20VC: Codex vs Claude Code vs Cursor: Who Wins, Who Loses | Will All Coding Be Automated - Do We Need PMs | The Real Bottleneck to AGI | The Three Phases of Agents and What You Need to Know with Alex Embiricos, Head of Codex at OpenAI

23:04And so not only do we encourage people on the team and elsewhere to just ask Codex to review, you can then also set it up to just automatically review. So nearly all code at OpenAI is reviewed by Codex automatically whenever you push it to a good repo. Actually, one fun thing for people who haven't tried Codex yet or didn't try it recently, sometimes the way that people see how good our models are is by asking Codex to review a different model's code. And basically, they're like, oh, shoot, I should probably just be using Codex to write my code in general. You said something really interesting there.

23:32You said for those that maybe haven't tried it yet or coming back to it, how do you think about retention with this category? I remember Tom Blomfield, who's a YC partner, tweeted months and months ago, but it stuck with me, a weird brain, about the ease of transition between different providers, whether it was cursor or ClawCode or Codex. I can't remember which one it was, to be honest. But how sticky are users and how do you think about retention? We've taken this kind of counterintuitive approach with Codex to just build it super openly. So the Codex core harness is open source and we're always trying to make it easier for people to switch.

24:06So for instance, when we first launched Codex last year, we created like created as even a heavy word. It was just we just established a convention, which is called agents.md. This is basically a file that you can put instructions for the agent in. And we didn't call it Codex.md. We just wanted it to be something that all agents can use. And pretty much every agent except Claude uses agents.md, which is awesome. And then just last week, actually, we helped push for putting skills, which are a standard for like giving the agent instructions and scripts. We push for those to be sorted in sort of a neutral named folder called agents instead of in like codex or something.

24:40And again, everyone has jumped on it except the usual suspect. I think it's really great for the developers to have a lot of choice. And we're trying to make it even easier for people to try different things. Now, that said, these coding tasks, right, where you're asking an agent to write some code, they're quite hermetic. And what I mean by this is maybe an analogy in TV would be like episodic, right? You can come in and you've got this open-ended agents file that any agent can read from. You've got these skills that any agent can use. And you can ask the agent to write some code and it produces a patch and that patch goes into Git.

25:10So kind of like both ends of this are pretty neutral, vendor neutral. So very easy to move between for now. As agents start to do work that is not writing code, but more general work, again, for software engineers or beyond for any builder, they're going to need to start interfacing with other systems. So as they start, maybe your agent is talking to Sentry, right? Or it's talking to your Google Docs or something. Then I think these agents become much stickier because actually deciding to connect an agent to that system is a sticky decision. And if you're an enterprise really trusting that the agent is going to have access to these tools, but there are really good secure guardrails and sandbox and like controls over how the agent works with these systems, I think is critically important.

25:50And that's not something that you're going to want to do multiple times. And so, you know, we've been kind of building Codex knowing that this is coming. And so we have like the most conservative sandboxing approach. Sandboxing is kind of like a set of controls, OS level controls over what the agent can do. But I'm a fan of Seven Powers, this brilliant book, which talks about kind of seven ways that businesses accrue value and sustainability. And like, you know, your stickiness or your retention is one. if we're on the same team with Codex, how do we create retentive patterns, behaviors, programs to ensure that people stay with Codex and they don't flip to cursor when there's a better model or claw code when there's a better model?

26:27Yeah. I mean, it's interesting because I think on the one hand, like we think about this, obviously we're running a business, but you know, our mission here is to like ensure that like we safely deliver the benefits of AGI to all humanity. And so something that's like unintuitive to people about like the Codex team. Alex, you actually, I know, but your job is the success of Codex. I get that. Our job is the distribution of intelligence. And so we're obviously building out Codex. And this is really unintuitive to a lot of listeners. But we put all this effort into training these models, and then we serve these models to our competitors.

26:58And from our perspective, this is so difficult for me as a venture capitalist to understand. You are aware of this. Yeah, I'm totally aware of it. It's like where OpenAI is like a really interesting and unusual place to work. But basically, because we're playing such a long game for us, if the competition gets better, we learn. It's actually helpful for us. And so we're pushing really hard at growing Codex. You learn because if they're closed and they improve, you don't learn. I don't think so. For example, there are a bunch of recent launches. Like even today, I literally just like quote tweeted a thing this morning about a launch from Warp.

27:33No particular affiliation, right? And there are a bunch of cool ideas in there about how they like framed up the way that their agent can work in the cloud at the same time as working locally. And for me, that's like inspiring. And I think I see all these things from various companies. And like one of the coolest things about the space is it's like we're all kind of inevitably reaching the same conclusions together and then building things out. And so, you know, on the Codex team, I think we have some massive advantages, right? We have the massive distribution advantage with Chat2PT. We have the massive like capability advantage of training our own models to be good in our harness and building our harness to be good at the new models.

