The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code. | Dan Shipper (Every)

Lenny Rachitsky:The business you're building the team you're building the way you're operating is the very bleeding edge of how companies are trying to operate in this AI era

Dan Shipper:We have a head of AI operations she's just constantly like building prompts and building workflows so that I and everyone else on the team are just automating as much as possible

Lenny Rachitsky:What are some things that you believe about AI that most people don't

Dan Shipper:I hate the headlines that are like entry level jobs are taken away by AI whenever I see a kid with HGPT I'm like holy shit they're gonna go so much faster than any other person that I've worked with we have this guy he made like a year's worth of progress in two months because every time I sat down with him and told him okay here's how you tell a story here's how you think about a headline like he recorded all of it put it into a prompt and he never made the same mistake twice

Lenny Rachitsky:There's this sense we're getting to a place where you don't have to write any code like you have a product team not writing code at all

Dan Shipper:No one is manually coding anymore organizations like ours people who are playing at the edge we're doing things that in like three years everybody else is gonna be doing

Lenny Rachitsky:Today my guest is Dan Shipper Dan is the cofounder and CEO of Avery which is a company that is at the very bleeding edge of what is possible with AI their team of just 15 employees has built and shipped four different products they publish a daily newsletter and they have a consulting arm that helps companies adopt the latest AI best practices on their product team their engineers don't handwrite a single line of code and instead use an arsenal of agents who help them craft requirements and build their products their editorial arm uses AI to publish better work faster and they even have a person whose entire job is to help every employee at the company become more efficient using the latest AI workflows in our conversation Dan shares a bunch of tactics that they use internally to increase the leverage of their own employees his personal AI tool stack the one predictor that he's found for whether a company will successfully find huge productivity gains through AI how he's building his company in a really unique way a bunch of predictions for where AI is going and so much more if you enjoy this podcast don't forget to subscribe and follow it in your favorite podcasting app or YouTube and also if you become an annual subscriber of my newsletter you get a bunch of amazing products for free for one year including Superhuman Linear Notion Perplexity Bolt Granola and more check it out at Lenny'snewsletter.com and click bundle with that I bring you Dan Shipper this episode is brought to you by CodeRabbit the AI code review transforming how engineering teams ship faster with AI without sacrificing code quality code reviews are critical but time consuming CodeRabbit acts as your AI copilot providing instant code review comments and potential impacts of every pull request beyond just flagging issues CodeRabbit provides one click fix suggestions and lets you define custom code quality rules using AST grep patterns catching subtle issues that traditional static analysis tools might miss CodeRabbit also provides free AI code reviews directly in the IDE it's available in VS Code Cursor and Windsurf CodeRabbit has so far reviewed more than 10,000,000 PRs installed on 1,000,000 repositories and is used by over 70,000 open source projects get CodeRabbit for free for an entire year at coderabbit.ai using code Lenny that's coderabbit.ai today's episode is brought to you by DX if you're an engineering leader or on a platform team at some point your CEO will inevitably ask you for productivity metrics but measuring engineering organizations is hard and we can all agree that simple metrics like the number of PRs or commits doesn't tell the full story that's where DX comes in DX is an engineering intelligence solution designed by leading researchers including those behind the DORA and SPACE frameworks it combines quantitative data from developer tools with qualitative feedback from developers to give you a complete view of engineering productivity and the factors affecting it learn why some of the world's most iconic companies like Etsy Dropbox Twilio Vercel and Webflow rely on DX visit DX's website at getdx.com/lenny

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

Dan Shipper:Thank you for having me I've obviously been a huge fan for a long time and so it's an honor to be here

Lenny Rachitsky:It's my honor Dan I feel like this is a podcast that was meant to be I'm so happy we're finally doing this there's so damn much that I wanna talk about there's so damn much we can talk about I thought it'd be fun to start with just some hot takes and the reason I want to start here is I feel like you spend more time thinking about AI building with AI using AI evaluating AI than anyone else I know nearly and so I really respect your insights and perspectives on where things are going so let me just ask you this kind of question and see where this goes what are some things that you believe about AI using AI tools that most people don't believe

