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“Cursor has, like, great analytics. Right? And so you go to the admin panel, you look at the analytics, and, you know, awesomely, they let you download into CSV. I was like, what if I just use cursor to figure out what my team is doing in terms of using cursor, but not in just, like, from a vanity metric point of view of, like, lines of code committed by AI. I think that's, like, kind of misleading, actually digging more into, how they're using Cursor and how do we sort of, like, replicate power users.”

“I'm coming here as we just shipped Gemma four. And, it's a really good open source model. The frontier to Gemma four is both huge and not so huge in terms of time. Like, of, Gemma four is based on Gemini three architecture. You know, it's a very weird thing. Right? You're talking about a set of ways which can fit on a USB stick.”

“But now it is really acutely constrained. Right? So you spend a lot more time. I at least spend a dedicated hour a week thinking about that question at a pretty granular level. So I will know by projects and by teams the compute units they are using. Right? And, you know, or or at least I have that information, and I'm looking at it and assessing it.”

“For Cloud Code, what we do is we actually ship almost all of our features in Research Preview. We clearly brand this when we ship something so that users know that this is an early product. This is just an idea. This is just something that we're trying to get feedback on and iterating on, and that this might not be supported forever. And what this does is it reduces our commitment for shipping something. We can just get something out in a week or two.”

“Just do things. I think there's a lot of value in, like, first principles thinking. And if if you, like, if you know what you're optimizing for and you have, like, strong first principles, then you can normally deduce what the right, like, course of action is and be able to clearly articulate that to all the stakeholders. And then you should just, like, do it. Like, I think jobs are fake. If you understand the constraints, you can figure out what you can do and then just, like, try to do it quickly, learn from the mistakes, and apologize or fix them if you did something wrong.”

“We are constantly trying to take these long term projects, which when you first announce them, slightly marginally looks ridiculous. Okay. You know, like, we're in the earliest stages of thinking about data centers in space. But to your earlier discussion around constraint inspires creativity. But if you take a twenty year outlook, right, where are you going to put most of these data centers? Really hard problems to solve.”

“But to give an example, like, search, you know, I was speaking with the teams. Right? Like, they now have for sub teams, like, latency budgets, like, in the milliseconds. You'll get 50% credit if so if you ship something which, you know, shaves off three milliseconds, you earn one point five milliseconds for your latency budget, and one point five milliseconds gets passed on to the user.”

“Transformers was done in the context of a lot of, like, like, TPUs, transformers were all done to solve a specific product need to some extent. Right? Like, the team's thinking about how to make translation better. In the case of TPUs, how do you, pay speech rec works? We suddenly have to serve it to 2,000,000,000 people. We don't have enough chips for it.”

“Then the review time, like, all my devs complain. Review times take too long. We found some solutions, actually. I think we were doing average of, like, a hundred and fifty hours, like, was the cycle time for a PR review because there was so much. We reduced it by 10 x down to, like, fifteen hours or so, roughly.”

“Memory is definitely one of the most critical components now. There is no way that the leading memory companies are going to dramatically improve their capacity. So you have those constraints in the short term, but they they get more relaxed as you go out. By the way, I think it'll push a lot of innovations on. We will make these things 30 x more efficient.”

“I love food and wine. I really do. And, like, I've done, like, sommelier training, etcetera, etcetera. With my friend in New York, we went to some, like, champagne tasting. And so, like, I just took notes. There's, like, this whole notebook. Effectively, then I just, like, popped this right in. And I said, here are a bunch of champagnes that I tasted. Figure out from my notes, like, what are my taste preferences?”

“Show the engineers, not just tell. And the worst thing any engine leader could do is just be like, I decree you must use AI. Come on. No one's gonna listen to you.”

“The nuclear option is I threaten it, and I say, Claude, if I'm using, like, Claude Opus for 4.5 high, like, okay. I'm gonna stop using you, Claude. I'm gonna switch to Gemini, and then it gets its shit together.”

“It's pretty important to build products that don't necessarily work yet so that you know, okay, what is missing, for this product to work? And then with the newest model, you can just swap it into the prototype you've already made and see, okay, does this new model close that gap?”

“The trick here, why Slack, is because Slack is how things go viral within your company. If you have pulled out the magic into some separate tool that others can't see, it doesn't happen. And so by getting things into Slack, people just like, holy shit. This is possible. Let's go.”

“Waymo was a great example where I think we increased our investment two to three years ago when the rest of the world got pessimistic on it. When others, some of the people are backing off. For example, if Waymo had reached this point earlier, I think I would have invested the capital earlier. But I would have been glad to invest more capital in Waymo earlier, but we weren't at the level of maturity needed to do that.”

