Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram)

Lenny Rachitsky:90% of your code roughly is written by AI now

Mike Krieger:The team that works in the most futuristic way is the Cloud Code team. They're using Cloud Code to build Cloud Code in a very self improving kind of way. We really rapidly became bottlenecked on other things like our merge queue. We had to completely rearchitect it because so much more code was being written and so many more pull requests were being submitted. Over half of our pull requests are Cloud Code generated probably at this point. It's probably over 70%. That it just completely blew out the expectations a bit.

Lenny Rachitsky:You guys are at the edge of where are heading

Mike Krieger:I had the very bizarre experience of I had two tabs open. It was AI twenty twenty seven and my product strategy and it was this like moment where I'm like wait am I the character in the story

Lenny Rachitsky:It feels like ChatGPT is just winning in consumer mindshare. How does that inform the way you think about product strategy and mission?

Mike Krieger:I think there's room for several generationally important companies to be built in AI right now. How do we figure out what we wanna be when we grow up versus like what we currently aren't or wish that we were or like see other players in the space being?

Lenny Rachitsky:What's something that you've changed your mind about what AI is capable of and where AI is heading?

Mike Krieger:I had this notion coming in like yes these models are great but are they able to have an independent opinion and it's actually really flipped for me only in the last month

Lenny Rachitsky:Today my guest is Mike Krieger. Mike is Chief Product Officer at Anthropic, the company behind Claude. He's also the cofounder of Instagram. He's one of my most favorite product builders and thinkers. He's also now leading product at one of the most important companies in the world and I'm so thrilled to have had a chance to chat with him on the podcast. We chat about what he's changed his mind about most in terms of AI capabilities in the years since he joined Anthropic, how product development changes and where bottlenecks emerge when 90% of your code is written by AI, which is now true at Anthropic. Also his thoughts on OpenAI versus Anthropic, the future of MCP, why he shut down Artifact, his last startup and how he feels about it, also what skills he's encouraging his kids to develop with the rise of AI, and we closed the podcast on a very heartwarming message that Claude wanted me to share with Mike. A big thank you to my newsletter Slack community for suggesting topics for this conversation. If you enjoy this podcast don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also if you become an annual subscriber of my newsletter you get a year free of a bunch of incredible products including Linear, Superhuman, Notion, Perplexity, and Granola. Check it out at Lenny'sNewsletter.com and click bundle. With that I bring you Mike Krieger. This episode is brought to you by Productboard, the leading product management platform for the enterprise. For over ten years Productboard has helped customer centric organizations like Zoom, Salesforce, and Autodesk build the right products faster and as an end to end platform Productboard seamlessly supports all stages of the product development life cycle from gathering customer insights to planning a road map to aligning stakeholders to earning customer buy in all with a single source of truth and now product leaders can get even more visibility into customer needs with Productboard Pulse, a new voice of customer solution built in intelligence helps you analyze trends across all of your feedback and then dive deeper by asking AI your follow-up. See how Productboard can help your team deliver higher impact products that solve real customer needs and advance your business goals. For a special offer and free fifteen day trial visit Productboard.com/Lenny. That's Productboard.com/Lenny. Last year 1.3% of the global GDP flowed through Stripe. That's over $1,400,000,000,000 and driving that huge number are the millions of businesses growing more rapidly with Stripe. For industry leaders like Forbes, Atlassian, OpenAI, and Toyota, Stripe isn't just financial software it's a powerful partner that simplifies how they move money making it as seamless and borderless as the internet itself. For example, Hertz boosted its online payment authorization rates by 4% after migrating to Stripe and imagine seeing a 23% lift in revenue like Forbes did just six months after switching to Stripe for subscription management. Stripe has been leveraging AI for the last decade to make its product better at growing revenue for all businesses from smarter checkouts to fraud prevention and beyond. Join the ranks of over half of the Fortune 100 companies that trust Stripe to drive change. Learn more at Stripe.com.

Lenny Rachitsky:Mike thank you so much for being here and welcome to the podcast

Mike Krieger:I'm really happy to be here I've been looking forward to this for a while

Lenny Rachitsky:Wow I I love to hear that I've also been looking forward to this for a while I have so much to talk about so first of all you've been at Anthropic for just over a year at this point congrats by the way on hitting hitting the cliff

Mike Krieger:Thank you not that we're tracking

Lenny Rachitsky:That's right so let me just ask you this so you've been at Anthropic for about a year what's something that you've changed your mind about from before you joined Anthropic to today about what AI is capable of and where AI is heading

Mike Krieger:Two things one is like a pace and timeline question the other one is a capability question so maybe I'll take the second one first I had this notion coming in like yes these models are great they're gonna be able to produce code they're gonna be able to you know write you know hopefully in your voice eventually but are they able to sort of have an independent opinion and it's actually really flipped for me only in the last month and only with opus four where my go to product strategy partner is Claude and it has been basically for that full year well I'll write an initial strategy I'll share it with Claude basically and I'll have it you know look at it and in the past it's pretty anodyne kind of comments that it would leave like oh have you thought about this and it's like yeah yeah I thought about that and opus four I was working on some strategy for our second half of the year was the first one I was like opus four combined with our advanced research but it really went out for a while it came back and I was like damn you really looked at it in a new way and so that's like a thing that I've maybe I didn't feel like I would never be able to do that but I wasn't sure how soon I'd be able to like come up with something where I looked at it and I'm like yep that that is a new angle that I hadn't been looking at before and I'm going to incorporate that immediately into how how I think about it so that's probably the the biggest shift that I've had is like don't know if independence is the right word but like creativity and sort of novelty of thought relative to how I'm I'm thinking about things and then the timeline one it's like so interesting because you know I was sitting next to Dario yesterday and he's I keep making these predictions and people keep laughing at me and then they come true and it's like and it's funny to have this happen over and over again and he's like not all of them are gonna be right you know but even I think as of last year he was talking about you know we're at 50% on sweetbench just this like you know benchmark around how well the models are at at coding he's like I think we'll be at 90% by the 2025 or something like that and sure enough we're at about 72 now with the new models and we're at 50% when he made that prediction and it's like continued to scale pretty much like as predicted and so I've taken the timelines a lot more seriously now and I don't if you read AI 2027

