YouSaid · the spoken record

OpenAI Guest

lines on the record: 137
first: 2025-09-16
most recent: 2025-09-16
sittings or episodes: 1
sources: podcast

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“And so at the time, we actually made a very explicit decision to heavily prioritize getting us and the entire company ramped on AI things. And to some extent, like, I don't know if I could have gotten the job that I have here at OpenAI if I was just applying randomly. I think it's because we had built something that was interesting that we were able to like get that attention and have that conversation. So I guess if there's one takeaway here, it's just like just got to build.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And is there some way for me to validate that? Like maybe it's because I can click to the website, or maybe you just have some stats on how many people used it. And then when I talk to them, I'm just like, yeah, let's talk about what you built and how you thought about that. So maybe that's somewhat helpful for folks who are looking for something. You know, I kind of reflect on my journey here to OpenAI, which I'm really grateful for. And I view it as a privilege to be working here. But when I look back to when we were working on the startup multi, it was like not an AI company. And we saw like ChatP come out and we started to follow all this LLM stuff. I remember just feeling like, wow, like there is a chance that if we don't do this right over the next couple of years, like my co-founder and I were talking, there's a chance that we actually just end up dinosaurs.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I don't even look. Actually, now that you, I didn't even realize that I haven't looked at anyone's grades. Admittedly, we're only hiring a few Newgrats. That is the single largest signal. It's just like, what have you built?”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And so it's been interesting just looking at Newgrad profiles. And I totally feel you on the I mean, it's definitely a tough time to be graduating. I don't know if this is advice, but what I can say is that when I look at new grad profiles, for me, the thing that I take the most signal from is if they've built something. And if they've built something that's linked from their profile, and I can just like click to it.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I don't know if I'm allowed to plug myself here, but yeah, we're hiring. But we mostly are hiring very senior, but we actually are, we decided we're pretty interested in hiring like a couple of new grads”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Which is absurd I happen to pick it up in an internship, but there's no class that actually requires you at least at the time, required you know how to use Git. And so I think the computer science departments around the country have to recognize that and make the changes we're talking about. And my hope is that in the term, students will won't wait around for their deans and their professors to do that for them because you can just go and use codecs for free. I think the research we use is literally free. Is that right?”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Gome winter senior year. And I think that's anxiety inducing, it's stress inducing. That has bleed over effects on can you concentrate on this project-based class when you're like also a number of the students were also juggling interviews and were coming to office hours when I thought they were going to be coming to ask about the code or asking like for career advice, which is totally fine. But I do think there's a transition phase right now, which is very, can be very stressful for computer science students. And I think you're right. the faster they're able to onboard to using these tools rapidly and realizing that the cap on what they can create now is extraordinarily high the faster i think they're going to transition into the new economy better because i do think there's an expectation certainly for modern software teams certainly at open ai that like you're just fluent in all of these tools now relative to you know four or five years ago it was crazy when i you know when we graduated through stanford i didn't take a single class that required the user”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“When they picked CS, the assumption was hey, if I do well in the core CS curriculum, if I take a 4.0 GPA and I do one or two good internships somewhere along the way and I apply for a job, At a pretty good deck company. That's just not happening anymore. And it might be because there's a set of layoffs or some overhang from the ZERP era, or it might be because a lot of engineering teams are reducing their footprint of entry-level jobs. But I was definitely shocked by how many Stanford CS grads they were looking for graduating seniors still looking for full-time jobs.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Look, it's hard to parse out from just a final project, but I did office hours with a lot of the students every week. And you could very clearly think the number one. Predictor of their success was their mindset. It was just about they curious and hungry to learn outside of like a traditional textbook. And look, some of them, some of the students just had a lot going on, you know, being a college student is a stressful thing today. And so I have a lot of empathy for there's definitely these awkward moment you're describing right now where a number of the graduating seniors who are graduating with college degrees this year started out as freshmen in a very different economy.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“The back that had made a half hearted attempt, but enough to get a good grade to customize the templates we'd given them, but clearly hadn't asked what is something that now I can create that I couldn't before now that I have access to extraordinary coding agents. And then there was just the classic sort of bottom of the class that I think just didn't accept those tools and think deeply about like trying them, using them, learning with them, developing a field for what they're good at and what not good at, and kind of turned in a final project that would have been totally possible to build a year ago.