Dan Shipper:I'm gonna go with my hottest take and this is the take that I have the least evidence for so let's just start with that have other more well reasoned takes to give you but this is my hottest one which is I think that AI may be a one of the biggest force for reshoring American jobs and so I think everyone is worried about it on employing people and for sure it will change the skills needed to do the jobs that you're doing but I think it may actually reshore a lot of jobs and it'll do that in two ways one is there are lot of expensive services that rich people and big companies pay for right now so like you know in house counsel or like you know call center or whatever and what cheap intelligence does is it makes those kinds of things affordable for small companies and individuals so it stimulates demand the other thing that it does is it allows people who are in those jobs to serve more people cheaply so if you're so it may not get rid of customer service for example but it may allow you know 10 people in the Midwest who would normally be working at a call center to serve hundreds of thousands or millions of people maybe maybe that's maybe that's too much but like a lot more people than they would ordinarily if they were the ones on the on the phone all the time and so it becomes much more cost effective for American companies to hire people in the US and I think the people in the US are gonna be better in a in in a lot of cases at using these AI tools to do work and so I think it may actually make it more effective to have job those jobs in the US run by people sitting in the US who are using it to get to get work done and also the model companies are here too so there's there's a lot of American stuff happening and you can you can decide whether or not you think that's a good thing but I think it's quite it's quite lost in the conversation over whether AI will get rid of jobs

Lenny Rachitsky:I like optimistic tics about AI so this is great and like to your point I want TBD if this is good for other countries but good for the US what else what else you got what other hot takes

Dan Shipper:Another another big hot take and this is this isn't less like contrarian and more just like I think people are truly sleeping on it I think people are truly sleeping on how good cloud code is for non coders and I'll extend this to not just cloud code but Google just came out with the Gemini CLI command line interface so things like that and I'll tell you about for people who are listening that don't know what cloud code is cloud code is just the command line interface so it's you know those black terminals that programmers use it's a command line interface that you can boot up it has access to your file system it knows how to use any kind of terminal command and it knows how to like browse the web all that kind of stuff you can give it something to do and it will go off and it will run for twenty or thirty minutes and complete a task autonomously agentically especially with cloud opus four that just came out it's this gigantic leap forward in AI's ability to

Dan Shipper:Work by itself and and cloud code can even spawn multiple sub agents that do a bunch of tasks in parallel and it's incredibly useful for programmers like everybody inside of every is using it all day every day like everyone's agent pill they've got like 15 agents doing all this kind of stuff it's crazy but non programmers don't use it because it's intimidating to use the terminal but you can like download for example you can download all your meeting notes and put it in a folder and just be like okay i want you to read every single one my meeting notes and tell me something that i do for example is tell me all the time that i subtly avoided conflict and it will it writes a little to do list for itself it can have a little notebook it can go and read each little thing and then like write into its notebook go down its do list and give you a summarized answer over multiple turns so it's not just like stuffing everything into context which is what you'd be doing with like a you know chatty bitty chat or a regular quad chat it's like actually processing every single file that you give it and so i think it's incredibly powerful for any kind of task that involves processing a lot of text

Lenny Rachitsky:So as a simple way to think about this you basically have an agent on your local computer that can read your local files and do your bidding

Dan Shipper:Yes exactly and it can do that for long amounts of time without going off the rails

Lenny Rachitsky:Interesting and so there's like a small hurdle that nontechnical people have to overcome which is using their terminal and giving commands but once they get it running it's just you talk to it in english and ask it to do

Dan Shipper:Stuff exactly

Lenny Rachitsky:So the hot take here is just claude code which most people think is for engineers is the most underrated tool for nontechnical people yep exactly what are some other ways you imagine people seeing this this meeting note example is really cool and i could see people do using this what else have you seen or thinking

Dan Shipper:About something that i've done a lot so i'm a writer for a lot of my job and for example i love and i know you're going to ask me about books i love so i'm going to give you a sneak peek which is i love war and peace i just read it for the third time