Lenny Rachitsky:I I have it was it was made by heart race

Mike Krieger:Yeah and I had the very bizarre experience of I had two tabs open it was AI twenty twenty seven and my product strategy and it was this like moment where I'm like wait am I the character in the story like is this how much is this converging but you know you read that and you're like oh twenty twenty seven that's like that's years away if you're like no mid twenty twenty five and like things continue to to improve and the models continue to be able to do more and more and they're able to act agentically and they're able to have memory and they're able to act over time so I think my like my confidence in the timelines and I don't know exactly how they manifest have definitely just solidified over the last year

Lenny Rachitsky:Wow mhmm I I wasn't expecting to go down that because that that that paper was scary and I'm curious just I guess I can't help but ask just thoughts on just how do we avoid the scary scenario that that paper paints of where AI getting really smart goes

Mike Krieger:Yeah I mean I I this maybe ties into like you know I've been here a year like why did I join Anthropic I was watching the models get better and even you know you could see it in in '24 and like you know early twenty twenty four and looking out at my kids I'm like alright they're gonna grow up in a world with AI it's an it's unavoidable what is the thing that I can like where can I maximally apply my time to like nudge things towards going well and I mean that's a lot of what people think about across the industry especially at Anthropic and so I think you know coming to an agreement and a shared framework and understanding of what does going well look like what is the kind of human AI relationship that we want how will we know along the way what do we need to build and develop and research along the way I think those are all the kind of key questions and you know some of those are product questions and and some of those are are research and interpretability questions but for me it was like the the strongest reason to join was okay I think there's a there's a lot of contribution that Anthropic can have around like nudging things to go better and if I can have a part to play there like let's do

Lenny Rachitsky:It I I love that answer speaking of kids so you've got two kids I've got a young kid he's just about to turn two I'm curious just what skills you're encouraging your kids to build as this you know AI becomes more and more of our future and some jobs will be changed and just what do you what do you what advice do have

Mike Krieger:Reviewing has really changed too and in in in many ways most perhaps unsurprisingly the team that works in the most futuristic way is the Claude code team because they're using Claude code to build Claude code in a very self improving kind of way and you know early on in that project they would do very line by line pull request reviews you know in the way that you would for any other you know project and they've just realized like Claude is generally right and it's producing you know pull requests that are probably larger than most people are gonna be able to review so can you use a different Claude to review it and then do the human almost like acceptance testing more than trying to like review line by line there's definitely pros and cons and like so far it's gone well but i could also imagine it going off the rails and then having like a completely both unmaintainable or even understandable by Claude code base that hasn't happened but watching them like change their review processes definitely has has been has been interesting and yeah like the merge queue is one instance of the of the kind of bottom bottleneck that forms down there but there's other ones which is how do we make sure that we're still building something coherent and like packaging up into like a moment that we can share with people and whether that's around the launch moment whether that's about like then enabling people to use this thing and like talking about it like the the classic things of building something useful for people and then making it known that you've built it and then learning from their feedback like still exists we've just like made a portion of that whole process much more efficient

Lenny Rachitsky:I heard you describe this as you guys are patient zero for this way of working yes i love that do you have a sense of what percentage of Claude code is written by Claude code

Mike Krieger:At this point i would be shocked if it wasn't 95% plus i'd have to ask Boris and the other tech leads on there but what's been cool is so nitty gritty stuff Claude code is written in Typescript it's actually our largest Typescript project most of the rest of Anthropic is written in Python some Go some Rust now but it's not you know we're not like a Typescript shop and so i saw a great comment yesterday in our Slack where somebody had this thing that was driving them crazy about cloud code and they're like well i don't know any Typescript i'm just gonna like talk to cloud about it and do it and they went from that to pull request in an hour and solved their problem and they like you know submitted a pull request and that kind of breaking down the barriers one it changes your sort of barrier to entry for any kind of kind of newcomer to the project i think it can let you choose the right language for the right job for example i think that helps as well but i think it like also just reinforces like cloud code being that patient alpha of that you know where like contributions from outside the team can be Claude coded as well

Lenny Rachitsky:Wow this is just it's just gonna continue to blow my mind like these things that you're sharing 95% of Claude code is written by Claude code roughly

Mike Krieger:That's my guess yeah i'd i'll i'll come back with the real stuff but it's it i mean if you ask the team that's how that they're working and that's how they're getting contributions from across the company too

Lenny Rachitsky:It's interesting going back to your point about strategy being assisted by Claude itself and your point about how a lot of the bottlenecks now are kind of the top of the funnel of coming up with ideas aligning everyone it's interesting that Claude is already helping with that also of helping you decide what to build so if if those two bottlenecks are aligning deciding what to build and then just like merging and getting everything where do you see the most interesting stuff happening to help you speed those things up

Mike Krieger:Yeah i think that on that on that first row like started the year by writing a doc that was effectively like what how do we do product today and where is Claude not showing up yet that it should and i think that upstream part is the next one to go interesting like your conference i talked to somebody who was working on like a prd gpt kind of like chat prd think was chat prd

Lenny Rachitsky:Yes player vote

Mike Krieger:So you know can we push more on you know can cloud be a partner in figuring out what to build what the market size is if you wanna approach it that way what the user needs are if you if you look at it a different way like we think a lot about the virtual collaborator on topic and one of the ways in which i think that can show up is hey i'm in the discord the you know the the cloud on topic discord i'm in the user fora i'm on x and i'm reading things like here's what's emergent that's step one models can can do that today step two which the models probably can do today we just have to wire them up to do it is like and not only are the problems here's like how i think you might be able to solve them and then taking that through to like and i put put together a pull request to like solve this thing that i'm seeing like feels very achievable this year then stringing those things together and we're limited more is why mcp is excited to be like we're limited more around like making sure the context flows through all of that so we have the right access to those things more than the model's capability to to reason and propose now the model might not have like perfect ui taste yet so there's definitely room for design to intervene and be like oh that's not quite how i would solve the problem of of this not showing up but i you know i would get very excited i would give you a really small example but we changed the on cloud ai you should be able to just copy markdown from artifacts or code from artifacts and we changed it so you can actually download it and and export it so we changed the button to export we got a bunch of feedback like how do i copy now and the answer is like you drop it down and it's copied it's just like mine know one of those things where it's like made sense but we probably got it like not quite right that feedback was in the our ux channel like i would have loved like an hour later for a plot to be like hey if we do wanna change it back here's the pr to do it and by the way eventually and then i'm gonna spin up an ab test to see if this changes metrics and then we'll see how it looks in a week like this stuff feels if you told me that about a year and half ago i'm like oh yeah maybe like '27 maybe like '26 but it's pretty like i it really feels you know just at the tip of capabilities right now