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And ship it. And they were allowed to use any coding tools. Obviously, in fact, we gave folks some credits to Mistral models and Black Forest models and the founder of Cursor came by and kind of talked about the ID and why they should all be using it. And what was extraordinary was it was so clear that the distribution of the final projects followed this power law where the top four or five teams that really adopted wholeheartedly the coding cursor and the AI models and did a fully sort of AI assisted workflow of their final project, like produced software that was production grade ready if I was still running the platform organ Discord, I would have totally shipped four or five of those on the front page of the app store we had. In fact, I sent some of them to the founders of Discord and they were like, we should probably ship this. The quality bar was just extraordinary for something they were able to build in basically a 10-week quarter. Then there was this sort of, you know, usual sort of middle.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, at teacher class CS143 at Stanford every year this year we taught it in winter quarter and we had about 300 students and I was thinking through what was a, in previous years we had a midterm and we had like problem sets. And this year we decided just to have it be a combination of speakers who are CTOs or folks, researchers in AI come in and talk about the infrastructure problems of building AI products at scale. And then we had one final project where everybody had to build an agent.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, and then I would probably encourage them to use these various tools so that they're picking up the skills. And, you know, I don't know, I don't know. This is just an idea in my head, but if we could help them kind of like speedrun through that arc. Maybe every quarter they're using a different set of tools. And so they're becoming very mentally plastic in terms of how they get things done. And I think that would be the best simulation of what future work would look like. I'm not sure what you would do.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And then, you know, similarly, I would have like a handful of classes where folks do things like very manually to understand what's going on behind the scenes and also to build the confidence that they can. But then generally, I would move towards having students trying to deliver some kind of like outcome, be it like they've learned something or they've built something or something.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And if you were, having seen what you have with Codex, knowing what you do about where it's going, let's say you were the chair of the computer science department at university, what would you do differently now versus before when Codex launched? Well, one is you'd allow kids to use the AI tools. But let's say you're thinking about the future of computer science education and how that should be taught over the next 5, 10, 15, 20 years. What would you do differently”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Have some foundation that you can build upon as the world evolves around you. So I think similarly, if I had a child in late high school, I would just want them to crush whatever it is that they're doing. And it wouldn't really matter what specific thing they've chosen. Eileen Technical, so that would be cool. But like maybe even that is optional. And then I would just raise them with the expectation that they'll probably have like many career transitions throughout their lives.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Because I was more interested in healthcare. Right, you know, and now you do investing, right? And like I studied mechanical engineering and then I changed to CS and now I work in product. In AI at OpenAI, but the startup that I had started was not an AI company. So things are constantly changing. And I think the most important thing is to be agile, curious, and like.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“So I'll answer this with humility because I don't have kids, but I do think about this. And actually, I think my point of view would just be that the world has always been changing. It's changing now, but it was changing before that. Maybe it's changing a little faster. But that's the main thing to notice is actually the pace of change, not the specific change. And so I think the most, you know, if I had a kid at late high school now, I would probably just be trying to encourage them to just be like excited it is about whatever they're doing and like be incredibly curious and constantly learning, right? Like I studied CS. Did you study CS as well?”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“First off, it's a good point on the actual integration work probably requires humans. I would say, yeah, if it's especially if it's in person type integration work or like complex, then I think you're spot on there. Industries that are out of bounds. I think it's like a hard question to reason about because we are building general products. And so you can kind of use ChatGPT to answer any question already today. So I wouldn't say there's like bounds, but it's more like focus. I would say, you know, right now OpenAI, we're very focused on like consumers generally and like being really good at coding. Know there's some other things too, so I would just say, yeah, the more maybe we should just not even have this answer in the podcast. Yeah, we could.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Point. Now, ideally, over time, I guess you're saying the model should, the product should just get good enough at integrating into the customer's environment. But sometimes for regulatory reasons or otherwise, you just need a human there. Are there some industries that clearly, do you feel like out of bounds for OpenAI? Because that just is not on the path to AGI.