Speakers in the public record
Claim mix
evaluation 6belief 5preference 3commitment 2prediction 2recommendation 1
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
The useful parts, with receipts.
19 published records
“So we could see if we were, you know, actually helping ourselves or not. And initially, one of the biggest performance gains that we saw when we were work, when we did work on the RAG a bit was giving it the ability to use the LSP to like go to definition and really try to get it to emulate how we do that, because I'm sure when you go into an editor with that, where like the LSP is not working or whatever, you suddenly feel really like disarmed and naked.”
- Publisher
- Latent Space
“recommend it. Don't fly from London to San Francisco for two days.”
- Publisher
- Latent Space
“It's hilarious, like we had to filter out so much of that stuff because when we first did the 16k model, like the amount of readme updating that went in, we did like no data cleaning, no real, like, we just sort of threw it in and saw what happened. And it was just like, It was really good at updating readme, it was really good at writing some comments, really good at, um, complaining in Git reviews, in PR reviews, rather, and it would, again, like, we didn't clean the data, so you'd, like, give it some feedback, and it would just, like, reply, and, like, it would just be quite insubordinate when it was getting back to you, like, no, I don't think you're right, and it would just sort of argue with you, so The process of doing all that was super interesting because we realized from the beginning, okay, there's a huge amount of work that needs to go into like cleaning this, getting it aligned with what we want the model to do to be able to get the model to be useful in some way.”
- Publisher
- Latent Space
“I think one of the decisions before you as a CEO is how much you have like the house model be like the one true thing, and then how much you spend time working on customer models.”
- Publisher
- Latent Space
“The decision to fork VS Code, I think, was controversial. You guys started as a VS Code extension.”
- Publisher
- Latent Space
“When we have more resource as a company, and, More time and, you know, once all the craziness that has just happened sort of dies down a bit, we are going to, you know, work on that mix.”
- Publisher
- Latent Space
“I'll briefly comment here. So this is the standard approach I would say most, uh, code tooling startups are pursuing.”
- Publisher
- Latent Space
“We believe that if you want a model to behave like a software engineer, it has to be shown how a human software engineer works.”
- Publisher
- Latent Space
“Honestly, people who are just willing to try something new, like the Genie UX is, is different to a conventional IDE, give it a chance, like that what we really do believe in this whole idea of like developers work is going to be abstracted, you know, levels higher than just the code, we still let you touch the code, we still want you to dive into the code if you need to, but Fundamentally, we think that if you're trying to offload the coding to a model, the model should do the coding and you should be in charge of guiding the model.”
- Publisher
- Latent Space
“improved reasoning data and just like I can keep bootstrapping and keep leapfrogging every single time. And that is like super exciting to me because I don't, I welcome like new models so much because immediately it just floats me up without having to do much work, which is always nice.”
- Publisher
- Latent Space
“I think obviously the most important tools to these agents are like being able to retrieve code from a code base, being able to read Stack Overflow articles and what have you and just be able to essentially be able to Google like we do is definitely super useful.”
- Publisher
- Latent Space
“Expensive, slow, really like crap for iteration, because like, you know, you make a change to your model, how does it do on SweetBench?”
- Publisher
- Latent Space
“Um, and of course, like, companies building in this space, we're all going to end up, you know, complying with the same rules, and there are going to be new rules that come out to make sure that we're looking at your code, that everything is safe, and so on. So from what we've seen so far, we've spoken to some very large companies that you've definitely heard of and all of them obviously have stipulations and many of them want it to be sandbox to start with and all the like very obvious things that I, you know, I would say as well, but they're all super keen to have a go and see because like, despite all those things, if we can genuinely Make them go faster, allow them to build more in a given time period and stuff.”
- Publisher
- Latent Space
“Like, we are right on the edge, and like, we are working, genuinely working with them in figuring out how stuff works, what works, what doesn't work, because no one's doing No one else is doing what we're doing.”
- Publisher
- Latent Space
“I like our approach because we can be super agile and be like, Oh, well, Anthropic have just released whatever, uh, you know, and it might have half a million tokens and it might be really smart.”
- Publisher
- Latent Space
“As soon as we did that, because in the entire run up to that we built the data pipeline, we already had all that set up, so we were like, right, we have the data, now we have the model, let's put it through and iterate, essentially, and that's, that's where, like, Genie as we know it today, really was born.”
- Publisher
- Latent Space
“I think that translation between natural language, English versus code, and back and forth, I think is actually a really ripe source of synthetic data.”
- Publisher
- Latent Space
“You have no idea why or how, for the most part, unless there are some comments, which, you know, anyone who's worked in a company realizes PR reviews can be a bit dodgy at times, but you see that you lose so much information at the end, and that's perfectly fine, because PRs aren't designed to be something that perfectly preserves everything that happened, but What we realized was if you want something that's a software engineer, and very crudely, we started with like something that can do PRs for you, essentially, you need to be able to figure out why those things happened.”
- Publisher
- Latent Space
“Because, 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 it ever writes in output can be read.”
- Publisher
- Latent Space