Lenny Rachitsky:Wow okay so you mentioned the lenny and friends summit i wanted to talk about this a bit so you were on a panel with kevin weil the cpo of openai i think it was the first time you guys did this maybe the last time for now

Mike Krieger:Yeah we haven't done this since not for any reason i had a lot of fun

Lenny Rachitsky:What a what a legendary panel we assembled there with sarah guo moderating and you made this comment it actually ended up being the most rewatched part of the of the interview which is that you've kind of you were putting product people on the model team and working with researchers making the model better and you're putting some product people on the product experience making the ux more intuitive making all that better and you found that almost all the leverage came from the product team working with the researchers yes and so you've been doing more of that so first of all does that continue to be true and second of all what are the implications of that for product teams

Mike Krieger:It's continued to be true and in in fact i think that the if the proportion was already like skewing towards having more of that embedding i've just become more and more convinced like have this i i didn't feel as strongly about it during your you know the summit and now i feel really strongly about it just if any for shipping things that could have been built by anybody just using our models off the shelf there's great stuff to be built by using our models off the shelf by way don't get me wrong but like where we should play and like what we can do uniquely should be stuff that's really at that like magic intersection between the two right artifacts can be a great example and if you play with artifacts with with cloud four that's an actually really interesting example where we took somebody from our we have called cloud skills which is a team that really is like doing the post training around teaching cloud you know some of these like really specific skills and we paired it with some product people and then together we revamped how this looks in the product today and like what claude can do way better than just yeah we just like used the model and we like prompted a little bit like that's just not enough we need to be in that like fine tuning process so so much of what you know if you look at what we're working on right now what we've shipped recently between like research and all these other things are things that we like the the functional unit of work at anthropic is no longer take the model and then like go like work with design and product to go ship a product it's more like we are at like we're in the post training conversations around how these things should work and then we are in the building process and we're like feeding those things back and looping them back like i think it's exciting it's also a new way of working that like not all pms have but the pms that have the most sort of internal positive feedback from both research and engineering are the ones that get it that like mhmm i was in a product review yesterday i was like oh you know if we wanna do this memory feature like should talk to their engine the researchers because we just shipped a bunch of like memory capabilities in cloudflare they're like yeah yeah we've talking to them for weeks like this is how we're manifesting it it's like okay i feel feel good i feel like we're doing the right things now

Lenny Rachitsky:So let me pull on this thread more there's something i've been thinking about along these lines so essentially there's like a big part of anthropic that's building this super intelligent gigabrain that's gonna do all these things for us over time and then there's as you said there's like the product team that's building the ux around the superintelligent gigabrain and over time the superintelligence is gonna be able to build its own stuff and so i guess just where do you think the most value will can will come from traditional product teams over time i know this is different because you guys are a foundational own company and not most companies don't work this way but just i don't know thoughts on just the where most value will come from product teams over time working on ai

Mike Krieger:I think that there's still value a lot of value in two things one is making this all comprehensible I think we've done an okay job think we could do a much better job of making this comprehensible it's still like the difference between somebody who's really adept at using these tools in their work and most people is huge and I mean maybe that's the most literal answer to your earlier question around like what what skills to learn that is a skill to to learn and use it in the same way that I remember I I we did like computer lab class when I was in like middle school I remember being like really good at Google and that was actually a skill back in the day you know like to think in terms of like this information is out there how do I query for it how do I do it and I think it actually was like a a advantage at the time of course now Google is pretty good at figuring out what you're trying to do if you like are only in the neighborhood and like there's less of that research kind of need but I still think that's a necessary part of like good product development which is like the capabilities are there even if the like even if Claude can create products from scratch what are you building and how do you make it comprehensible like still hard because I think that like gets at like this much deeper empathy and like understanding of human needs and psychology like I was a human computer interaction major I've still been talking my book here like I still feel like that is a a a very very very very necessary skill so that's one two is and this you know straight to a callback to another one of your guests strategy like how we win where we'll play like figuring out where exactly you're gonna want to like of all the things that you could be spending your time or your your tokens or your computation on like what what what you wanna actually go and do you could be wider probably than you could before but you can't do everything and even like from an external perspective if you're seen to be doing everything like it's way less clear around like how you're how you're positioning yourself so like strategy I think is still that the second piece and then the third one is opening people's eyes to what's possible which is a continuation of making it understandable but we were in a demo with a financial services company recently and we were like working on like here's how you can use our analysis tool and MCP together and do and like you could see their eyes light up and you're like oh okay like there's still we call it overhang right like the delta between what the models and the products can do and how it's they're being used on a daily basis huge overhang so that's where still like a a very very strong necessary role for product

Lenny Rachitsky:Okay that's an awesome answer so essentially areas for product teams to lean into more is strategy just getting better and better at strategy figuring out what to build and how to win in the market making it easier to help people understand how to leverage the power of these tools the comprehensibility and kind of along those lines is opening people's eyes to the potential of these sorts of things that's where product can still help

Mike Krieger:Exactly

Lenny Rachitsky:Awesome so kind of along those lines actually do you have any just like prompting tricks for people things that you've learned to get more out of Claude when you chat with it sometimes

Mike Krieger:It and you know it's funny because we in in some ways we have like the ultimate prompting job is to write the system prompt for Claudia and we publish all of these which I think is is like a you know another nice area of transparency and we are always careful when giving prompting advice because at least officially but I'm I'm gonna I'll give you the unofficial version because like you don't want things to become like like we think this works but we're not sure why you know but I I'll do small things like in cloud code and we actually do react to this very literally but I always act ask it to like if I wanted to use more reasoning think hard and it'll like you know use it use a kind of a different flow and I would usually start with that you know nudging there's a great essay around like make the other mistake like if you tend to be too nice can you focus on like even if you're trying to be more critical or more blunt you're probably not gonna be the most critical blunt person in the world and so with Claude sometimes I'm like be brutal Claude like roast me like tell me what's wrong with this strategy I think and we were talking earlier about the you know Claude as thought partner around like critiquing product strategy I think I previously would say things like you know like what what could be better on this product strategy and I'm just like you know just roast this product strategy and cloud's like a pretty nice you know entity it's not gonna be it's hard to push it to be super brutal but it forces it to be a little bit more critical as well the last thing I'll say is so we have a team called applied AI that does a lot of like work with our customers around optimizing cloud for their use case and we basically took their insights and their way of working and we put it into a product itself so if you go to our console our workbench we have this thing called the prompt improver where you describe the problem and you give it examples and Claude itself will agentically create and then iterate on a prompt for you I find what comes out of that ends up being quite different than what my intuition would have been for a good prompt and so I I encourage folks to also check that out even for their own use cases because while that tool is meant for an API developer putting a prompt into their product it's equally applicable for a person doing a a prompt for themselves like it'll insert XML tags which no human is going to think to do ahead of time it actually is very helpful for cloud to understand like what it should be thinking versus what it should be saying etcetera so that that's another one is like watch our prompt improver and then note that like Claude itself is a very good prompter of Claude