28:05And like no one else has early access to those. And so I think we're playing to win and we have a really big advantage or a number of advantages, but we're also playing this long game where, you know, again, we serve our models to everyone, where we push for open standards so that everyone can use like all the things that we're pushing for as well. Can I ask you, what will be the defining factor of winning? And I know I'm using venture language and you're brilliant and kind of much more free and open, but what was like the defining factor of winning? Again, if I push you, is it like GTM, which is like the biggest enterprises in the world do want to work with open AI.

28:39I have many friends in your sales team. The inbound that you get from the largest brands is incredible. So GTM, because of the incredible brand, product execution and just codex being a freaking awesome product, or compute, inference, speed, actual compute advantage. Which one is the defining winner? Okay. So I think if we're going to talk about it more from an open AI perspective, obviously this way above my pay grade, but I would say it's compute advantage and having the best models. And in order to achieve that, we then need to build businesses that generate revenue. And also that something that's really interesting, we noticed with having the Codex team, which is a sort of combined team of research and product, is also by building these successful products, we create a lot of pressure to improve the model in sort of a faster way.

29:27That's maybe the company perspective, right? If we come to the product perspective, I think the single most important thing we can do is build a really good product that people want to use. And like I was saying earlier, I think we really want to build products for individuals and then allow people to become fluent in those products and then pull in automation. And I think that may be counterintuitive, but will result in way more impact than anyone purely approaching it from the enterprise workflow perspective. I think that's mostly a question of product execution. And then that works for, say, prosumer.

29:59When it comes to enterprise, the go-to-market side is really important. Something that I've learned the hard way is if we go to an enterprise and we're just like, hey, we're here, feel free to use the stuff, that doesn't work. There's actually quite a lot of education that needs to be done. And there's a lot of configuration that we need to support and education of the broader team. So that motion looks much more like coming in, pitching, meeting the head of developer experience or whatever, understanding how they want their team to operate, and then giving them tools to propagate that mechanism of operating to the rest of the team.

30:27You said the word revenue there, which is one metric to measure a business against. When you think about like your metric of success, which you sit down with Sam or Brad or whoever it is and say, hey, this is what we're optimizing for. What is the metric that uses the defining North Star for your progression? It's actually not revenues. The primary is active users. How do you measure active users? Like daily active users? Yeah. So we measure weekly active users. And it's, you know, did this person like actually do a turn in our product? You know, did they send a prompt? Is weekly active a frequent enough metric, do you think?

31:06Sounds nice. But if this is actually replacing the IDE, is daily active not better? I think daily active will be better soon. We just happen to use weekly active. It's like a standard here. And I think as we were getting started, it made sense. But I actually agree with the criticism there. It's like, we should probably just be a daily. Like, I think we need to be getting to a world where for any given task that you have, your first instinct is to ask an agent to help. It's kind of like, you know how like with Google search, it's just like, okay, anything I need to do, I just like go into this text box and I can get navigated to the right location.

31:36Then you had ChatGPT. It's like for any information I need, I can go into this text box, type it out and get information that helps me. And I think the next phase that we'll see this year is like for any task I need to do, as opposed to just get information, I go to this text box or this input and something happens that helps me, even if it's not the full task, even if it's only a small part You said about kind of chat that, again, I jump around, sorry, my brain. My mother has to walk with me around London and she like deals with this manic, episodic brain. But you said about chat and the interface there.

32:06I'm really fascinated by this because it is a seemingly incredibly efficient input function for busy humans. But I spoke to Anish Akaya, who's a GP at Andreessen, and he came out the other day. And he's like, no, no, no, this was created by Sam and Elon and it works for very efficient people. but most of the planet want browser-based discovery interactions, UIs. Do you think that chat will be the enduring UI in the next wave of AI interaction with humanity? The simple answer is yes, but actually I think there's two components here. Like if we just imagine the future, like just like let's think of some sci-fi movie, right?

32:40Like what does AI look like? I believe that sci-fi is a really good predictor of what the future should look like. And usually it's pretty simple because it's a story. And I think simple is usually right, it's going to be some just like entity that I can talk to however I want about whatever I want, right? I felt like I shouldn't have to navigate to a place where I work with like my coding AI. And then I have this like different place for my like sales AI. And I have to like be like, hey, I'm now talking to sales thing and like do that. It's just like, I just going to talk to a thing and it's just going to help.

