**Lenny Rachitsky** (0:00)
Do you lead work on Codex?
**Alexander Embiricos** (0:01)
Codex is OpenAI's coding agent. We think of Codex as just the beginning of a software engineering teammate. It's a bit like this really smart intern that refuses to read Slack, doesn't check data, dog, unless you ask it to.
**Lenny Rachitsky** (0:12)
I remember Karpathy tweeted the gnarliest bugs that he runs into, that he just spends hours trying to figure out nothing else to solve. He gives it to Codex, lets it run for an hour, and it solves it.
**Alexander Embiricos** (0:21)
Starting to see glimpses of the future where we're actually starting to have Codex be on call for its own training. Codex writes a lot of the code that helps manage its training run, the key infrastructure, and so we have a Codex code review is catching a lot of mistakes. It's actually caught some pretty interesting configuration mistakes. One of the most mind-blowing examples of acceleration, the Sora Android app, like a fully new app. We built it in 18 days, and then 10 days later, so 28 days total, we went to the public.
**Lenny Rachitsky** (0:45)
How do you think you win in this space?
**Alexander Embiricos** (0:47)
One of our major goals with Codex is to get to productivity. If we're going to build a super system, it has to be able to do things. One of the learnings over the past year is that for models to do stuff, they are much more effective when they can use a computer. It turns out the best way for models to use computers is simply to write code. We're getting to this idea where if you want to build any agent, maybe you should be building a coding agent.
**Lenny Rachitsky** (1:04)
When you think about progress on Codex, I imagine you have a bunch of evals and there's all these public benchmarks.
**Alexander Embiricos** (1:10)
A few of us are constantly on Reddit. There's praise up there and there's a lot of complaints. What we can do as a product team is just try to always think about, how are we building a tool so that it feels like we're maximally accelerating people rather than building a tool that makes it more unclear what you should do as the human.
**Lenny Rachitsky** (1:24)
Being at OpenAI, I can't not ask about how far you think we are from AGI.
**Alexander Embiricos** (1:28)
The current underappreciated limiting factor is literally human typing speed or human multitasking speed.
**Lenny Rachitsky** (1:35)
Today, my guest is Alexander Embiricos, product lead for Codex, OpenAI's incredibly popular and powerful coding agent. In the words of Nick Turley, head of ChatGBT and former podcast guest, Alex is one of my all-time favorite humans I've ever worked with, and bringing him and his company into OpenAI ended up being one of the best decisions we've ever made. Similarly, Kevin Weill, OpenAI's CPO, said, Alex is simply the best. In our conversation, we chat about what it's truly like to build product at OpenAI, how Codex allowed the Sora team to ship the Sora app, which became the number one app in the App Store in under one month. Also, the 20x growth Codex is seeing right now and what they did to make it so good at coding, why his team is now focused on making it easier to review code, not just write code, his AGI timelines, his thoughts on when AI agents will actually be really useful, and so much more, a huge thank you to Ed Baiz, Nick Turley, and Dennis Yang for suggesting topics for this conversation. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. And if you become an annual subscriber of my newsletter, you get a year free of 19 incredible products, including a year free of Devon, Lovable, Replit, Bolt, N8N, Linear, Superhuman, Dscript, Busperflow, Gamma, Perplexity, Warp, Granola, Magic Patterns, Raycast, Charperd, Mobbin, PostHog and Stripe Atlas. Head on over to lennysnewsletter.com and click Product Pass. With that, I bring you Alexander Embiricos, after a short word from our sponsors. Here's a puzzle for you. What do OpenAI, Cursor, Perplexity, Vercell, Platte and hundreds of other winning companies have in common? The answer is they're all powered by today's sponsor, WorkOS. If you're building software for enterprises, you've probably felt the pain of integrating single sign-on, skim, RBAC, audited logs and other features required by big customers. WorkOS turns those deal blockers into drop-in APIs with a modern developer platform built specifically for B2B SaaS. Whether you're a seed-stage startup trying to land your first enterprise customer or a unicorn expanding globally, WorkOS is the fastest path to becoming enterprise-ready and unlocking growth. They're essentially Stripe for enterprise features. Visit workos.com to get started or just hit up their Slack support where they have real engineers in there who answer your questions super fast. WorkOS allows you to build like the best with delightful APIs, comprehensive docs, and a smooth developer experience. Go to workos.com to make your app enterprise-ready today. This episode is brought to you by Fin, the number one AI agent for customer service. If your customer support tickets are piling up, then you need Fin. Fin is the highest-performing AI agent on the market, with a 65% average resolution rate. Fin resolves even the most complex customer queries. No other AI agent performs better. In head-to-head bake-offs with competitors, Fin wins every time. Yes, switching to a new tool can be scary, but Fin works on any help desk with no migration needed, which means you don't have to overhaul your current system or deal with delays in service for your customers. And Fin is trusted by over 6,000 customer service leaders and top companies like Anthropic, Shutterstock, Synthesia, Clay, Vanta, Lovable, monday.com, and more. And because Fin is powered by the Fin AI Engine, which is a continuously improving system that allows you to analyze, train, test, and deploy with ease, Fin can continuously improve your results, too. So if you're ready to transform your customer service and scale your support, give Fin a try for only 99 cents per resolution. Plus Fin comes with a 90-day money-back guarantee. Find out how Fin can work for your team at fin.ai.lennys. That's fin.ai.lennys.
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