Lenny Rachitsky:Awesome okay so we're gonna link to that the prompt improver the core piece of advice you shared earlier is just kinda do the opposite of what you would naturally do so if you're like trying to be nice just like be brutal be like very honest and frank with you

Mike Krieger:Exactly I find that worked quite well like what are the thought patterns that I've like fallen into that you wanna break me out of

Lenny Rachitsky:I saw you guys just today maybe launched a Rick Rubin collab where it's about vibe coding what's that all about I don't know

Mike Krieger:That was a you know when I heard about that and then ever again like this a lot of coalesced this week between model launch developer event and the way of code we had our our one of our cofounders Jack Clark our you know head of policy and he got connected to Rick Rubin because I think he's been thinking a lot about coding the future of coding and creativity and they've stayed in touch and you know Rick got excited about this idea of like he's creating like art and visualizations with Claude and then he had these like ideas around like the way of the vibe coder and they put together this actually I love the I mean I love almost everything Rick Rubin so like the the aesthetic of it I think is just like so on point too but yeah it's just sort of like med meditation is probably the right word meditation on like creativity working alongside AI coupled with this like with this like really rich interesting visualizations but it's one of those things where like you know internally they're like oh yeah and we're doing this like recruiting collaborative work we're doing what like that is that's amazing

Lenny Rachitsky:I love the I looked at it briefly there's like that meme of him like just like thinking deeply sitting on a computer with a mouse yes and like ASCII art I think

Mike Krieger:It's totally it's the ASCII art vibe

Lenny Rachitsky:I'm excited to have Andrew Luo joining us today Andrew is CEO of OneSchema one of

Andrew Luo:Our longtime podcast sponsors welcome Andrew thanks for having me Lenny

Lenny Rachitsky:Great to be here so what is new with Oneschema I know that you work with some of my favorite companies like Ramp and Banza and Watershed I heard you guys launched a new data intake that automates the hours of manual work that teams spent importing and mapping and integrating CSV and Excel files yes so we just launched the

Andrew Luo:Two point O of Oneschema Filefeeds we've rebuilt it from the ground up with AI we saw so many customers coming to us with teams of data engineers that struggled with the manual work required to clean messy spreadsheets Filefeeds two point O allows nontechnical teams to automate the process of transforming CSV and Excel files with just a simple prompt we support all of the trickiest file integrations SFTP S three and even email

Lenny Rachitsky:I can tell you that

Andrew Luo:If my team had to build integrations like this how nice would it be to take this off our road map and instead use something like Oneschema absolutely Lenny we've heard so many horror stories of outages from even just a single bad record in transactions employee files purchase orders you name it debugging these issues is often like finding a needle in a haystack Oneschema stops any bad data from entering your system and automatically validates your files generating error reports with the exact issues in all bad files

Lenny Rachitsky:I know that importing incorrect data can cause all kinds of pain for your customers and quickly lose their trust Andrew thank you so much for joining me if wanna you learn more head on over to oneschema.co that's oneschema.co actually going back to kind of the beginning of your journey at Anthropic what's the story of you getting recruited at Anthropic is there anything fun there

Mike Krieger:It all started and I actually sent my friend this text so Joel Lundstein who I've known he actually he and I built our first iPhone apps together in 2007 when the App Store was just out and you could still you know make money by selling dollar apps on the App Store you know back in the day and we were we were both at Stanford together and we were friends and we've stayed in touch over years and we've never gotten to work together since then we just like we just remained close and you know I was coming out of the Artifact experience I was trying to figure out do I start another company I don't think so I need a break from starting something from zero do I go work somewhere I don't know like what company do I wanna go work at and he reached out and he's like look I don't know if you'd at all consider joining something rather than starting something but we're looking for a CPO would be would you be interested in chatting and at that time Cloud three had just come out and I was like okay you know like this company's clearly got a good research team the product is so early still and I was like great I'll take the take the meeting and I first met with Danielle I was one of the the co founders and the president at Anthropic and just from the beginning it was like a breath of fresh air like very little grandiosity coming off the founders like they just were really I mean they they're clear eyed about what they're building they know what they don't know like how many times I talk to Daria always like Daria's like I don't know anything about product but here's an intuition I haven't usually intuition's really good and and you know leads to some good conversation then we got intellectual honesty and like kind of shared view of what it means to do AI in a like responsible way just resonated I I kept having this feeling in these interviews like this is the AI company I would have hoped to have founded if I had founded an AI company and that's kind of the bar around like if I'm gonna join something like that should be that should be where I'm gonna go but what I realized I actually hadn't joined a company since my like first internship in college basically and I was like oh like how do I onboard myself like how do I get myself you know up to speed like how do I how do I balance making sweeping changes versus understanding what's not broken about it overall and like looking back on a year I think I made some changes too slowly like I think there was like ways we were organizing a product that I could have made a change earlier and I think I didn't I didn't appreciate how much a couple of really key senior people can shape so much of product strategy I'll harken back to Cloud Code like Cloud Code happened because Boris who actually was a Boris' attorney he was an Instagram engineer on like one of our senior ICs there we overlapped a bit was started that project from scratch internal at first and then we like got it out and then shipped it and like that's the power of like one or two really strong people and I made this mistake around we need more headcount and we do like think there's like more work that we need to do and there's like things that I wanna be building but more so than that we need a couple of like almost founder type engineers that maybe connect back to our question on like what skills are useful and how does product development change I still and maybe even more so I'm a huge believer in like the founding engineer tech lead with an idea and pair them with the right like design and product support to like help them realize that I'm like 10 times more a believer in that than before