Lenny Rachitsky:Wow that's a long book

Dan Shipper:It's so it's so long but it's so good i think tolstoy is a brilliant writer and one thing that i wanted to do is i was like i wanna inflect some of my writing with some of tolstoy's style and the way i did that is i think he's incredible at these little subtle sentences where he shows you what a character is thinking and feeling just by how they behave like how they move their face or like the mismatch between the intonation in their voice and the expression in their eyes like all that kind of stuff like he's just like a an incredible student of human behavior and psychology and so i just downloaded war and peace to my computer which you can do because it's public domain and then i had claude read like the first three chapters of war and peace and pull out all of those descriptions and make then make a guide for itself for like how to do descript like character descriptions like tolstoy and you could totally do this with like a regular like opus command but you couldn't put all of war and peace into it it would take a lot more hand holding to get it to do this and it just sort of did this by itself like without my like really intervening it also ended up like downloading i i had to download a russian version of war and peace and the english version and then start comparing different scenes that i love to like tell me about things that i might have missed in the translations so that you can get as deep and weird and nerdy for whatever subfield you care about as you want to same thing for like if you've got tons of customer interviews or or like tons of customer data you wanna go through it's like incredibly powerful for for going and figuring stuff out stuff out from big data sets like that

Lenny Rachitsky:You actually inspired me to use this is not what you're describing but it's also something that's very cool this is gonna sound so nerdy i'm reading anna karenina right now yes based on also tolstien this is recommended by previous podcast guests and so i was like alright i gotta read this also very long on my kindle i'm just like all right 13% in i've been reading for months

Dan Shipper:Hot take i think warm piece is better than anachronino especially for like a tech person but they're both good

Lenny Rachitsky:Okay there we go there's my year

Lenny Rachitsky:I saw you tweet this use case that i love that i've been using which is just while i'm reading having chatgpt voice sitting around and then just asking it questions because you don't actually have to feed it the book it knows the whole book and anthropic just shared this i don't know if they shared or someone found this in their legal briefings that they actually bought tons of books and scanned them themselves yeah that's how they did fair use and so it has all this context so just sitting there asking it like what the heck is this thing in russian society it's super fun okay so this is awesome so the tip here is just coming back to your hot take the tip is you basically can have an agent using local files and doing all kinds of cool stuff on your computer versus having to upload it into into projects or into your prompts and things like that yeah super cool so the i guess the bet here is that people are gonna discover this and start using this just day to day

Dan Shipper:I think they absolutely will and i also think probably the model companies are gonna start making this more accessible like i think one of the things that will just come from cloud code and other things like it into their everything else you use whether it's on the web or wherever is the original all of the original ai apps were pasting a chat box into an existing ui so you know you've got copilot it's got a little it's got like the autocomplete in the in the ide you've got cursor it's got a little sidebar with it with a little chat and the difference with cloud code is you never look at the code it's not meant for coding it's not meant for coding by hand it's meant for you to say i want you to get something done and it goes and does it and i think we're just getting to a point where for pretty much all of these you know all the usual applications ai is going to be good enough that we can get rid of the interfaces more or less where you're like digging into all the things that it's actually doing and and it's you're you're sort of interleaved with its execution and you're more just like i'm delegating it's gonna go do it

Lenny Rachitsky:Yeah I had a Cursor CEO Michael Thorel on the podcast and this is his big vision is what comes after code mhmm way we exactly should be exactly and I also just had the founder of Base44 on the podcast who sold built this company sold $80,000,000 to Wix and he shared that for the so he's been around for six months the company for the last three months he hasn't touched a single line of front end code all Base 44 or sorry all Cursor and other tools he's using so this is happening

Dan Shipper:Same thing for people inside of Every like no one is manually coding anymore

Lenny Rachitsky:Okay definitely need to talk about that before we do any other hot takes that you want to throw out there

Dan Shipper:I have one other hot take which is I have a definition for AGI and so AGI is like famously hard to define like what it what does it mean for it to be artificial artificial general intelligence the Turing test was one but like we pretty much blown past the Turing test in a lot of ways so we have no good one and so what I have noticed is that you can tell how much better AI is getting by how long a leash you can give it to do work so with Copilot it was like a you can tab complete and that was like the beginning with ChatGPT you ask it a question and it it returns a response and that's like maybe slightly better than a tab complete and then now with with Cloud Opus Four and Gemini and all that kind of stuff like it can go off and and work for also with deep research it can go off and work for like twenty or thirty minutes so that leash is getting longer where where you have to intervene and I was thinking about this and it reminded me of Winnicott who's a child psychologist he wrote this book called Playing in Reality and his conceptualization for what it means to become an adult what it means to go from being an infant to a child to an adult is when you're when you're first born you're effectively fused with usually your mother your caregiver like there's no difference between you and her or you and whoever your caregiver is and growing up is this process of being gradually like let down in certain moments where you can handle being let down so you learn that there's separation between you and your caregiver so for infants it's like instead of being like fused at the hip for like every hour of every day you get left alone maybe it's like you get left left alone to cry it out like who knows if that's like the right thing to do with infants a lot of consternation there but like that's teaching you that there's a separation between you and your mom or you and your dad like there's there's not going to always be someone to pick you up and raising a child is about knowing when they're ready to be let down a little bit and have to stand up on their own so I think there's that same leash with human development it's like you get longer and longer periods of time where you can be on your own so we're still in the kind of like twenty to thirty minutes is maybe maybe I don't know I guess you probably can't leave a toddler alone for twenty to thirty minutes but like you know it's a little bit older than a toddler