33:08So I think what we're going to have is that we'll have chat or voice, basically conversational interface will be sort of the pillar of everything that you can talk to about anything and that you can add into any group chat or whatever so it can like discover how to help you. But then if you're like a power user and you're very good at a specific thing, you probably don't wanna be disintermediated by having to talk to another person. It'd be like if you had an executive assistant, but you can only work by talking to them. That's like super annoying, right? So at some point you wanna get to the show notes and like look at them yourself and like edit them yourself, right?

33:39You wanna edit the thing yourself. So I think we'll pair chat with like functional like graphical interfaces that are bespoke to like what someone needs. So like in my case, I will probably chat to like do my, you know, podcast prep. But when it comes to like actually looking at product and code, I probably want like the Codex app that I can go into and get deep in, right? Whereas maybe if we're talking to a marketer, maybe that marketer will like chat to ask questions about the product. They're not gonna download the Codex app just to ask questions about the product. But maybe they'll have like a super custom GUI for like ad analytics or something that they go into.

34:10Totally get that. And it kind of wrongly assumes on my behalf a consumer interaction at some point in that journey. And I want to ask you, how do you think about agent-to-agent experiences and designing experiences for agents? We spoke about, for example, going into large enterprises and how you can be helpful. I'm just using the most boring thing ever, expense approval. You could have agent submission of expenses on my behalf for my trip to San Francisco, and then the agent on the flip side doing approvals for that from OpenAI's compliance department. How do you think about that and that paradigm shift?

34:43That's interesting. You know, to be honest, I'm not sure what that's going to look like. My quickest answer to this is that we've noticed as we build Codex that the best interfaces for Codex to do work also tend to be the best interfaces for humans. So when people ask, oh, how can I make my code base more efficient for the agent to work with? The answer is often like, well, have you looked at it yourself? And is it easy for a human to work with? So a very specific example would be running tests in a code base. Naively, if you just set up most test runners, they just emit all the outputs of all the tests.

35:17And so as a human, it's really annoying because you have to go in and find the one that failed. And it's like, you've got to read hundreds of thousands of lines. Turns out that's terrible for AI as well. But if you filter it down to just only emit the failed test, better for humans, also better for agents. So probably the agent-to-agent interaction points will be very similar to if there was a human in the loop. And that's nice because it means you can kind of atomically replace individual systems. I mentioned our show on LinkedIn and a wonderful investor from a different company. It's like Harry Potter, you know, Voldemort.

35:47And it's like, you know, he who shall not be named. I don't want Sam to kill me. But from another company, you ask him, how do you think about a coding data moat? And does Anthropic have all the data now? I definitely don't think they have a significant advantage in terms of data on coding. I think that from what we've seen, and I would defer to my research team on this, but I feel like we have plenty enough data to build really good coding models. I actually think the place that's more interesting for getting data now is as we get into knowledge work tasks, that's kind of data that's not really available most places on the internet.

36:25And so you start to have really interesting brainstorms for how to help a model be good at it. Maybe you have to pay people to simulate doing tasks so that you can learn these trajectories for the model. Maybe you should acquire startups that are no longer a business but have a lot of data, like say they're Slack or something. Yeah, I think that kind of knowledge work task distribution is much harder than coding. That's so interesting you said there about the data that doesn't exist, so to speak. How do you think about your interactions with the data providers, your McCaws, your Turings, your Invisibles, your da-da-da-da-da-da of the world?

37:00Will you spend 10x there Or will you go, we are spending too much on data. We should do it ourselves and do data acquisition. Yeah, I mean, I think the way that we think about these things is just like, how do we move as quickly as possible? And so becoming able to set these things up in-house is like very expensive in time. And we're a small team. So what I have observed so far is that if we need to run a data campaign at scale, we're usually going to enlist help from one of these companies. On the consumer side for Codex, we've spoken about enterprises and going into them, how to engage in terms of developer experience, developer relations.

37:34Do you compete with a lovable and a rapid on a low-end consumer basis in a year or two's time? Is that a business where you're like, you know what, Codex is not for every person to create an about me or a small business to create their own site? How do you think about consumer in that way? Yeah, I would say that right now it doesn't feel like we're competing super directly. But I don't know if you saw our Super Bowl ad, the tagline of which is just, you can just build things. With the app, we noticed that many people who are less technical are starting to build things. And so the kinds of things they're building are much more hello worldy.

38:07And so I think that we will see some overlap in use cases where you have people just pulling up codecs because they have it as part of their ChatGPT. Actually, a big announcement last week was that we're now offering some codecs to people even on free ChatGPT plans or on the Go ChatGPT plan. So this is massive just in terms of like bringing availability to everyone. And so I think we're definitely going to see people with like a free chapter PT plan coming in and just like building simple things where they otherwise might have gone to a specialized tool. What would you most like to do differently, but for whatever reason you can't?

