Cat Wu

“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?”

“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.”

“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.”

“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.”

“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?”

“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.”

“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.”

“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.”

“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.”

“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.”

“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.”

“The timelines for a lot of our product features have gone down from six months to one month and sometimes to even one day. We want to remove every single barrier to shipping things. We want to make sure every single person on the team feels empowered to take their idea from just an idea to like out in the world in less than a week, sometimes even in a day.”

“As a PM, there should be less emphasis on making sure that you're aligning your 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? I think the PMs who do the best on AI native products are the ones who can figure out how can I shorten the time from having this idea to actually getting the product in the hands of users.”

“As code becomes much cheaper to write, the thing that becomes more valuable is deciding what to write. Like what is the right UX for this feature? What is the most delightful way that a user can experience it? It takes a lot of care and taste to figure out, okay, which of these is worth building and what is the right way to build it? That skill set can come from any background, but I think that's the most important thing.”

“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 in to the prototype you've already made and see, okay, does this new model close that gap? You want to be ready when that model jump happens.”