Lenny Rachitsky:Maybe twenty thirty seconds

Dan Shipper:You you can with a toddler it's like you can be in the same room but not interacting with them total like every single second for for twenty for twenty minutes sometimes so it's it's around there and I think there's a similar I think that we have that similar leash with AGI and so I think a good definition of AGI is when does it become economically profitable for people to run agents indefinitely so it just never turns off it's a Cloud Code that's always running it's always doing something you just never turn it off you don't need to because like you know that it's worthwhile to keep it to keep it on it's never waiting for you to be like okay next thing it'll always respond to you when you're like okay next thing but it's off just essentially living its life like a teenager and that is profitable for you you'd rather have it do that than just wait for you to tell it what to do next

Lenny Rachitsky:And interesting

Dan Shipper:I think that's the good definition of AGI

Lenny Rachitsky:And the profitable piece is also just the cost of running that thing and having it

Dan Shipper:It's it's partly the cost and partly the value right and obviously you can like game this a little bit and be like cool I'm just gonna like tell Claude to like run-in a loop forever but like I'm talking about more than that like more widespread more widespread adoption of agents that that work all the time and and I like the profitable thing because if it costs a little bit of money and we're we're the bar is profitability then there's like a it has to actually be doing something useful for you to keep it on

Lenny Rachitsky:It's interesting how that also is very the metaphor of of a senior employee and autonomy and essentially the more autonomous they are the less instruction you have to give the less reviews you have to do is also just directly correlated with how senior they are totally okay great anything else along these lines

Dan Shipper:I mean have plenty of them I think I'm generally like I hate the headlines that are like it's gonna replace jobs or like it's gonna unemploy like two thirds of the workforce like I don't think that's true I hate headlines that are like you don't use your brain when you use Chachi B T or like there another another good headline is like doctors alone doctors plus AI or just AI like which one is better AI is better therefore like doctors are gonna be outmoded like all that stuff is I think pretty dumb so for the doctors plus AI example I think it's important to recognize that using AI is a skill and so if you study doctors in a vacuum that don't really have a lot of experience with AI yeah you could probably create a situation such that it's better to just use an AI and sometimes it is going to be better but there's a lot there's so many contexts that doctors need to make decisions and do things that it's really hard to take one study and make any sort of conclusion about that and it's especially hard when you're dealing with a technology that's developing so rapidly that doctors can't really be expected to be experts at it yet but I would guess in five or ten years that will be totally and completely different for the student example or like the you know AI turns your brain off example I think it's really important to understand that in the history of technology it has always been the case that you give up certain skills in order to get other ones so for example Plato was famously very skeptical of writing because he thought it would harm your memory and it did we don't remember things quite as well as they did back in the day because they had to remember long epic poems to entertain each other but I think writing is a worthwhile trade for having a slightly worse memory and I think something similar is going on with AI where yeah you may be slightly less engaged in certain tasks but if you use it right you're going to be way more engaged in other tasks where you have much more power and so you can construct a study that says brain connectivity goes down when you use AI in the same way that you could construct a study that says people's memory is were are worse when they have writing skills but I don't think anyone would want to go back to a world where no one was literate

Lenny Rachitsky:Interesting I imagine you can build a GPT from that and then instead of having a meeting with Dan now just talk to this thing and he'll make decisions definitely.