38:39I feel like it's been a very good few weeks for us. So we're very, I'm pretty jazzed about everything that's happening. Yeah, that's really interesting. You said it's been a very good few weeks for us. And I feel that. does the team feel the changing winds of momentum, both in positive and negative cycles? Absolutely. We are very attuned to it, right? Like if you look at the history of Codex, the first thing we launched last year was like this amazing idea that people were super excited about. It's like, hey, we're going to give the agent its own computer in the cloud. You're going to have as many of them as you want work for you in parallel on tasks.

39:13Super great idea. To be honest, it didn't work as well as what we shipped later. It was not the best. And then since August with GPT-5, we started pushing really hard on interactive coding, which is where most of the competition in the market is. You know, we went on an absolute tear. I feel like the public metric we had was like since August, we grew by like 20x. And then like even like late in the year, we like doubled from December to now. I forget the exact number there. But like that was competing neck and neck. But the shift that we feel last week is, you know, we, we felt like we had the most intelligent model that was cemented with five free codecs.

39:48We had feedback around our model being slower and like maybe less fun to work with. And like being less good at communicating with you while it was working, we address that feedback. And that's true, even compared to like the other competitor model that launched like 20 minutes before us and was like, maybe this is spicy. It was like soda for 20 minutes. So I mean, state of the art. And then we'd always been getting a lot of feedback on like the quality of the user experience in codex our most popular surface was the ide extension and our cli which is a command line interface was less polished but with the app the feedback has been like resounding from the market that this is like a really high quality experience it's like simple like unintuitively simple and people are just loving using even our biggest credits are converted so yeah and then we and then we had the super bowl ad and then we went to free and so going back to your question of like what am i most want to do differently i have two things for you.

40:36The first is I actually want to get back to cloud. When we pivoted our strategy from like focusing on the cloud agent last year to working interactively, the thinking was very simple. It was just, and it's kind of like what I was telling you about FDEs actually. If you go too far ahead to workflow automation before your end user is fluent with the tooling and can get it to work simply, then there's like this disconnect and you just have this pipe dream idea that's not like effective except for the most power users. But once you have this base where people are using your tool every day, and they're configuring it, and every time they use it, it gets better, then the step up to letting it run independently in the cloud is a much smaller step up.

41:10So I think it's time for us to get back to building out the cloud product and making it super tightly integrated with the local product. It already is somewhat integrated. And the other thing I want to do differently is start thinking more about the bottlenecks. Like CodeGen, writing code, has become basically trivial now. But the hard part is what you were talking about with code review, right? How do we know the code quality is good? How do we know we're doing the right things? And those bottlenecks, I think, are underappreciated still and underinvested in. So I think we want to get to a world where you can have an agent that is unbottlenecked, that you trust to own an entire microsystem or internal tool or whatever, and can do the full iterative loop, including feedback from users, without having to go through human review.

41:49And that is a really hard problem to solve, both from an intelligence perspective, but also from a safety perspective and a controls perspective. How much weight should we place on benchmarks and evals? Probably, this is an annoying answer for you. It's like some, right? Like they do tell you, in my mind, they give you a good measure of intelligence. And so you can put weight on those for intelligence. And especially before evals are saturated, I think when you see meaningful progress in those benchmarks, it's like very, very helpful. And then I think you have to pair that though with like what it feels like to use the model.

42:21And that's a vibes thing. Like whenever I talk to any, even internally or even talking to like customers of our models, I'm always surprised by how vibes-based the evaluation of how it feels to work with a model is. How vibes-based life is. People want to work with people they like is the lesson that I give to kids. People want to work with models they like. Relationships matter. Can I ask you, I think that Cursor will lose half of their revenue this year. I think we'll go from a billion to 500 million. It's a bold statement. Agree or disagree? Oof. Can I just like no comment?

42:59Yeah, you totally can. I don't know. I think it's really hard to say. Like, more serious answer here is just like, I think they've built a really successful business. We see them a lot when we're in enterprise. Do you? Yeah. Or is it just Cloud Code? Because I don't know anyone that hasn't. No, I see Cursor a lot more than Cloud Code. And it makes sense to me. My sort of narrative for this is that you have to meet people where they're at. For most people, like they're used to using an IDE. They've been used to using tab completion even before there was AI, right? Like top completion existed pre-AI and then AI just made it better.

43:32And so I think what's like coolest about Cursor from my perspective is that it meets developers exactly where they are. And it's a sort of a switch. It's like you used to be using VS Code or something, switch to Cursor, almost nothing is broken about your workflow. Everything works, just certain aspects got better. And obviously VS Code, I still use VS Code. There's like reasons you might like it more and they're improving rapidly as well. But I think that pitch from Cursor lands well with a lot of people. And so, you know, the bet on Cursor, I think, is that they can like continue meeting people where they are and then like ladder into these more advanced agentic features.

