Sherwin Wu
Head of Engineering, OpenAI Platform. On 4 shows, 3 appearances. The Shows tab opens the full record on each.
engineeroperatorexecutive@sherwinwu ↗LinkedIn ↗
Sherwin Wu is the Head of Engineering for OpenAI's developer platform and API products. He previously worked as a software engineer at Quora, Opendoor, and Palantir.
4shows
3appearances
55statements
16resolved
14supported
0contradicted
88%fully supported
Everything Sherwin Wu said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Wu: Blindly following customer requests leads to AI product local maxima
“Because the field is changing so much at any point in time, you know, a lot of people are kind of in this local, local maximum. And if you just blindly listen to your customers, they'll, they'll be like, yeah, I want a better vector store. Like I want a better…”
Wu: OpenAI engineers using Codex open 70% more PRs
“So they're actually opening 70% more PRs and than the engineers who aren't using Codex as much and the gap is widening.”
Wu: AI tools widen the productivity spread across engineering teams
“Codex really empowers, like, top performers to get a lot, like, to be a lot more productive, and so it really, like, and I think this may be true for AI more broadly, like, across society, which is, like, the people who really lean in, or, like, the people who…”
Wu: AI will enable engineering managers to manage far more than 6-8 engineers
“My sense is I think managers will be able to manage much larger teams in this world. Kind of like how, you know, like software engineers are managing 20 to 30 codexes. My sense of these tools will allow managers, people manage to be higher leverage and will al…”
Wu: A one-person billion-dollar startup will likely exist eventually
“It's like, yeah, if, you know, if people are so high leverage, at some point there will likely be a one person billion dollar startup.”
Wu: Rise of AI micro-companies could shrink venture-scale return opportunities
“You know, it might, we might end up in in a world where there's just, like, a handful of big players that are offering platforms and supporting all of these startups, but, you know, the types of venture-scale return startups that can really hundred or thousand…”
Wu: AI startups should build for capabilities that are 80% viable
“My general advice, and I've been giving this to people for a while, and I think it's still true today, is make sure you're building for where the models are going and not where they are today. You know, the, it's clearly a moving target, and I think a lot of t…”
Wu: OpenAI deployed o3 on an air-gapped Los Alamos supercomputer
“We actually did a custom on-prem deployment with them onto one of their supercomputers called Venado. And so this actually involves a bunch of, you know very bespoke work with some FDs also with a lot of our developer team. To actually bring one of our reasoni…”
Wu: GPT-5 hallucinations dropped to near zero on certain benchmark evaluations
“I think there was an eval that showed that hallucinations basically went to zero for a lot of this.”
Wu: Short on the entire AI tooling startup category
“I'm short on the entire category of like tooling
around AI AI products.”
Wu: Short on reinforcement learning environment startups
“RL environments I think are really big right now as well.
Unfortunately, I'm very short on those.
not really I don't really see a lot of potential there.
See a lot of potential and reinforcement learning and applying it, but I think the startup space around R…”
Wu: 95% of OpenAI engineers use Codex and 100% of PRs are AI-reviewed
“So, 95% of engineers use Codex.
100% of our PRs are reviewed by Codex daily as well, so basically any code that goes into production that's merged in, Codex kind of has its eyes on and suggests improvements, suggests changes in the PRs.”
Wu: OpenAI engineers juggle up to 20 parallel Codex threads simultaneously
“I know many of the engineers on my team basically have like, 10 to 20 threads kind of being pulled on at the same time. Obviously not active running codex jobs. But just a lot of parallel threads. They're checking in on what they're doing. They're steering the…”
Wu: OpenAI team is maintaining a 100% Codex-written codebase without manual coding
“So there's a team that that's actually doing an experiment right now with an open AI where they are basically maintaining a 100% code expert and code base. So, you know, like, you know some, you know, you'll have the AI write code, but you'll obviously end up …”
Wu: Codex cuts OpenAI code review times from 15 to 3 minutes
“And it makes, you know, code reviews go from a, you know, I don't know, 10:15 minute task to sometimes even just like a two to three minute task, because you have a bunch of suggestions already, already baked in.”
Wu: The vast majority of code at OpenAI is authored by AI
“Almost every engineer heavily uses Codex in all of their tasks at this point, and so I, you know, if I were to guesstimate, like, the vast majority of code at this point is, It was probably authored by AI.”
Wu: OpenAI managers use internal ChatGPT for employee performance reviews
“We're doing performance reviews right now, and it's actually really easy to use ChatGPT with internal knowledge, hooked up to GitHub and like our Notion docs and Google docs. To give a, get a really good sense of what this person has done over the last 12, 12 …”
Wu: Organizational barriers are the main bottleneck to AI-assisted shipping
“If people are just like cranking PR after PR, the main thing bottlenecking progress and, you know, shipping something tends to be organizational or like process oriented.”
Wu: AI models could execute multi-hour to day-long tasks in 12-18 months
“If you follow this trend, like, I think, like, in the next 12 to 18 months, we could see models that could do multi-hour long tasks very, very coherently. At some point, it might reach, like, you know, six hours a day long task.”
Wu: Native speech-to-speech multimodal models will improve dramatically in 6-12 months
“I think they're gonna get a lot better at audio over the next six to 12 months, especially the likes, you know, the native multimodal models, the speech-to-speech ones.”
Wu: AI startups fail from lack of customer resonance, not OpenAI competition
“Every startup that I've seen that is kind of fizzled out is not because open AI or, you know, big lab or Google or something has come to squash them. It's because they built something and it like really didn't resonate with the customers.”
Wu: Every model released in OpenAI products is released in the API
“Every single model we've released in one of our products gets released in the API.”
Wu: Los Alamos OpenAI supercomputer deployment is shared with Lawrence Livermore and Sandia
“The other cool thing is it's actually being shared between Los Alamos and some of the other labs Lawrence Livermore Sandia as well because it, it's the supercomputer setup where they can all kind of connect with it remotely.”
Wu: Failed Enterprise AI Deployments Usually Lack Data Scaffolding
“My hunch is some of the enterprise deployments that don't actually work out likely don't have the scaffolding or infrastructure for these agents to interact with as well. A lot of the, like, really successful deployments that we've made, a lot of what our FDs …”
One line per show, most statements first. The link opens Sherwin's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 a16zLEDGER | Head of Engineering, OpenAI Platform | 0 | 0 | 50% 2/4 | full record on the a16z Podcast → |
 LENNY'S PODCASTLEDGER | Head of Engineering, OpenAI Platform | 1 | 24 | 100% 1/1 | full record on Lenny's Podcast → |
 BG2LEDGER | Head of Engineering, OpenAI Platform | 1 | 19 | 100% 6/6 | full record on BG2 Pod → |
 LATENT SPACELEDGER | Head of Engineering, OpenAI Platform | 1 | 12 | 100% 5/5 | full record on Latent Space → |