Alistair Pullen
Co-founder & CEO, Cosine. On 1 show, 2 appearances. The Shows tab opens the full record on each.
founderexecutiveengineer@AlistairPullen ↗LinkedIn ↗cosine.sh ↗
Alistair Pullen co-founded Cosine, an AI lab known for building the autonomous software engineering agent Genie. Prior to Cosine, he was an early engineer and the first technical hire at Fancy, which was acquired by Gopuff.
1shows
2appearances
34statements
6resolved
5supported
1contradicted
83%fully supported
Everything Alistair Pullen said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Pullen: CoScene's Genie outperforms OpenAI o1 out of the box on SWE-bench
“So it was obviously great to see, like, we still are better than O-one out of the box. You know, even with an older model, and I'm sure that that, that Delta will continue to grow once we're able to train O-one and once we've done more work on our dataset usin…”
Pullen: SWE-bench is a poor proxy for real-world AI coding competence
“I know Sweebench is, like, the most commonly talked about thing, and honestly, it's a very, it's an amazing project, but one of the things we've learned the most from actually shipping this product to users is, it's a pretty bad proxy at telling us how compete…”
Extracting problem-solving history most determines Cosine Genie's SWE-bench performance
“The way that we Decided we want to try to extract what happened in the past, like as forensically as possible, has been and is currently like one of the main things that we focus all our time on. Because doing that as we're getting as much signal out as possib…”
Cosine refuses to publish SWE-bench trajectories to prevent competitor model distillation
“For the moment, as a closed source company, like fighting for an edge, we've decided not to publish that information for that exact reason. I don't want someone basically taking my tragedies and then taking a model that's suing them in GA and just distilling i…”
Pullen: You cannot build a successful startup solely on the YC advantage
“You can't build a startup on the YC advantage. It's obviously nice and it makes you feel warm and fuzzy inside, but like at the end of the day, it's not that that's going to make you win.”
Pullen: SWE-bench is currently the best metric for software engineering agents
“It was actually a very useful tool in building Genie because beforehand it was like, yes, vibe check this thing and see if it's useful. And then all of a sudden you have an actual measure to see like, couldn't it do software engineering? Not the best measure, …”
Training on pull request diffs yields code generators, not software engineers
“What the, very crudely, what the pre-trained models are reading is they're reading those final diffs and they're Emulating that and then being able to output it. Right. But of course it's a super lossy thing, a PR. You have no idea why or how, for the most par…”
File modification is more fundamental for coding agents than browser access
“At least with what we've seen, the browser is helpful, but it's not as helpful as like writing the correct files. If that makes sense. Like, it is still helpful, but obviously there are more fundamental things you have to get right before you get to like, oh y…”
Step-by-step prompting on foundational models cannot achieve SOTA SWE-bench performance
“I think it's fairly obvious that with the foundational models, like you can ask them to think by step by step and ask them to plan and stuff, but that isn't enough because if you look at how those models score on these benchmarks and then they're not They're n…”
Genie's SWE-bench success rate drops to roughly 50% past 60k tokens
“Performance of Jeannie over the length of the context window degrades fairly linearly. So actually, I actually broke it down by probability of solving a SWE bench issue. Given the number of tokens of the context window at 60 K, it's basically .5. So if you go …”
Cosine's Genie achieved a state-of-the-art 43.8% on SWE-bench Verified
“We got 219 out of 500, which is 43.8%, which is To my knowledge, at least right now, state of the art also”
Pullen: Replacing Genie's reasoning traces with o1 traces improves performance
“Even now we've started Replacing some of the reasoning traces in our Genie model with reasoning traces generated by O-one, or at least in tandem with O-one, and we've already started seeing improvements in performance from that point.”
Autonomous coding agents require grounding all generated code in context windows
“Fundamentally to build a product like this, you need to get as much information in front of the model as possible and make sure that everything ever writes in output can be
Traced back to something in the context window, so it's not hallucinating it.”
Access to GPT-4 Turbo experimental fine-tuning enabled Cosine Genie's creation
“Eventually we were able to get on the experimental access program and we got access to four turbo fine tuning. As soon as we did that, because in the entire run up to that, we'd built the data pipeline. We already had all that set up. So we're like, right, we …”
Pullen: Most scraped open-source data consists of README and documentation updates
“When you scrape enough of it, most of open source is updating readmes and docs.”
Pullen: Enterprise customers are growing more willing to share proprietary codebases
“Mostly we've actually seen, I'd say people becoming more amenable to the idea over time, actually rather than more skeptical, because I think they can see the upside.”
Standard semantic embedding similarity fails on codebase retrieval tasks
“And once you've done that, I will write a query saying like, find me some authentication code or something, embed it, and then do the cosine similarity and get the top of K right. That doesn't work. And I wish it did work. Don't get me wrong. It doesn't work w…”
Generating hypothetical code from queries significantly improves codebase retrieval accuracy
“So what we ended up, the first approach we took and that kind of did well enough for a long time was, okay, let's train a model to be able to take in English code queries and then produce a hypothetical Code snippet that might look like the answer, embed that,…”
Cosine's Genie achieved roughly 66% codebase retrieval accuracy across benchmark tasks
“And I think in our technical report, I can't remember the exact number, but I think it was around 65 or 66% retrieval accuracy overall measured on. We know what lines we need for these tasks to find for the task to actually be able to be completed. And we foun…”
Anthropic model fine-tuning will be offered through AWS Bedrock
“They are partnered with AWS, and it's going to be in bedrock. As far as I know, I think that's true.”
Upgraded frontier models will automatically improve Cosine's synthetic data flywheel
“When models like that come out, obviously the signal in my data, when I regenerate it goes up. And then I can then train that model that's already better at reasoning with improved reasoning data. And just like, I can keep bootstrapping and keep leapfrogging e…”
Token log probabilities show models are most certain when writing code
“The certainty of code writing is so much more certain than every other aspect of Genie's loop. So whatever's going on under the hood, the model is really comfortable with writing code. There is no doubt, and it's like in, in the token probabilities.”
Cosine's Genie hooks into existing GitHub CI rather than building environments
“The model itself is not in charge of like setting up the code base and running it. So genie sits on top of GitHub. And if you have CI running GitHub, you have GitHub Actions and stuff like that, then Genie essentially makes a call out to that, runs your CI, se…”
Cosine injects synthetic AST errors into training data to teach error recovery
“And that was in sort of two parts. We synthetically generated runtime errors where we would Intentionally mess with the AST to make stuff not work or index out of bounds or refer to a variable that doesn't exist or errors that the foundational models just make…”
One line per show, most statements first. The link opens Alistair's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 LATENT SPACELEDGER | Co-founder & CEO, Cosine | 2 | 34 | 83% 5/6 | full record on Latent Space → |