Dan Shipper:And I I I mean we do this a little bit it's not the same as it's not the same as having being able to predict exactly what I'm gonna say in a meeting but I think if you're a CEO or founder or manager it's really stunning how much of your job is just repeating yourself and that is one of the best things about this AI particularly AI revolution is that you don't have to repeat yourself and so we had it like last quarter I tend to set like one or two quarterly goals and like one of my big goals for us last quarter was don't repeat yourself so I don't want to ever say the same thing in a meeting twice if I can help it so for us at Every like one of the big parts of Every is we have a daily newsletter and I'm spending a lot of time like giving feedback on headlines or giving feedback on how do you write an intro or like how is this what is this idea any good like that kind of stuff and we've started to codify all that into prompts that basically it's not the same as mimicking me it can't exactly say exactly what I'm gonna say in a meeting but it pushes my taste out to the edge so that writers who are not able to talk to me like by the time I see it they've already talked to like some simulation of a simulation of me and that's incredibly powerful.

Lenny Rachitsky:Let's follow this thread this is exactly where I wanted to go I feel like the business you're building the team you're building the way you're operating is the very bleeding edge of how companies will operate and are trying to operate in this AI era you guys are trying to be super AI first it's super aligned with just so much of how you of your writing there's just like so much reason to study what you guys are doing thank you and this is benefiting all of us so thank you so first of just tell people what the heck Every is and then share a few insights into just how you operate it's funny that you laugh.

Dan Shipper:Everyone asks that because it's just it's like a it's a very it's just it's a very weird shape of a that you can actually see other companies that have this shape from earlier eras but they're it's a little bit it's less common it doesn't make as much sense and I think it's newly enabled by AI and we can talk about why but the way that I typically talk about Avery is we do ideas and apps at the edge of AI so the core of the business is we have a daily newsletter we've been doing it for about five years we have about a 100,000 subscribers all the people from the top AI labs read us anyone who's who's basically interested in or working in AI at the frontier and wants to know what's going on reads us we do a lot of like for example whenever whenever OpenAI or or Anthropic drop a new model like we get our hands on it early and then we get to play with it and write about it which is it's like my ideal job I love it it's the best don't if a curse on this podcast but it's.

Lenny Rachitsky:The fucking mess perfect excellent use and you call those vibe checks is that the.

Dan Shipper:Yeah we call them vibe checks which I think is really important because and this gets to the next part the the apps part of of what we do I think it's really important to do vibe checks and and to call them vibe checks because they're about how does it feel to use this thing and how does it feel to use it for work for things that you would normally use it for like in your job or in your life because I think that captures something that standard benchmarks just don't capture and really can't and the best people to tell you to write a vibe check are people that are actually at the edge using it for stuff and so what we found over time is we have we we love we think the best writing and content about technology is from people that are actually using it and building with it and so we've always had this sort of function where we're always building little experiments in addition to our writing and that that helps us write great stuff and that has turned into a suite of apps that we run internally and the people who are people who are building those apps are also writers and they're contributing to things like vibe checks so you get a really inside look into how is this stuff being built for people who are actually using it every day and the suite of apps that we have one's called Quora we just launched Quora publicly on the day that we're recording this which is really awesome congratulations thank you you can think of it like a chief of staff an AI chief of staff for your email it helps manage your email with AI it's very cool we can go into more of it later we have another one called Sparkle which is an AI file cleaner we have another one called Spiral that does content automation with AI we originally incubated Lex which is an AI document writer which we spun out into its own company and my Every co founder Nathan runs that and basically we bundle everything together so you pay one price you get access to all of the software that we make and we're constantly putting new stuff in the bundle and I can tell you more about like what kinds of things we like to incubate and how do we like to incubate it because I think there's there's a lot of there's some really interesting special things in there but I've been blabbing for a while so I'll stop there.

Lenny Rachitsky:There's also consulting firm which I wanna talk about but let's keep we off.

Dan Shipper:Have consulting we also do that and that is another that's like the third leg of the stool in the business it doesn't fit quite as nicely into my ideas in app streaming but we spend a lot of time with big companies where we teach them how to basically how to be AI first we train all the people on how to use AI and it's it's very cool it's it's really it's really fun and and very a very important part of what we do.

Lenny Rachitsky:That feels like a billion dollar business right there I wanna come back to it I think so because everybody wants to learn this okay so share a few ways that you guys operate you mentioned that your team doesn't write any code what are just some ways that allow you to operate this efficiently I know your team's really small you have a daily newsletter you three four products you have a consulting arm how big is the team of everybody.

Dan Shipper:We have 15 people.