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Well, let me push back on that for a second because it turns out that in many industries, serving the customer deeply, like you're describing, often requires a human touch that might be sales, it might be solutions engineering, it might be customer support and so on. It does sound like what you're saying is you would certainly keep your engineering team very small and minimal. But if servicing the domain required more of the human touch, then that you would scale. Because if it required Often my experience is that getting an agent to actually work in the enterprise and the legacy industry requires going in and doing a fair amount of integration work, at least up front. So maybe it's a setup thing, right? Upfront, you parachute somebody who understands how to get an agent up and running. And then you can leave because it's really just for them, for the customers like consuming teammates like you were saying earlier, but maybe where you do need people is that integration.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And then I think the other thing I might do is I might keep my company really small. So rather than doing the classic hyperscale thing, I would try to use agents as much as possible. Be as small as possible so that we're just agile and nimble. I guess this is probably like just the sort of age old advice, but.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“It sounds like the last mile connective tissue between an industry where you have deep domain expertise becomes more valuable, whereas the first mile of like all the general purpose parts of an agent's flow, you basically, you should assume you should offer that to OpenAI.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Then we had to go collect a bunch of those type of tasks or invent those tasks. So, again, like train the agent how to do it and evaluate how well it was doing. So I think that, again, for a very specific industry, I don't know, I'm trying to come up with an example. Let's say accountants, but in a specific region of the world where there's like a specific set of rules, like they might have very specific tooling that's provided by the state for doing that accounting, right? There might be very different kinds of base knowledge and documents available. And then the way you need to do the work might be different. So, I mean, I think it is a very good question, and I'm not 100% sure what I would do as a founder right now. But I think that I would try to lean really hard on very good customer knowledge and less hard on product.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Agency uses and train on and like and then use it test time. So that's hard. And then I think the task distribution is also really interesting. Like Codex, we have a lot of intuition for what a good code and task could look like and like kind of where to draw the boundaries. Today it's like provide prompt and then you get an answer or a diff that you can turn into a PR. But like those are some decisions we had to make around what the boundaries of the agent are.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Various amounts of dependencies even installed, like varying amounts of unit tests. We actually, the startup that I sold to OpenAI was like multi, that's how I joined. And we had very few unit tests on a lot of our code. And it's like kind of funny. But that's realistic. That's like a real startup code base So actually, if you wanted to do that for some specific function, I don't think it would be easy for us at OpenAI to create that many environments.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And those aren't things that OpenAI is going to like. Generally do for like every industry, right? Like coding happens to be of particular importance to us just broadly, but even within coding, there's a lot more specifics, specific areas. So just to really spell this out, if you think of the environment, like it's really, you know, training codecs was like really non-trivial to like figure out how to give the environments different, how to give the model different environments to train in, you know, with like different kinds of realistically dependency setups.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Obviously, give it to customers. And the interesting thing about it is that those latter three things, right? The tooling, the environment, and the task distribution, like I said, the customers, so four things, whatever. All of those things are very much based on knowledge of a customer.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Okay, so if I was leaving OpenA today, probably the market changed that I would be thinking the most about, or one of them would be agents. Okay, great, not super controversial. Then I would think, okay, like we were talking about earlier, an agent is basically like a really good model that I'm probably not going to build at my startup. And then I need to give that model access to tooling in an environment. And then I need to like figure out what tasks it needs to be good at.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“So you've been a founder before. One of the scary things about hearing OpenAI going from being serious about models to all sorts of products is if you're a founder in this space and you want to build something interesting in the coding space, there's this tension looming, right? Which is anything I'm going to build just going to be subsumed by OpenAI's products next year. So how would you think about that? If you were leaving OpenAI and starting a company today, what would you do and what would you not do?”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“And so, whereas before, we had these amazing models. You could use them in whatever tool that you want to use them in. Now, definitely, I mean, a lot of the stuff that I'm working on is thinking about like, hey, actually, there's a lot of, you know, as we build agents, there's a lot of value we can provide by not only thinking about the model, but also thinking about how the model is like useful to you in a certain form factor. And actually the form factor really affects. Everything. And so, yeah, we're spending a lot of time and effort building even better coding models and even better coding products, particularly focused around agents, but even beyond.