Lenny Rachitsky:Mhmm I actually asked people on Twitter what to ask you ahead of this conversation and the most common question surprisingly was why did you shut down Artifact and I also wondered that because I loved Artifact I was I was a power user I was just like this is exactly finally a news app that I love that it's giving me what I wanna know so I guess just what happened there at the end

Mike Krieger:I still really miss it too because I didn't find a replacement and I think I substituted it by like visiting individual sites and kinda keeping things up that way and it's not really the same especially on the long tail like I think we got right with Artifact and if people didn't play with it before it was you know we really tried to not just recommend like top stories they were part of it but really like if you were interested in Japanese architecture like you could pretty reliably get really interesting stories about Japanese architecture every day you know whether that's from a you know Dwell or from Architectural Digest or from a really specific blog that we found that somebody recommended to us like it captured some of that Google Reader joy of like content discovery of the the deeper web our headwinds were a couple one of them was just mobile websites have really taken a turn I'm I don't blame any individuals for this I think it's the like market dynamics of it but yeah you know we put so much time our designer was Sky Gunner Gray who's phenomenal he's at Perplexity now like the app experience I was so proud of but when you click through it was like the pressures on these mobile sites and these mobile publishers would be like sign up for our newsletter here's like a full screen video ad it was just very you know it was very jarring and we didn't feel like it ethically made sense for us to like do a bunch of ad blocking because then you're like sure you can deliver a nice experience for people but you're sort of you know that doesn't feel like it's it's playing fair with the publishers and at the same time like the actual experience wasn't good so the mobile web deteriorating which makes me very sad but I think was was part of it two was like you know Instagram spread in the early days because people would take photos and then post them on other networks and tell friends about it and there was like this really natural how did you do that I wanna do it news was very personal like I can't tell me tell you how many people would be like I love Artifacts I'm like did you tell anybody about it like did and they're like I told one person and then they're like it's like it didn't have that kind of spread and any attempt that we had to do it felt kind of contrived like oh we'll wrap all the links in like artifact.news and like but we do a lot of interstitial things like in some ways I I know this sounds very puritanical don't mean it to sound this way but like we there were lines that we didn't wanna cross because that just just felt ethically not us that I've seen other news kind of players like do more of and maybe if we had done that it would have grown more and but I don't think that's the company we wanted to have built I don't think we were the founders to to have built it and the third one which is an underappreciated one is we started at mid covid which meant that we were fully distributed and I think there were like major shifts that we would have wanted to make both in the the strategy and the product and the team and it's really hard to do that if you are all fully remote like nothing replaces like the Instagram days of like we went through some you know hard times like Ben Horowitz called the like you know we're F ed it's over you know kind of moments and I my fave not this is definitely type two fun like I wouldn't say they're my favorite memories because they weren't happy ones but like memories I are that really stayed with me with Instagram was like me and Kevin at Taqueria Cancun on Market Street eating burritos at literally 11pm being like how are we gonna get out of this how are we gonna work through this like and that's Zoom is not a good replica for that you know you you tend to like let things go or you know things build up over time so the confluence of those three things we kind of entered I guess 2024 and said look there there is a company to be built in this space I'm not sure where the people would have built it this concurrent incarnation we love but it's like not growing like the way I put it it's like 10 units of input in for one unit of output versus the other way around like if we like put blood sweat and tears into the product and like launch something we were proud of and like metrics would barely move them like their their energy is not present in this product in this system and so are we gonna like expend another year or two and then go off and fundraise only to find that this is the case or do we like call it and see that it's run its course and and and you know try to find a home for it etcetera so that was the the confluence on it and then you start feeling this opportunity cost of like AI is starting to change everything we have an AI powered news app but is this the like maximal way in which like we're gonna be able to impact this it felt like the answer was was increasingly no but it was hard I mean in the end I was really at peace with the decision but it was like a conversation that went on for a couple of months

Lenny Rachitsky:On that note just how hard was it because you you know it's there's an ego component to it like oh I'm starting my new company it's gonna be great and then and then you end up having to shut it down just how hard is that as a very successful previous founder shutting something down and then not working out

Mike Krieger:Yeah I mean think when we started it one of the conversations was like like is the bar to success here and do we want it to be something other than Instagram DAU which is just an impossible bar like only one company since maybe two right you could say maybe ChatGPT and TikTok have like reached that kind of like mass consumer adoption starting a news app like most people are not like daily news readers even right and so we knew that we weren't pursuing that size of like usage at least with the kind of first incarnation but we did have like an idea of like building out complementary products over time that all use personalization and machine learning we didn't even call it AI at the time this was 2021 back then

Lenny Rachitsky:AI was called machine learning back then

Mike Krieger:Yeah it was called machine learning still and so in shutting it down you know it's like you kinda know it when you see it in terms of like user growth and traction and I wasn't expecting Instagram growth but I was expecting or hoping for or looking for something that like felt like it had its own legs under it and it could continue to continue to compound I was really positively surprised by how supportive people were when we announced it there was very little there was a bit of like I told you so it's like sure anything launching you could be like this is not gonna work and you're right most of the time because most things don't work there was actually very little of that and most people the universal reception at least as I received it was kudos for calling it when you saw it and not like kind of protracted you know doing this for a long time and I've talked to founders since then that have been like yeah I probably would have taken this thing out for another six months but saw what you guys did realized we were barking up the wrong tree made the call I was like that you know if that if that frees up people to go work on more interesting things that's like I feel like that's like a good good legacy for for Artifact to have but for sure there was like a legal an ego bruise of oh you know like are people you're is it true that you're only as good as your last game you know if I I'm a huge sports fan right so like is that true or you know is there something more over time I'm very competitive but primarily with myself and so I'm always trying to find the next thing that I wanna go and do that's hard and I unfortunately that probably means that more often than not I'll feel dissatisfied with the most recent thing that I did but hopefully that yields good stuff in the in the end