“Mission means that teams are willing to make sacrifices that hurt their own goals and their own KRs in service of Anthropic's goals and Anthropic's KRs. And people are very happy to make those trade offs. So, like, an extreme example is if Cloud Code failed, but Anthropic succeeded, I would be extremely happy. And, like, we're like, the whole team is very willing to make decisions that follow that chain of thought.”

“One of the things I really like to do is to ask the model to introspect on its own behaviors. So sometimes when I notice that the model does something unexpected, like, for example, there's, like, situations where the model will make a front end change and run tests, but not actually use the UI. It's actually pretty useful to ask the model to reflect on why I did this. And sometimes they'll say that, hey. There was, like, something confusing in the system prompt, or I didn't realize that, the front end verification was, like, part of this task.”

“When people think about quad and quad code, this is one of the things that people bring up the most where they just really love that quad is like it's it's like lighthearted and fun, but it also is extremely competent at your task. People really like, like, Claude's low ego. And so if you tell it, hey. You did this thing wrong. It's, like, truly sorry. It's like, oh, shoot. Like, thanks for telling me. Like, let me fix it. Let's work together.”

“I would also push listeners towards focusing on bringing your automations from, okay, this is a cool concept to, like, hey, this actually works a 100% of the time. Like, sometimes I see users trying to automate something, getting it to, like, 95% accuracy, and then giving up on it. And this if an automation doesn't work a 100% of the time, it's not really an automation. And that last five to 10% does take more time.”

“I think now with AI and with how much that has accelerated engineering and with how quickly the model capabilities are improving, the timelines for a lot of our product features have gone down from six months to one month and sometimes to one week or even one day. And with that, we actually need to make sure that products ship quite quickly. And what that means is as a PM, there should be less emphasis on making sure that you're aligning your, like, multi quarter roadmaps with your partner teams and more emphasis on, okay, how can we figure out the fastest way to get something out the door?”

“Last night, I was work where we have this code with cloud conference coming up, and there's a few talks that I'm giving there. I have my Google Drive connected. I have Slack connected. Alex, who's our product marketer, put together a draft of what the points that we that he thinks we should cover are. And so I just, like, fed this all into Cowork. I told Cowork the narrative that I want to tell, and it actually just worked for an hour. It it walked through Twitter to see what we launched. It looked through our evergreen launch room. And it synthesized all this together to this 20 page deck that I woke up to this morning.”

“On our team, we're pretty focused on hiring engineers with great product taste. This this way, we can reduce the amount of overhead for shipping any product. Like, there are many engineers on our team who are fully able to end to end go from see user feedback on Twitter through to, like, ship a product at the end of the week with almost no product involvement. And this, I think, is actually, like, the most efficient way to ship something.”

“I had landed I was going to the East Coast. I landed, for my flight, got into an Uber, hopped on, like, an entire team, all hands, like, speed run. We call it it was, like, basically, cursor speed run. And I was in the Uber using cursor, putting up the PR. And the goal of the speed run was every single person would just pick up the most trivial thing. It could be like copy change, a bug, whatever, and just put up the PR. And we ended up, I think, in fifteen minutes I think a 100 people had joined. In fifteen minutes, we ended up putting up, like, 70 PRs. And we broke GitHub too, which was cool because we learned, like, our infrastructure needed improvement.”

“I invented this role called super builder. And the single job single most important job of a Super Builder is to create more Super Builders. So we we hired our first Super Builder and they, we we talked about some ideas and one of the biggest things because most of our company uses Slack. We're all in Slack. And Slack, you know, I'm strong it's like strong believer is just a bunch of humans pretending to be systems. Right? And the cost of writing something in Slack is zero, but the cost of answering something in Slack is enormous, and most of it is noise.”

“So we immediately looked into this when we saw it. We realized that this was the result of human error. There is, a human working with Cloud to write a PR. This was just an update to how we release our packages. And it actually went through two layers of human review. And so the this was a result of human error, and we've hardened our processes to make sure that it doesn't happen in the future.”

“Hey. The overton window shifted. We have like, I felt like the company was built for that moment. The vertical thing, it's it's it's not an accident or something. It was a very intentful we were on the seventh version of TPUs. So to me, we were behind in terms of frontier LLM models, but we had all the capabilities internally, and we had to execute to meet the moment.”

“I think your question earlier on, like, you know, I think you were asking in the context of way more robotics, like, companies. I do think companies which are that's one advantage startups are gonna have. More AI native teams. And and, you know, you can probably get at it through your interview processes, etcetera. Whereas for us, we would have, like, retraining, transformation etcetera. And I think that that's maybe an advantage, like, the younger companies are gonna have.”

“I was on a call with with, like, a a user of our product. Right? And they're like, hey. It'd be cool if you, like, changed x, y, and z. And what literally, while I was on the call, I just put up a PR and pushed it. And they're like, before the call ended, it was thirty minutes. I was like, just, you know, reload the app. It's fixed.”