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“I think ChatGPT is in fact an amazing and large business, and it's super cool to work at a company that is really distributing AI Like a giant number of people. But yeah, we are incredibly serious about coding. And in fact, we always have been, you know, since the first Codex product that was powering GitHub co-p All the way through with our models. I will say, though, I think people are noticing we are getting, we've always been very serious about coding models and we're now getting like very serious about coding products as well.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“There's this narrative violation I keep hearing about folks in San Francisco that, oh, you know, OpenAI is all in on consumers because the rise of chat GPT is a consumer companion has been so extraordinary. But clearly our entire conversation is an exception to that story, right? Because almost everything we've talked about has been focused on developers and governments. Why is that misconception there?”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Kind of the way we've kind of thought about building is the most important thing is to build to AGI and then distribute the benefits of that to all humanity. And so we're kind of like leaning towards the like, okay, the primary thing is the like fully, the thing where we host it for you, contain the environment and everything. And it's kind of in parallel, we have this like sidetrack of like, okay, and like, how are we going to make sure that today, you know, you can use codec CLI. You could use that in a, I guess, relatively air-gapped way. Obviously, it needs to sample the model. And then as we build new capabilities into Codecs and ChatGPT, how do we just make sure that if you're running something like CLI, you can get the most of all the capabilities as they can.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, I think it's interesting for me playing this through my mind as we, you know, as we're working on codecs, I do think there needs to be an answer for like, you know, how do you use this agent in an air-gapped environment? How to use this agent, like, you know, those critical industries, and then there's just many large companies who have incredibly stringent security needs.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Those scenarios often need a slightly different, like the ergonomics of code are different. They're very on-prem. They require a level of air gapping from cloud systems that modern software engineering workflow doesn't lend itself to. And so we may see this bifurcation of codecs as a family. I'm curious over the next few years, the military requirement, or let's call it the critical industry needs of modern autonomous coding agents might require some pretty basic architectural differences than the, you know, let me ship the latest and greatest of our next version of our software product on GitHub. I think it's a coincidence that the last time we saw a huge adoption in IT infrastructure on the world was the Cold War. And now we're living through some pretty unstable times, both in the Middle East. And I think that is causing governments. I think the US has always been somewhat forward.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Drone warfare code bases that interact with air traffic control systems, with UAV planning, with mapping. Those are the code bases that are most urgently being upgraded. I think in other parts of the world, there's just a desire to modernize. So if you look at the UAE or the Kingdom of Saudi Arabia, we talked about how the UAE rolled out, is rolling out ChatGPT to the entire country. I think that's coming mostly from a top-down directive to just embrace the AI future that's coming rapidly. Basically, the more AGI build I find the head of state is, the more rapid the adoption is. Certainly for ChatGPT-like tools, but also coding, that's not driven by some military function. But then there are other regions like Europe where for sure geopolitics accelerating all that. And I've talked about this before, but usually.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“So for sure the geopolitics has accelerated adoption for a bunch of governments, right? In Europe, the Ukraine crisis has forced a lot of governments in that region to go, wait a minute, like our air traffic control systems, especially an age of unmanned sort of drone warfare, it is crazy that when there's a bug, we need to call in some legacy contractor who built it like 20 years ago to come and do some on-site maintenance, right? That's been a wake-up call. And so you're seeing these like, there was a, there's sort of an 800 billion dollar defense bill that your past six months ago. And the most urgent adoption is certainly happening at the intersection of legacy code not working and battlefield needs.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“So, I'm curious if you mentioned some of the companies or governments or systems that you're thinking about kind of had this one time upgrade for military reasons and then never upgraded from there. I am curious if there's like a specific reason that they all want to upgrade now that you're seeing or if actually we're still kind of in the state of like there's no forcing function. So like although it's easier to do there's still no impetus.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“I have a question about that actually. I'm kind of curious. So a lot of the larger companies that we talk to, their use case is very different. It's not like building new features, right? Is what we see like most of our users using us for, but it's refactors, large refactors, and replatforming”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Especially mission critical industries, where there was like a one-time software upgrade largely driven by military scenarios. And then we never modernized all that infrastructure since then. So that's why I think the cybersecurity side of this, the safety evals that you're talking about, I think over time will come to be seen as having been very prudent because the thing that puts all of that adoption at risk is having like one terrible incident that then changes the risk posture for a bunch of enterprises.