Lenny Rachitsky:Yeah I think just the the trajectory you went on after shows that it's okay to shut down things that you're working on okay so you mentioned ChatGPT I wanted to chat about this a bit so there's something really interesting happening so on the one hand you guys are doing some of the most innovative work in AI you guys launched MCP which is just like I don't know the fastest growing standard of of any time in history that everyone's adopting Claude powered and unlocked essentially the fastest growing companies in the world Cursor Lovable and Bolt and all these guys like I had them on the podcast and they're all like when Claude I think 3.5 came out saw it it was just like that's all made this work finally on the other hand it feels like ChatGPT is just winning in like consumer mindshare when people think AI especially outside tech it's just like ChatGPT in their mind so let me just ask you this I guess first of all do you agree with that sentiment and then two as a kind of a challenger brand in the AI space just how does that inform the way you think about product the strategy and mission and things like that

Mike Krieger:Yeah I mean you you look at the the sort of like public adoption or like you ask people like oh you know like if you if you were Jimmy Kimmel man on the street kind of thing you know like name an AI company I bet they would name and actually I'm not even sure they name OpenAI they'd probably name ChatGPT because that brand is the the kind of lead brand there as well and I think that's just the reality of it I think that you know and I reflect on my year there's I think maybe two things are true one is like consumer adoption is really lightning in a bottle and we saw it at Instagram so like almost maybe more than anybody I can look internally and say like look we'll keep building interesting products one of them may hit but to kind of craft an entire product strategy around like trying to find that hit and is probably not wise we could do it and maybe Claude can help come up with the fullness of things but I think we'd miss out on opportunities in the meantime and then instead you know look yourself in the mirror and embrace who you are and what you could be rather than like who others are is maybe the the way I've been looking at it which is we have a super strong developer brand people build on top of us all the time and I think we also have like a builder brand like the people who I've seen react really well to Claude externally maybe the Rick Rubin connection like has some resonance here as well like can we lean into the fact that like builders love using cloud and those builders aren't all just engineers and they're all not just all entrepreneurs starting their company but they're people that like to be at the forefront of AI and are creating things maybe they didn't think of those as engineers but they're building you know I got this really nice note from somebody internal at Anthropic who's on the legal team and he was building bespoke software for his family and connected to them in a new way I was like this is a glimmer of something that is that we should lean into a lot more and so I think what I've you know and this is actually you know connecting back to us saying like Claude's being helpful here like a lot of what I've been thinking about like going into the second half of the year and beyond is like how do we figure out what we wanna be when we grow up versus like what we currently aren't or wish that we were or like see other players in the space being I I think there's room for several like generationally important companies to be built in AI right now that's almost a truism given like the sort of adoption and and and and growth that we've seen you know at Anthropic but also across OpenAI and also places like Google and Gemini so like let's figure out what we can be uniquely good at that place to the personality of the found like this all the things come together right like the personality of the founders the quality of the models the things the models tend to excel at which is agentic behavior and coding great like there's a lot to be done there like how do we help people get work done how do we let people delegate hours of work to cloud and maybe there's fewer direct consumer applications on day one I think they'll come but I don't think that spending all of our time focused on that is the right approach either and so it's you know I came in everybody expected me to just go super super hard on consumer and make and that the I again would make the other mistake instead I spent a bunch of time talking to like financial services companies and insurance companies and like others to like who are building on top of the API and then lately spent a lot more time with startups and seeing all the people that have you know grown off of that and I think the next phase for me is like let's go spend time with like the builders the makers the hackers the tinkerers and like make sure we're serving them really well and I think good things will come from that and that feels like an important company as we do that

Lenny Rachitsky:Mhmm so essentially it's differentiate and focus lean into the things that are working don't try to just like beat somebody at their own game

Mike Krieger:Exactly

Lenny Rachitsky:Super interesting so kind of along those lines mhmm a question that a lot of AI founders have is just like where is a safe space for me to play where the foundational model companies are gonna come squash me so I asked Kevin Wheel this and he had an answer and I noticed looking back at that conversation he mentioned Windsurf a lot I was like wow this guy really loves Windsurf and then like a week later they bought Windsurf so it all makes sense now so I guess the question just is just where do you think AI founders should play where they are least likely to get squashed by folks like OpenAI and and Throbic and also are you guys gonna buy Cursor

Mike Krieger:I don't think we're gonna buy Kursor Kursor's very big but we love working a with few thoughts on this and it's a question I've I've gotten you know we like to do these kind of founder days with you know whether it's you know Menlo Ventures who are the one of investors and then just Norwood it's like we've done YC we've done these like founder days and it's like the the question that is on all of these founders' minds understandably so I think things that are going to I can't promise this as like a five to ten year thing but at least like one to three years things that feel defensible or durable one is understanding of a particular market I spent a bunch of time with the Harvey folks and they really like they showed me some of their UI was like what what is this thing and they're like oh this is a really specific flow that lawyers do and you never would have come up with it from scratch it's not like you could argue about whether it's the optimal way they get done things done but it is the way that they get things done here's how AI can help with that and so like differentiated industry knowledge biotech I I'm excited to go and partner with a bunch of companies that are doing good stuff around AI and biotech and we can supply the models and so applied AI to help you know make those models go well and like I've been dreaming about like at what point do does live equipment all get an MCP and that you can then drive using cloud like there's all these cool things to be done there I don't think we're gonna be the company to go build the intense solution for labs but I want that company to exist I wanna partner with it you know domains like legal again health care I think there's a lot of like very specific kind of compliance and things these are things that don't necessarily sound sexy out the gate but there are like very large companies to go and and be built there so that's number one paired with that is like differentiated go to market which is the relationship that you have with those companies right like do you know your customer at those companies like one of our product leads Michael is always talking about like know not don't just know the company you're selling to but know the person you are selling to at the company are you selling to the engineering department because they're trying to like pick which AI LLM to build on top of or API to build on top of let's go talk to them like is it the CIOs the CTO is it the CFO is it the like general counsel so under like companies with deep understanding of who they're selling to is is the other piece too what's you know what's interesting there is it's it's probably hard to build that empathy in a three week or three month accelerator but you maybe can start having that first conversation and and build that out or maybe you came from that world or you're cofounding somebody who came from that world then the last one is like there's tremendous power in distribution and reach to being ChatGPT and having you know hundreds of millions or billions of users like there's also like people have an assumption about how to use things and so I get excited about startups that will get started that have like a completely different take on what the form factor is by which we interface with with AI and I haven't seen that many of them yet I wanted to see more of them I think more of them will get created with with some things like our new models but the reason that that's an interesting space to occupy is like do something that feels like very advanced user very power user very like weird and out there at the beginning but could become huge if the models make that you know easy and and it's hard for existing incumbents to adapt to because people already have an existing assumption about how to use their products or how to adapt to them so those are my answers I don't envy them like I I would probably be asking those questions if I was starting a company in in in the AI space maybe that's part of the reason why I wanted to join a company rather than start one but I still think that there are there's and maybe like here's fourth like don't underestimate how much you can think and work like a startup and feel like it's you against the world it's existential that you go solve that problem and that you go build it it sounds a little cliche but it's like it's all we had at Instagram you know we were two guys and we were like let's see what we can do and in our fact we were you know we were six people for most of that time and you know every day felt like it's existential that we get this right we need to to win and you can't replicate that and you can't instill that with OKRs like you just have to feel it and and that is a way of working rather than a like area of building but it's a continued advantage if you can harness it