Dan Shipper:Okay so a couple things one and I think everyone should do this is we have an AI a head of AI operations I sit with her once a week and every time I'm doing something repetitively I'm like we put it in a to do list and she's just constantly like building prompts and building workflows and stuff like that so that I and everyone else on the team are just automating as much as possible and I think that has been a big unlock because it's really hard to if you're working in a job all day you're fighting fires and you're like am I going to do this in the way that I know how or am I going to do it in the new way that might not work I'm going to spend a bunch of time in Zapier building some no code automation I don't want to do that having an AI operations lead lets you basically identify those things and have them solved without people who are doing the work actually getting in getting like having to take time to do it which I think makes it much more likely it happens there's always a trick with that where it's like you have to make sure it gets used so it's basically you're developing little applications internally but if you're good at making applications people use it's great highly recommend having an AI AI operations lead.

Lenny Rachitsky:15 people okay yeah so just give us insight into some of the ways you operate that are kind of at the bleeding edge.

Lenny Rachitsky:I imagine you saw the CEO of Quora tweeted about this wanting to hire exactly this sort of person yeah so clearly this is a trend so the idea is this per your point that this needs to be somebody who's who's outside of the day to day work of the company and is specifically focused on helping the team be more efficient with AI yeah yeah and then is this person mostly just you automating you or can they help other people no

Dan Shipper:She helps she helps everyone basically

Lenny Rachitsky:Everyone okay

Dan Shipper:Where we're starting right now is with the editorial operation so there's so much stuff in the editorial operation where I or our our our editor in chief Kate like Kate is constantly doing like little small copy edits to make sure everything is like in every style it takes like hours hours a day and so now opus is at a point where you can give it a style guide and a prompt and it'll go through go through anything you're writing and copy edit it which is amazing the trick is it's not just building that you also have to get Kate to be like did you put this through the prompt yet anytime someone gives her something so there's a little bit of like behavioral update too that has to happen which I think is a really interesting organizational challenge and I think for us it's a little easier because everybody inside the org is very AI first and just wants to go do it we don't have anyone really who's like I don't know I don't really wanna do this and that's a whole different challenge which I think a lot of organizations face but there's always a problem of getting people to use it

Lenny Rachitsky:That is super cool what is her background this AI operations person

Dan Shipper:She her name is Katie Parrott she does a lot she actually does a lot of ghost writing for us so she also when when people inside of every who are builders often they just write themselves but sometimes they want help and she'll help them write about whatever they're working on so that's how she started with us she still does that but she also spends a lot of time doing the AI operations stuff and then before that she was she worked at Animals which is a content marketing agency like one of the top content marketing agencies and they're very process oriented and I think the reason Katie is so good is because she's incredibly good at that kind of process stuff or like thinking about that but she's also a great writer and she's also just incredibly excited about AI she just wants to tinker and wants to ease it that was the thing that got me to be like okay you should just come and do that instead of just ghost writing we should add this to your plate and it's it's been really fantastic so I think that's a at minimum you really just want someone who's just like I wanna tinker I wanna build stuff there's also people who have a little bit more of that process orientation I think that is important and to the extent they understand the craft of the thing that they're trying to build for that also helps a lot

Lenny Rachitsky:This is an amazing tip I feel like everyone's gonna start hiring these

Dan Shipper:I I think so there's there's a couple other people who talk about this I heard Rachel Woods who's another sort of she thinks a lot about AI stuff she she's talking about I think it's becoming like it's becoming a thing and and I think it's I think it's really important and and it just like bleeds out into every other part of the org so like we're doing this inside of the editorial org but there's a lot of copy that goes out on Quora and by the way Quora is spelled C O R A so it's different from Q U O R A slightly confusing there's a lot of copy that goes on a Quora or Spiral or Sparkle that we want to have that same every quality bar for and so we have you know engineers sending Kate like here's the Figma file can you go and like do copy edits and that sucks for everybody and Kate is one person and it's just really hard to do that so one thing that we did Nitesh who's one of the programmers engineers on Quora built a Cloud Code command that just uses that prompt and checks through the entire code base for all the copy edits and then creates a pull request on GitHub and then sends the pull request to Kate so she's just like looking at the pull request and being like does this make sense and so you can translate that prompt into for example a format that engineers can use and suddenly your engineering team is writing marketing copy in the style you want I think that's so cool