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Whose IT infrastructure is just newer to adopt agents, they're still legacy. I mean, the vast majority of us running off and on-prem and it's not modern, you know, it's certainly not TypeScript, but it's easier to upgrade from systems that were written in C++ to Python than it is to go from Cobal to 4Pran or whatever to Python. But if there's anything that makes me super excited that these economies will merge, it's autonomous agents, right? Doing all the plumbing work and doing it for a fraction of the cost and time that these mega sort of consulting companies have started to charge. And frankly, many of them don't end up ever completing a project. They just turn into a boondoggle. So I'm very excited about that part. And that's why I think AI is going to eat software, because software did, the modern sort of startup economy and digital economy, software ate really fast. But there were other parts of the world.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Training data on Fortran and Cobola and so on, then the one time upgrade costs should fall and we should see ideally this is my hope is that tools like Codex modernize that entire sort of legacy code economy. And then we get to upgrade everybody onto like modern software engineering, right? It's tending to happen from what I can see now in countries that get to leapfrog legacy infrastructure because it's starting from day one. And it's very similar to like civil infrastructure like roads and highways and so on. So if you go to a country like Singapore, which is a much more modern country because it's barely 60 years old, it only got its independence in the 1950s, then they didn't have to build the roads and so on that Britain did and then upgrade them all, which is like refactorors suck and they take way more time. If you could just start from sort of a clean slate, it's much easier to modernize. And so what I'm finding is that it is easier for countries.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“That were set up in post-World War II or in the Cold War with the default assumption that everything had to be locked down. Often these code bases are running big parts of critical infrastructure like the railway system of an economy or the air traffic control system. So very high impact and high stakes code. They're not modernized whatsoever. And they're constantly rotting because of debt, technical debt. And I think one of the most exciting things is that the one-time migration cost to modernize these code bases now has collapsed precipitously because agents can do so much of the plumbing work that typically would hire some system integrator, Accenture, Deloitte for a 10-year contract where they'd come in. This is part of the founding thesis of Doge, right? Which is like just vast parts of the American government in IT infrastructure is like super legacy. And we're getting overcharged as a country to modernize it. And agents go in and are, as long as we can get enough distribution.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“No, I think that's right. I don't think people often talk about the coding economy as one homogenous economy, and the reality is there's multiple sub economies, but they're at least two big economies, which is there's the, for lack of a better word, there's the digital native companies. These are technology companies usually born in the post internet era where they grew up, where either the founders or most of the vast majority of the team has grown up natively understanding how to do modern software development. The default assumptions when a code base is initialized is that it's going to be, you're going to use Git for version management. There's going to be branching. There's going to be good review process and so on. Sort of modern software teams. And then there's the vast majority of actually the world's mission critical code, which we talked about earlier is Fortran, COBOL, like running on-prem in these massive ETL systems, Virginia or in parts of Europe.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“That's a really tough question. I sort of changed my mind every time I answer it. So maybe a slight cop out. And then I'm curious for your answer too would be that there will be teams. Whom 90% of their PRs. Written by agents. But I don't know how quickly that will spread. This is a common thing with AI. It's like we live on, like, you could call it in the bubble, you could call it on the cutting edge. And so we're just adopting everything rapidly. But then it takes a while to like. Or DFGs out. But I think the cutting edge will be at like 90% on teams.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah. So I think that Big unlock for agents at work because there's like streams you can subscribe them to your communications tool. And in personal life, I think that might be a bit slower, but we'll see.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Yeah, but like it's similar if imagine you hired a teammate and then the only time they do work is if you specifically tell them to do a task. Then they would just be very underutilized, right? But what makes a great teammate great is that they kind of tell them what their job is and they just start responding.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“Because what I realized is that obviously we need to do a lot of model improvement, but I also saw how this just concretely a lot of normal product work to do. Set them up in the right way. And then that normal product work will then pull the models into being more and more useful. So I think like by 2027, like agents will just be absolutely ubiquitous in the workplace. I think in personal life, it might be a little bit slower because in personal life, there's less of these constant pipes of signals of things to respond to. The reason this matters is that if you think of chatGT, you just have this like input box, right? And like most people. Including myself, probably use it for like 1% of the things that I could use it for because I just don't even know to use it in that way or I don't prompt it right”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source
“I am pro thinking about it. You know what I mean? Like, I don't think we're at a point where it's obvious, but it sounds kind of crazy, but I feel like it's a question worth considering every now and then. More concrete.”
2025-09-16 · a16z Podcast · How OpenAI Built Its Coding Agent · IDENTIFIED FROM THE TRANSCRIPT · source