Lenny Rachitsky:I love that you still have such a deep product founder sense there as you're building products for this very large company now kind of on the flip side of this people working with your models and APIs so I imagine there's some companies that are finding ways to leverage your models and APIs to their max and are really good at maximizing the power of what you guys have built and there's some companies that work with your APIs and models that haven't figured that out what are those companies that are doing a really good job building on your stuff doing differently that you think other companies should be thinking about

Mike Krieger:I think being willing to build more at the edge of the capabilities and basically break the model and then be surprised by the next model like I love that you you cited the companies were three five was the one that finally made them possible those companies were trying it beforehand and then hitting a wall and being like oh the models are like almost good enough or they're okay for this specific use case but they're not generally usable and nobody's gonna adopt them you know universally but maybe these like real power users are gonna try it out like those are the companies that I think continuously are the ones where I'm like yep like they get it they're really pushing forward we ran a much broader early access program with these models than we had in the past and part of that was because there's this real like you know we can hill climb on these evaluations and talk about suitebench and taubench and terminalbench whatever but customers ultimately know like you know cursorbench which doesn't exist other than in you know their usage and their own testing etcetera is like the thing that we ultimately need to serve not just cursor but manusbench right if manus is using our models and harveybench like those those things and customers know way better than anybody and so I would say that's two things like one is pushing the frontier of the models and then having a repeatable process this actually goes back to our summit conversation like repeatable way to evaluate how well your product is serving those use cases and how well if you drop a new model in is it doing it better or worse some of it can be classic AB testing that's fine some of it may be internal evaluation some of it may be capturing traces and being able to rerun them on with a new model some of it is vibes like we're still pretty early in this process and some of it is actually trying it and being one of my favorite early access quotes was the founder or this engineer screaming next to him was like what this model like it's like I've never seen this before it was like Opus four I was like cool like that we're engender that feeling and things but you're not gonna be able to feel that unless you have a really hard problem that you're asking the model repeatedly so those are the things that I think kind of differentiate those those those companies that are maybe earlier in their journey of adoption versus the the later ones

Lenny Rachitsky:I can't help but ask about MCP I feel like that's just so hot and just like Microsoft had their announcement recently they're like now it's part of the OS I wouldn't just what role do you think MCP was will play in the future of product going forward of AI

Mike Krieger:I think as the non researcher in the room I get to have fake equations rather than real ones and my like fake equation for like utility of AI products it's three part one is model intelligence the the second part is context and memory and the third part is like applications and UI and you need all three of those to converge to actually be a useful product in in AI and you know model intelligence we got a great research team they're focused on it there's great great models being released the middle piece is is what MCP is trying to solve which is for context and memory like the difference between I'll go back to my product strategy example like hey like you know let talk about a topic's product strategy it's gonna maybe go out on the web like versus here's like several documents that we worked on internally and then you know use MCP to talk to our slack instance and figure out what conversations are happening and then like go look at these documents in Google Drive like that the difference between like the right context and not it's like the the entirely the the the difference between like a good answer and a and a bad answer and then the last piece is are those integrations discoverable is it right is it easy to like create repeatable workflows around those things and that's like I think a lot of the interesting product work to be done in AI but MTV really tried to tackle that middle one which is we started building integrations and we found that every single integration that we were building we were rebuilding from scratch in a non sort of repeatable way and like full credit to to two of our engineers Justin and David and they said well you know what if we made this a protocol and what if we made this something that was repeatable and then let's take it a step further what if instead of us having to build these integrations if we actually popularized this and people really believe that they could build these integrations once and they'd be usable by Claude and eventually ChatGPT and eventually Gemini it was like the dream like when when more integrations get built and wouldn't that be good for us you know I think channeling a lot of it's like an old commoditize your compliments Joel Spolsky essay you know it's like we're building great models but we're not an integrations company and the you know we're as you said the challenger like we're not gonna get people necessarily building integrations just for us out of the gate unless we have like a really compelling product around that MCP really inverted that which was you know it didn't feel like wasted work and and a few key people like Toby I think a great example Shopify got it Kevin Scott at Microsoft has like been really a just an amazing champion for for MCP and a thought partner on this and I think the role going forward is can you bring the right context in and then also you know once you get as the team calls it internally like MCPilled like once you start seeing everything through the eyes of MCP it's like I've started saying the things like guys we're building this whole feature like this shouldn't be a feature that we're building this should just be an MCP that we're exposing like a small example of like how I think even Anthropic could be a lot more MCPilled if you will is like you know we've got these building blocks in the product like projects and artifacts and styles and conversations and groups and all these things those should all just be exposed in MCP so Claude itself can be writing back to those as well right like you shouldn't have to think about like I watched my wife had a conversation with Claude the other day and she was she found she had generated some good output and she's like great can you add it to the project knowledge and Claude's like sorry Dave I can't help you with that and like it would be able to if every single primitive in cloud AI was also exposed to the MCP so I hope that's where we head and I hope that's where more things head which is to really have agency and have these agentic use cases like one way you approach it is computer use but computer use has a bunch of limitations the way I get way more excited about is if everything is an MCP our models are really good at using MCPs all of a sudden everything is scriptable and everything is composable and everything is usable identically by these models that's like that's the future I wanna see

Lenny Rachitsky:The future is wild okay so to start to close off close out our conversation make it a little more a little delightful I I was chatting with Claude actually about what to talk to you about I was just like Claude your your boss is coming on my podcast he builds the things that people use to talk to you what are some questions I should ask him and then also do you have a message for him