44:03You know, that relationship with the customer is valuable and it's hard to I don't think that goes away. Do you think it was the right strategic decision to start building their own models? It's hard to say, but I feel like there is a bit of a gap in the market right now for that kind of model. Again, if we think about what is the thesis, at least my thesis, you know, I'm not like super close to like working with Cursor or anything, but like my thesis for like how they win is that they meet everyone where they are and they like make it really easy to like step up into using more advanced agentic workflows.

44:32Maybe they noticed that the models that, for example, we were putting out or some of the competition we're putting out were like kind of slow relative to what their customers wanted. You know, my first magic moment in Cursor was like when I hit command K the first time. That's like a feature that lets you select some code and just like edit it in line. And I was like, this is incredible. Right. And so if they noticed a lot of their customers want to be able to kind of pair with the AI and then maybe after pairing with the AI for a while, then they start doing more delegation and then they move it to the cloud.

44:58Then there is a gap for that fast model that they trained. So I think that makes sense in that context. In terms of like market composition, as an investor, I have to think through how do I think about the eventual state of this given market kind of a terminal state? How do you think about that? Is it like Uber and Lyft? And like the majority of the market will be on Codex or Claw Code? Or is it like AWS, Azure, Google Cloud, and a 33, 33, 33? Okay, so I think this might end up with fewer providers that are capturing a lot of value in the long run. And here's why. And maybe this is a bit spicy, but I think that we are kind of in this temporary phase where we have agents that are really good at coding.

45:41right and if you look back last year like maybe more people thought we would have agents that are good at other domains too but that didn't happen last year so we only have pmf for coding agents like in the industry overall i would say right and then there's some like very narrow other use cases like customer support etc but i think that's probably temporary and then over time we're going to end up with agents that kind of can do anything for you this is kind of what i was saying earlier like there's just like a super assistant you talk to it about anything and then there is like specific UI that you can go look at if you happen to be deep in a specific function.

46:12So in that world, I don't think you want like 12 agents at the company and you have to like go, your employees have to go figure out the right one to talk to because then they won't achieve fluency. And if they don't want to achieve fluency, then they will also won't like pull automation into their roles. But if you have this one thing that you can talk to about anything, right? So your onboarding is just like, go talk to this thing about anything you need, then people will develop muscle memory to go to it. It'll become the center of gravity of work and people will pull in automation. So I think that that future makes much more sense.

46:38And I think like as the people building ChatGPT were like really well set up to deliver that. This is kind of a stretch, but an analogy here is I used to work at Dropbox. And for a while, this is before Slack was big. And for a while we thought, we wondered if people should like go comment on like documents in Dropbox or if they should like go talk about the documents in Slack. And it was like obvious that it was like more optimal for people to like put comments on the right timestamp in the video in Dropbox or like comment on the document in Dropbox, right? So it was more optimal. However, what we saw is that Slack is just such a center of gravity of people just like talking to each other.

47:14Like nobody wants to comment on the document. I just want to Slack you. And so we saw that like there was this really big pull towards things happening in Slack, even if it was less efficient. And I think we're going to see something similar at work where if there is a single agent you can use for nearly anything, there will just be this giant pull and everyone will talk about how they use that one agent for things. Teams will share best practices with each other. There'll be hackathons around how to use that best thing. Yeah. And you'll end up with just a handful of these. You said about kind of agents not really proliferating in terms of usage other than coding.

47:41And actually maybe this being the time and customer support is one of the examples. My question to you is, I'm an investor today. I'm looking for companies which will accrue value over time and provide incredible products to customers. There is a belief that the durability of revenue of large SaaS companies today is zero and that SaaS is dead because the model providers, you, Anthropic, others, are going to come for our lunch, so to speak. What would you advise me? Things are built for humans. Otherwise, what's the point? Even SaaS tools are built for humans. So for me, I think my question is, does this SaaS company own a relationship with a human on the other end of things?

48:23And if it does, then I suspect it's not going away. Or does the SaaS company own some really important system of record? It's probably not going away. Maybe both of those two things, the interaction with the human and the system of record, are more important than ever, actually. On the other hand, is the SaaS company kind of a glue layer, but it doesn't own either of those two things? I'm not the expert here, but I'm more nervous about that kind of company. If we take that stance, Salesforce and ServiceNow, they're down 20%, 30%, 40%. They shouldn't be. I don't think they should be. I don't know.

