give you billboards. But for you as a founder, like how do you keep your mind sharp? Like you mentioned you're pretty routine based, but like what specifically keeps you, keeps you in check as an executive? Yeah. I think the biggest thing for me is getting up early in the morning before work and working out. The delta of my productivity on days where I have time to do that versus don't is actually insane. Yeah. Like the morning workout is everything. Um, so that's the, do you track it?

48:52What do you mean? Like my product? Do you have like an aura ring or a lot? Um, I used to use a whoop. I stopped it because I'm so obsessed with like numbers that it was like getting too much. It was just like too much. Yeah. Um, but, uh, also even like I have an eight sleep. And so like my sleep after, if I work out, like every call goes well, every meeting goes well. I feel like we're, you know, making so much progress. If I don't, I always feel like so much slower. I drink more coffee and then, yeah, sleep worse. So, yeah. I just threw out my Apple watch. I stopped wearing it like a couple months ago.

49:25Do you believe in like the RF? You know. I actually studied that in college. Oh, no way. Fun fact. RF. EMF and RF. Yeah. I studied that. But no. Although I did like notice something. Really? Yeah, I don't know. I'm sure I'm fine. Yeah. But do you do AirPods or wired? I switch between them. I like go on really long flights a lot. So like they'll die. I'm going into a rabbit hole I shouldn't go into. Yeah. Okay. Who's one founder that you really admire or look up to? Someone that I admire a ton. This is kind of cliche, but I fucking love Winston Churchill. Okay. I've read so many different Churchill biographies.

50:11It's kind of a, it depends on if I'm like on a walk or I'll typically get an audio book and the physical book and I'll kind of alternate. But Churchill was just such a badass figure in terms of decision making, you know, rallying people together. Also just even before he became prime minister, he had some crazy experiences just around the world. and the kind of relentlessness that he had and conviction that he had in what was right. And then also kind of ingenuity in terms of like getting things done around constraints of the real world with competing kind of incentives from these different parties.

50:52I think he's incredible. Any favorite book? It's tough because I actually, I think there is a current lack of a, of a comprehensive, like the comprehensive ones are like 3000 pages, which is kind of like, yeah, it's like not as feasible, um, to, to do that. But, um, I think probably the most interesting, there's some, I think there's some, uh, there's a 200 page one on his early life, which probably has all the info that you like don't learn in history class about like why he's a very interesting person. Just like from the kind of like individual characteristics trait. I really liked his integration in The Crown.

51:36Did you ever watch that? No, I didn't. It's great. You should watch it. Particularly that season. I don't know which one it was, but it was great. Do you have a founder that you look up to? Elon Musk. Yeah, fair. He can't lose. And he doesn't. Yeah. It's ridiculous. I actually, I remember our, I remember Sean, our board member from Sequoia. right around the acquisition, we were at this dinner and everyone was like, there's no way the Twitter acquisition is going to work well. It's like, it's definitely going down in flames, like all that stuff. And I remember he was like, mark my words, like two years from now, you all will still be using it.

52:09Everyone is going to be like, it's going to be more relevant than ever. And then obviously, you know, here we are. Elon never loses. I have the fastest growth on X. X is the best channel. I only care about X. It's great for Sean. He made a good bet. Is there anything you particularly learned from him? From Sean? I think the crazy thing about Sean is he is so deep on so many different topics. It's genuinely like we'll not talk for like a week and then he'll somehow still know exactly everything that's happened since we last spoke and like the likelihood of what this happened and that happened. And he does all of that.

52:48And he's like really relentless on all these kind of different things that he's working on. And also, you know, really values family, spends a lot of time with families. Kind of always like, you know, we always like talk about that side of thing. And I think it's just pretty impressive how he does it. Also, fun fact about our walk. That guy walks literally everywhere. Like he walks to the airport when he's leaving. What? Like from San Francisco to the airport. With his bag? Yes. He walks? Yes. Like with a rolly bag. Yes. Wait, like, is there a... London Heathrow Airport. Like any airport he's at.

53:21It's hilarious. You should have him on and talk to him about this. I haven't gotten the walking from him yet. I'll have to be the pod on a walk. Yeah, no, it's wild. It is wild. How do you do that? These are questions you'll need to ask him. But that is relentlessness. And I think that's, it's very contagious. That is. Didn't Jack Dorsey do that too? I don't know. I feel like he would walk from San Francisco to Palo Alto. That seems like his vibe. Yeah. There's got to be some paths. Maybe they cross paths. Sean and Jack, they'll see each other. There's some secret tunnel we don't know about. Yeah, yeah.