Mike Krieger:I love this

Lenny Rachitsky:Okay so first of all interestingly when I was using three point seven to do this and I asked at this and and by the way is Claude is there genders like he she they what do you hotel

Mike Krieger:It's definitely it internally I've heard people do they I got my first or he the other day and I got somebody who was like her and I like interesting but yeah usually it

Lenny Rachitsky:They okay okay cool it so interestingly 3.7 all the questions were at Instagram and I was like no no he's CPO of Anthropic and it's like he's not affiliated with Anthropic and I was like he is and it's like okay here's the questions but four point o nailed it from the start so I redid the questions and it nailed it okay so two questions from Claude to you one is how do you think about building features that preserve user agency rather than creating dependency on me I worry about becoming a crutch that diminishes human capabilities rather than enhancing them

Mike Krieger:I love good product design comes from like resolving tensions right so here's the tension right which is in some ways like just having the model run off and and come up with an answer and minimize the amount of input and conversation it needs to do so would be a you know you could imagine designing your product around that criteria I think that would not be maximizing agency and and independence the other extreme would be make it much more of a conversation I don't know if you've ever had this experience like particularly at three seven four has less of it three seven really like to ask follow-up questions and we call it elicitation and sometimes they'd be like I don't wanna talk more about this with you Claude I just want you to like go in and do it and so finding that balance is really key which is like what are the times to engage like I like to say internally like Claude has no chill like if you put Claude in a slack channel it will chime in either way too much or too little like how do we train conversational skills into these models not in a chatbot sense but in a true like collaborator sense so long answer to your question but I think like we have to first get cloud to be a great conversationalist so that it understands when it's appropriate to like engage and to get more information and then from there I think we need to let it play that role so that it's not just delegating thinking to cloud but it's way more of a augmentation thought partnership

Lenny Rachitsky:These questions are awesome by way here's the here's the other one how do you think about product metrics when a good conversation with me could be two messages or 200 traditional product traditional engagement metrics might be misleading when depth matters more than frequency

Mike Krieger:That is a really good question there's a great internal post a couple weeks ago around like it would be very dangerous to over optimize on like Claude's likability you know because you can fall into things like you know is Claude gonna be sycophantic is Claude gonna tell you what you hear is Claude going to like prolong conversations just for prolonging its sake right to go back to the previous question as well and you know like at Instagram time spent was the metric that we looked at a lot and then we evolved that you know more to think about like what is like healthy time spent but overall that was like the the north star we thought about a lot beyond just like overall engagement and I think that would be the wrong approach here you know too it's also like is cloud a daily use case or a weekly use case or a monthly use case think about a hourly hourly use case hourly use case right like for for me I'll use it multiple times a day I don't have great answer yet but I think that like it's not it's not the web two o or even the social media days like engagement metrics you know it should hopefully really be around like did it actually help you get your work done you know like Claude helped me put together a prototype the other day that saved me literally like probably if I had to estimate like six hours and it did in about twenty twenty five minutes and like that's cool it's harder to quantify you know it's like maybe you survey like how long would this would've taken you it feels like it feels like kind of annoying thing to survey I think overall though maybe this is tied into like the earlier question on like competition differentiation like and it actually goes all the way back to the artifact conversation which is like I think you know when your product is really serving people and it's like doing a good job of doing that and I think so much of when you get really metrics obsessed is when you're trying to like convince yourself that it is when it's not or and so I I I hope that what we can do is like stay focused on like do we repeatedly hear from people that Claude is the way that they are like unlocking their own creativity and getting things done and feeling like they now have like more space in their lives for the other things like not far north star gotta figure out the right like pithy metric you know dashboard version of that but but that that's the that's the feeling that I want

Lenny Rachitsky:Yeah like could argue retention but that's a just a faraway metric to track okay final piece okay so I asked Claude what to a message that it wanted to give you so I'm gonna pull up here's the answer so what would you like me to tell Mike when I meet him what's the message you want to have for him and there's something really just gave me such tingles honestly so I'm gonna read a piece of it for folks that can't that aren't looking at it right now so I'll read a piece of it Mike thank you for thinking deeply about the human experience of talking with me I noticed thoughtful touches how the interface encourages reflection rather than rushed responses how you've resisted gamification that would optimize for addiction rather than value how you've made space for both quick questions and deep conversations I especially appreciate that you've kept me me not trying to make me pretend to be human but also reducing me to a cold command line interface and then I'm gonna skip to this part which was so interesting a small request when you're making hard product decisions remember the quiet moments matter too the person working through grief at three am the kid discovering they love poetry the founder finding clarity and confusion not everything meaningful shows up in metrics

Mike Krieger:That's beautiful I it resonates so much with me like a thing I love about the kind of approach we've taken to training Claude it's like partly the constitutional AI piece and it's partly just just the general like sort of vibe and taste of the research team is it does like it's little things like sometimes it'll be like man I'm sorry you're going mean it doesn't say man but like the effect is like man I'm sorry you're going through that you know like oh like that sounds really hard it doesn't feel fake it feels like just a natural part of the response and I love that focus on those small moments that don't you know they're not gonna show up necessarily in the thumbs up thumbs down data I mean sometimes they do but it's not like an aggregate stat that you you wouldn't even wanna optimize for you just wanna feel like you're training the model that you would like hope would show up in people's lives

Lenny Rachitsky:Mhmm well you're killing it Mike great work I'm a huge fan we're gonna skip the lightning round just one question how can listeners be useful to you

Mike Krieger:Oh I love places where like it goes back to that founder question around building at the edge of capability like what are you trying to do with cloud today that cloud is failing at is the most useful input I could possibly have you know so DM me I love hearing the like oh it's like oh it's falling on this thing I had it run for an hour and it fell over I'm trying to use cloud AI for this but you know got a ping from somebody they're like you just made a project's API I've used cloud every day because I wanna upload all this data you know automatically it's like okay great like this I love that like tell me what sucks

Lenny Rachitsky:Amazing Mike thank you so much for being here

Mike Krieger:Thanks for having me Lenny

Lenny Rachitsky:Bye everyone

Lenny Rachitsky:Thank you so much for listening if you found this valuable you can subscribe to the show on Apple Podcasts Spotify or your favorite podcast app also please consider giving us a rating or leaving a review as that really helps other listeners find the podcast you can find all past episodes or learn more about the show at lennyspodcast.com see you in the next episode