48:54What do you think? I would love to hear your take on this. I think it's massively exaggerated. I think there are some companies that legitimately should be. Respectfully, I think Dropbox is in a very difficult position. And I think your Monday.com's of the world, though, for the majority of SMBs and consumers who use it, which is the large majority of their market, actually, could they vibe code a to-do list? Yes. Would it be cost efficient to do so? Not really, actually, by the time you customize it and perfect it. And to be honest, a to-do list is generally pretty bland in terms of what you need to do.

49:25Add task, complete task, show historical tasks assigned to new members. It's not very difficult. And so actually, I think you just keep it. And so I think it's massively overblown. And I think that's the classic knee-jerk reaction from markets. I completely agree. I mean, if anything, like now that it's so much easier to build. But I do think, sorry, I do think like I think you're going to come for customer support. And I wouldn't want to be in that category. I think this maybe changes what kind of founder you invest in, right? I think there was this maybe temporary phase that I liked personally as a product builder.

50:01There was this phase where you would invest in the person who can just build good product. And you could kind of ignore if they had a good thesis around a customer or go to market or distribution or anything like that. Because it was so hard to build good product. And I think that was an anomaly. If we look at where we are now, maybe that kind of founder is not the founder you should invest in. Because it's kind of relatively easier to build good product. And you need to go back to like investing in the founder who's like thought through distribution, who has a good domain expertise of what to build for a specific customer, etc.

50:29So, again, if you were on my team as an investor, how would you think about interesting areas for us to invest in, in companies that will accrue value and not be threatened by model providers? Because, again, you're going into health. You go into code. Obviously, Codex is very clear. You go into customer support. Where are you not going? Where is Claude Code not going? I'm tempted to just say, like, I don't know. I think it's a hard time to be an investor. The market is so dynamic, it's hard to say. It's a really tough time to be investing today. My answer is kind of twofold, actually, which is number one, I look for things with physical infrastructure.

51:03I don't think you're going into energy supply. And then two is the fintech and banking integrations, gnarly financial products. I don't think OpenAI is going to go into building 500 relationships with banks in Southeast Asia. I tend to agree. It comes back to, are you going into a gnarly, complicated market where customer relationships and knowledge of the market are everything? That still seems great. How bad is the war for talent? From the UK, we look at SF and I say to companies, it's better to build in Europe because it's impossible to acquire talent and it's impossible to retain it. Am I wrong?

51:38I think that the war for talent is incredibly fierce right now. Obviously at OpenAI, we have an incredibly strong brand and so we're able to attract a lot of talent. But even so, we put a ton of effort into like closing candidates that we're really excited about. Even like even we feel it. It's not like you don't just get whoever you want for free. Can I ask the entry price that you get stock at? Is it still attractive for the best talent? I haven't had anyone tell me anything to the contrary. To what extent do you think about like finding the perfect fit versus finding someone who's good enough?

52:09So, you know, earlier I made my joke about like PMs kind of being optional. Yeah, I think that's not actually true. You still need product people. But I do think that they have to be the perfect fit. And if you have someone who's like not the perfect fit, they might just do more harm than good. It's kind of means that like we're way more selective than I might have been in other roles. I'm a CS student. OK, I'm at Stanford. I'm an Imperial. I'm at Cambridge. I'm wherever, ETH, great institution. What would you advise me, knowing all that you know now, that would help me navigate the next five years of my career?

52:42I want to be valuable to the AI ecosystem environment as an engineer entering the workforce in the next year. Basically, there's actually never been a better time to be an engineer because you have incredible tooling available to you to get an incredible amount done. And your ability to ramp into a complex code base that you might be hired into has never been faster because you can go ask AI a ton of questions about the code base. and you can ask it to plan out changes that would otherwise take you like days to research maybe. I think first off, I would say like, you should be like very optimistic.

53:17But then of course, like about your abilities once you're at the job. Then the other question is how do you get the job? Because it's never been like easier to build things. The thing that becomes scarcer is like agency, taste and like quality. I would urge you to like just build things and demonstrate your agency and your taste around what you build and like build things that are of high quality and then share those things. You know, we get a lot of inbound from folks both applying for jobs through the careers page or also on social. And this is just me. But when someone writes to me with like some interesting thoughts and like a link to an interesting project, that gets my attention much more than like a normal resume does.

53:56Final question, so we do a quick fire. What has Claude Code done well that you sit back and you learn from? Number of things. It's like I was saying, I think way back last year, they made something that was really easy to use and just like work with all your tools with Xero setup by running it locally in your terminal. When we started investing much more in the Codex CLI and shipped great models for it, like GPT-5, our growth exploded. And so I think that idea of just meet people where they're at, give them something easy to use, let them ramp from there and figure out how to use it has been awesome.

