How Anthropic Uses Claude Fable 5 With Mike Krieger

**Dan Shipper** (0:04)
Mike, welcome to the show.

**Mike Krieger** (0:05)
Great to be here, Dan. Good to see you.

**Dan Shipper** (0:07)
So for people who don't know you, you're the head of Anthropic Labs, and you're the co-founder of Instagram. And today what I want to talk to you about is Fable 5 So Fable 5 is dropping tomorrow, recording this the day before. It's going to come out after it drops. But what I really wanted to do is bring you on the show to tell me about what it's like to use this model beyond the first day. I think when a model this powerful drops, it's so useful to have someone who's using it day in and day out to tell you, this is where it's powerful. This is how it actually changes. This is what it doesn't change. So that you kind of don't get the same AI psychosis type thing. You can actually think about, okay, this is how it fits into my life.

**Mike Krieger** (0:43)
Yeah, absolutely. And it's also just been interesting.
We've had some models in this mythos class leading up to the Fable release for a couple of months now. And I think it's very exciting to see how people will build with this externally. But I think you're also right that day one impressions, I think it really comes from getting to use this over a couple of weeks. I think we've seen that even with previous models, like the December into January usage, Opus 4.5 or Opus 4.6 was really important because people spend extended time on the model and then figure it out. Oh, actually, I wasn't pushing it hard enough. I got to go further and I got to rethink what's even possible with this generation.

**Dan Shipper** (1:21)
Totally. I mean, I don't know. I feel like there are people internally at every who have been using it, who have been like, oh my God, I think I need a new set of skills to use this model. I think you can especially see this with people who are maybe more non-technical internally and who are more on the knowledge work side of things, where they're like, I don't even know what I would use this for. The people who are orchestrating agents are like, holy shit, I feel like there's so many new things I need to learn. I'm curious for you, tell us about the difference between your impression when you first tried it and now.

**Mike Krieger** (1:47)
Yeah. I think your point on adapting workflows is a really good one. Quite literally workflows, I'll talk about that in a second, but also just in terms of like, how do I think about usage of the model? Because at first, the timing was interesting because it coincided with me transitioning from CPO into labs and going really back into builder mode. I think it was about a month and a half or two months into that that we first had one of these models available internally.
I sat there and I was like, I feel like a total newbie again, because I feel like the way that I am prompting or even thinking about decomposing a task is really out of date now with this model. Like it's no longer, and it's even thinking about the time horizon or the sort of interactivity model I think has to evolve as well. Like going from, I think early on would be like, I have an idea for this feature. Can we start by doing like, absolutely not, right?
Like, let me express more of the intent. And then just being, I remember like, Raj April be like, wow, on the one shot, it's already incredibly impressive. But then it also understands the intent around how we're going to evolve this and understands like the global context as well. So I think that's been a really interesting evolution. Till now where, I was talking to somebody this morning where, you know, I think about doing work at a flight. And I was like, okay, I can do most of this work remotely. And I don't even worry that like the Wi-Fi is going to drop out because I know that if I set up the right, you know, context instructions, like flash loop, you know, I'll see it, it'll see it through. And I think my last two months have been full of a lot of times where I will, you know, wish Claude a good night, set it off on like a pretty complex task of something of this like model class. And wake up to, you know, actually, it's usually done by like two in the morning, and I guess it just foothills its thumbs for the next four hours. But like, really impressive ability to like complete the swing, get itself out of the situation where it's like, okay, all right, well, Mike asked me to do this complex task overnight. I got stuck because this remote service went down. I'm going to write a like scaffolded like back end for it for now. So, you know, I'll document that. You know, go all the way through. I have a like good mental model of like how far that's going to get me. And when it comes back online, I'll fix it. I'll keep track of that fact. It's just like it is I think the most impressive thing for me is like you're just be able to like delegate that kind of level of task and just trust that the right thing will happen by the end. And of course, like you'll review the result and there's still like a whole verification thing that we can and should talk about, because I think that's an important part of still completing the swing there. But it's really forced me to re-think like what is being productive with one of these models look like and it is much more like we've talked for a while about, you know, like what is it like when these models are more of like a companion or a co-worker and it really feels like now it's like a teammate that I can delegate like a lot of work to.