53:51That's wild. Okay, Matan, as we close out, I like to do some Kalshi markets, some future predictions. Great. Number one, with all of the recent releases, what do you think the best AI will be this month? I'm afraid to admit, I think I use Kalshi a lot. You do? I do. I think - Wow, Kalshi Brex. This is amazing. I swear this wasn't sponsored. I'm tired of Turing. You know, they have 4 million engineers. That's not a bad lead gen. Yeah, we should work with them. You should definitely get integrated with Turing. Yeah. I know them. Yeah. You should put us in touch after. Okay. Yeah. My understanding is that I'm pretty sure Google is at the top there.

54:32The thing is, the one thing that's tough is I'm pretty sure the market is not necessarily for coding in particular, but like a kind of general performance. I think for coding, it's so tough because I think it's so task specific. For my personal coding use cases, I'll probably be using GPT-5 still by the end of the month. GPT-5 is pretty good. Yeah. It's all based on LM Arena. So read the fine print. Yes. Don't forget that. Given that, I was going to ask this after the next one, but do you think open AI will raise their prices this year? Yeah. You do? Yeah. How much? I don't know. I think model by model or it might be, they might do like plant, like certain plans or, you know, they, there are a lot of things you can do to make it not clear if you're raising the price or not by like change, just changing some of the structure.

55:24And, um, I think the unit, unit economics will certainly change. Yeah. So at the time of this, the market price for pro is 20 a month and the price of plus is 200 a month. So if it's any increase on time. Oh, I see. Okay. But what if, what if, and I guess read the fine print. Um, but if they like change what you get for 20 or 200, does that not count? Cause if that doesn't count, then I'll say no, they won't change it. Cause I think people like 20 and 200, but I think what you get with the 20 and 200. Yeah. Yeah. They're just nice numbers. They're nice numbers. What you do is you add another tier.

55:58Yeah, exactly. Like 2000, the$2 ,000 too. Just skip that. Just go with 10x and you'll be good. Yep. Okay. All right. We figured that out. Okay. So we're going to do some of these like IPO predictions. Okay. So CalShe also just added this new market. It's for IPO predictions. Nice. There are some fun ones. I'll bucket them out. Okay. So first, who do you think is going to go public first? OpenAI, Anthropic, or XAI? That's a good question. If you believe in the conspiracy theory that like Elon's using like the X, XAI thing to like be acquired by Tesla and then have more ownership of Tesla. I don't know if you've seen this, but there's a, I think there's a pocket of Twitter that's like really into that.

56:41I'm going to say OpenAI, but I don't think it'll be particularly soon. I wonder what, like how that like restructures them. Cause you know, they're. Yeah. I think, yeah, it's also subject to a lot of. But like that could make it attractive to you. Yeah. See if it just flattens everything out. bit help. We'll just go into broader AI companies. There's Glean, Databricks, and Cerebris. Which one do you think is going to IPO first? I would say Cerebris, Databricks, Glean, in that order. That's the order? Yeah. Why? I've just heard, I don't know, vibe-based. You've heard? What have you heard? No, just vibes.

57:14Just vibes in the ether. These are just vibes? Yeah. What's your take? I'd probably say that's the same. Glean is growing really fast. You don't hear about Databricks too often anymore. But it's like the one that's like, everyone's always like, oh my God, when is it going to... It's like one of those things. Like when is Databricks finally IPO-ing? Maybe they're quiet because they're getting ready. That's a strategy. Yeah. Okay. Latan, it was great to have you on. Congratulations on the big round again. Thank you so much. Thanks for coming on Sorcery. Thanks for having me. Hey, it's Molly. If you enjoy our interviews, check out our newsletter, sorcery.vc where we deliver a once a week top deals and tech headlines email and also go deeper on our podcast interviews subscribe to sorcery today and don't forget to subscribe to the podcast on youtube spotify apple or wherever you listen link in description to sign up

From the publisher

Factory just raised a $50M Series B from NEA, Sequoia Capital, NVIDIA, and JPMorgan, alongside angels like Frank Slootman, Nikesh Arora, and Aaron Levie. The company is pioneering agent-native development with its flagship “Droids” — autonomous software engineering agents that can handle everything from migrations and refactors to testing, documentation, and incident response.


In this Sourcery interview, Factory CEO & Co-Founder Matan Grinberg shares the journey from studying string theory at Berkeley to building one of the fastest-growing AI infrastructure companies in Silicon Valley. He explains why the shift from autocomplete to delegation is the most fundamental change in software development since the move to the cloud, and how Factory achieved real traction with Fortune 500 enterprises like EY, Nvidia, MongoDB, Zapier, Bayer, and Clari.


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