54:26So that's probably the biggest learning we've had from them. What mistake do you think they made that you've also learned from, having had the benefit of seeing them make it? They over-indexed on their initial success with their command line interface tool. I think at the end of the day, it's not the friendliest UI. And it makes it hard to extend beyond pure builders. And it makes it difficult to truly delegate to agents because effectively to delegate through that kind of interface, you have to be kind of a power user of your terminal or Tmux or something. And so that's why we built the app. And I think the market reception around the app, to me, it was kind of a risk when we started.

55:00But it makes me really feel good about that decision because the Codex app is a much more intuitive, simple interface to get started with. It's like less scary. But then it naturally leads you to this idea of like, I'm going to take my hands off the keyboard and like delegate to the agent. You mentioned Dropbox earlier. The alumni from Dropbox is incredible and really amazing to see the talent that's come out of Dropbox. What's your single biggest lesson from Dropbox that has shaped some of your thinking now with OpenAI? Oh, I don't need to think about that one. That's kind of the thing I was telling you about earlier, right?

55:32Like when you're building tooling for people, like for end users, you have to think about like that tooling as a system of engagement. If people don't want to use your tool, if it doesn't naturally feel like the easiest way to get something done, then people just won't use it. Again, I learned that from watching how Slack just absolutely took off. And so I think about that a lot now when we're building these agents. I'm like, if we build our agent purely as workflow automation, then it's always going to be like pulling teeth to get that thing started. You're going to need to hire Accenture or someone to come in.

56:02They're going to need to deploy FDEs. It's going to be tough. But if you can build a system that people just love using, even if they only use it for partial tasks, over time, they'll get better and better at using it. And then you'll get connected to the tools you want over time. And then you can start laddering in automation. Obviously, these aren't mutually exclusive. How on earth do you reinvigorate growth at Dropbox today? At least from when I was at Dropbox, the thing we were uniquely good at was desktop software. And desktop software, it's funny, it was never not back. But anyways, it's so back.

56:32basically because if you're solving for productivity and knowledge work, yes, there are systems of record everywhere that you need to connect with, but everything at the end of the day happens on the user's computer, either in their browser or just like locally in apps on their computer. I do think that the fastest way we're going to see productivity gains from agents at work is going to be at first meeting users on their computer, working with the stuff that they have available to them, without having deployed FDEs to set anything up. And then over time, you'll connect in these various systems.

57:00And so if I was Dropbox, I'd be thinking about how do we leverage our unique domain expertise in like building really good like desktop software and the sort of collaborative layer on top of your computer? How do we leverage that to enable productivity agents? It's a bit broad, but I think that's the angle you go. No, I love it. And I really appreciate the response. Final one before we do a quick fire promise. I've been brought up in a world where margin matters. Software margins are wonderful. And it's what makes software a brilliant category to invest in. We're seeing margin profiles that are very different in inference heavy plays in particular.

57:32To what extent should I put that out of mind and appreciate that costs will come down, cost of tokens will come down, and actually it's about usage and customer love, margins will come, or no, margins are actually freaking important. Keep that focus. I think both costs are going to come down significantly. And I also think that if this is the year of agents being deployed broadly at work, then this is also the year where they're going to have to be connected to all these various systems. And I think that's going to be very sticky. And so I view this year as a race. And so I think you want to win that race.

58:04And you should be OK taking some hit to margin in the meantime. Dude, quick fire round. So I say a short statement. You give me your immediate thoughts. Does that sound OK? Yeah. What have you changed your mind on most in the last 12 months? When I joined OpenAI, I thought that this is a little longer than 12 months ago. But when I joined OpenAI, I thought that we would all just be hanging out with our computer screen sharing. within a year from there. You know, we'd have this agent that we're just talking to. That was completely wrong. I think the rate of like progress in like multimodal models was like slower than I expected.

58:34Multimodal means, you know, like models that work with like video and audio. So instead, what happened was that we saw that like agents that work with your computer through code are the way. And so for me, that's been a complete rethink in terms of like how we bring the benefits of AI to like just people generally. It's not through video and audio primarily. Which less unknown capacitor do you respect most and why? The first one that came to mind was AMP. I think they're building, yeah, AMP. It's out of the folks at Sourcegraph. Their product has a great reputation of just being like, you know, punching way above its weight.

59:06But I think the other thing that I really respect is that they helped initiate this whole like standardization around like agents.md and like.agents slash skills, which are what I was saying earlier about like making it so it's easier for users to manage all these different agents that they're trying. We obviously put out agents.md, but they put out agent.md. And basically, Quinn started this all by putting out a tweet that said, hey, do you guys buy the domain agents.md? We'll standardize to your spelling. And as small as that was, that initiated this whole standardization that I think has been awesome in the community.

59:36Do you think the response to Anthropics ads was the right response? I mean, there were so many different responses. The one that I heard, obviously, I think was right. The one that I heard was, well, one company is being pretty negative about the future. And the other company, us, OpenAI, is being really positive and just telling people they can build things into dream. I thought that response was brilliant. I mean, Sam wrote an essay. Do you think it was a good response? I think so. I mean, I think as one of the cool things that I love about OpenAI is like people are like very unapologetically and authentically themselves.

1:00:09And so for me, that was just like a very authentic response. And I like that we do that. What's the hardest product decision you've had to make since being at Codex? Well, I can tell you the most painful product decision we had to make. For a while, Codex Cloud was effectively unlimited. Not free, like you needed to pay for ChatGPT, but then you had unlimited usage. Every day that we left it that way, we knew that it would be harder to wind back at being unlimited. But we were just so focused on competing on our other things that had more PMF that we punted that decision out. When we wound back that unlimited use to some more reasonable limit, there was a lot of blowback from users.

1:00:43And it was a very small minority of users who thought everything should be pseudo-free forever. but that blowback affected us everywhere because like the social chatter doesn't really distinguish between these things. I think the lesson I learned the hard way there is like you can't make things unlimited for too long. Dude, it's like pricing, grandfathering pricing is just, it's such a hard thing. What do we do today in engineering or product that in five years time you'll look back on and go, oh my God, can you believe that we did that? Well, one is just editing code by hand. I think probably another one, this is maybe spicier, but another one might even be like actually managing the deployment and monitoring of systems by hand.

1:01:23Like I basically think that probably big companies will take a long time to like deploy this. But many startups might actually kind of start building on a completely new stack that's like fully AI managed. To be clear, the stack doesn't exist yet, but a fully managed AI stack where basically it's been built to give you really strong deterministic guardrails over what the agent can do and control over to whirl back deploys and everything like that. And so we'll get to a world where the way you start a company is you start by getting an agent and just asking it to build things. And then you get more agents in that.

1:01:53And then maybe eventually you add your co-founders to this service that you use to work with agents. And so you end up like maybe your main communication tool is actually your agent communication tool. And then maybe you're not actually handholding this very painful CI and deploy process, but you're just having agents do things. Weird question, but I'm intrigued. Are you the one providing agent guardrails? And what I mean by that is agents can go anywhere within an enterprise. Are you responsible providing those guardrails? Or is there a third-party matter provider who is saying, hey, Alex, you can't go into that.

1:02:26That's human resources. Or you can't go into that. That's marketing. How do you think about guardrail provisioning? And is that the role of the agent provider or a third-party provider? I think we'll probably see both. We are putting a lot of effort into agent guardrails. Like I said, we're basically the only company that cares about OS-level sandboxing for coding agents. For instance, there's none that exists on Windows. We're the ones building that. And we're doing it in open source, so hopefully other people can use it. We think about that a lot. Chachptee supports connectors. So you can talk to your Google Docs or something.

1:02:55And we put a lot of effort into guardrails around what the agent can do with your Google Docs. Those are just two examples, but we think a lot about this. And I think probably, though, the way that we'll do it will not be sufficient. Like there'll be third parties who provide like very bespoke things for very bespoke, you know, company needs. And there'll probably be a mix of both. Final one for you, my friend. What are you most excited about when you look forward 10 years? This is probably going to happen in much less than 10 years. But my mission sort of personally, when I joined the company, was I just felt like even with the models we had a year and a half ago, there was so much just capability overhang or just ability for these things to be useful, but we hadn't built the right products around that.

1:03:33And so people like me were getting more benefit than people like my grandma. What I'm most excited for is to get to a form factor for AI that means that they're just helping everyone regardless of whether they're in tech and especially if they're not in tech or especially if they're older. And so the concrete vision I have is at some point, we'll add an agent to our family WhatsApp or something and it'll just start being useful to the family without anyone having to think harder about it than that. There are many other ways that that could happen, but I think concretely, that's the most obvious thing we can do with like my grandma.

1:04:06Dude, I so appreciate you. I so appreciate you putting up with my wandering questions and my very episodic mind. You've been fantastic, man. Thanks so much. I mean, I appreciate you putting up with my wandering answers. So all good. We're two here. But before we leave you today, the early story of Atlassian is probably very similar to your own. Atlassian knows firsthand the challenges that startups face every day and that the right tools are essential to go from MVP to IPO That's why Atlassian for startups gives eligible companies up to 50 seats free on the premium edition For products like Jira, Confluence, Loom, Jira Product Discovery, Compass, and Bitbucket So your team can use the best-in-class tools to plan, track, and collaborate on work Whatever that work may be, many of today's most successful startups like Cloudflare, Canva, and Rivian relied on Atlassian for their growth trajectory.

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