Lenny Rachitsky:That is extremely cool I wanna take I'm gonna take us on a little tangent you keep mentioning Claude and I'm I'm curious just what is kind of in the stack of tools that you find yourself using your team ends up using this seems like Claude is a core part of it

Dan Shipper:I do love Claude I would say I'm generally my first thing that I open is O three I'm like a Chachu booty boy and I think O three is super high quality I think it's great for writing it's great for coding it's great for all that stuff and what it has that really makes a difference still from from Claude is it has memory and I just love that like I've spent so much time yelling at Chattypie T about like I need my writing to be punchy and concise you know and it just knows that now so I think when I ask it to write something for me it's like actually better than yours or maybe not yours but like you your average your average Chattypit user and I also find like I use it a lot for self reflection and personal growth type stuff so it knows me so when I send it a meeting transcript and I'm like how did I do it's like well you did that thing that you normally do but you're way better on this other thing I like that I think that's really great so day to day O three that's my that's my go to I think Claude Opus is first of all Claude Code everyone inside every that's basically what we use if you're building something you're using Claude Code it's crazy it's so good Gemini just came out with something so I'm very excited to try that because I think that that's the model that we use most for the apps that we build like inside the apps it's incredibly powerful and it's incredibly cheap which is great so I wanna try the CLI tool they came out with we also use Codecs a bit which is OpenAI's coding tool that's for like I wanna one off self contained like I wanna pick off this little feature what else do I use going back to Claude Claude Opus four can do something that no other model except one other model that I can't talk about oh boy can do something that no other model can do

Lenny Rachitsky:We won't go there we don't wanna get you in trouble okay go on but

Dan Shipper:Yeah no other model can do this which is earlier versions of Claude and I think generally versions of other models when you ask them is this piece of writing any good Claude example would always give it a B plus and then if you chain if if you did another turn of the same conversation you're like I updated this it would always go to a minus and then if you give it another turn it would go to like a you know so it like doesn't have the same kind of gut it's like it's sort of thinking about what you probably wanna hear too much and there's various methods that you can use to like prompt prompt engineer around this like give it a template or like whatever and they sorta worked but it just still doesn't doesn't have that thing where it's like can it tell if writing is interesting or any good does it have that gut sense and Opus four has it it's really wild and I think that's I think that's super important because it opens up all these use cases where you might wanna use a language model as a judge so for us for example we're working on a new version of our product Spiral which does content automations you've used that in the past and we're doing a essentially Claude Code but for content style product where you know you say I want I wanted to write a tweet you give it all the documents it has a bunch of memories it creates a to do list for itself and then it goes and writes and one of the things that is so interesting is now because it can it can judge things part of its to do list is okay wrote three tweets I'm gonna like judge whether I think these are any good and then it can improve before it comes back to you and that's just like a huge huge unlock that we were struggling for like three months to like build this like crazy system to like try to get it to judge writing and then Opus four just like one shot at it and we're like great this product works let's like let's start shipping it so yeah I love it for that

Lenny Rachitsky:Are there any other AI tools that you just use regularly you mentioned Granola even outside of the bottles so what are were some that you think maybe people are sleeping on

Dan Shipper:I use Granola so I used to use Super Whisper and Whisper Flow which I think are fantastic we have an internal version of that called Monologue that will be shipping in like a month or so that I I use now but you can think of it as roughly equivalent and I think like generally speech to text interfaces are the future and more people should be using them and more people should be building them as affordances I use I use we use Notion all the time and I specifically use their meeting recording I think that's most I think that's mostly the stack

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Lenny Rachitsky:Let's go back to ways that your team operates you mentioned having Kate was that her name yep okay what else what else do you do that you think other companies should be doing or will eventually start doing

Dan Shipper:So the Quora team which is Kieran and Nitesh basically the team

Lenny Rachitsky:Two people

Dan Shipper:That's the team

Lenny Rachitsky:Yeah well

Dan Shipper:It's Quora it's it's Kieran Nitesh and fifteen Claude code instances so it's you know it's more powerful than you think

Lenny Rachitsky:This is I love that this is just again a glimpse into the future

Dan Shipper:One of the things that we do that I think is really cool and they basically invented this like I had nothing to do with this is they invented the idea of compounding engineering so basically for every unit of work you should make the next unit of work easier to do so an example is

Dan Shipper:In a Claude code world where you're not coding a lot you end up spending lot of time essentially typing PRDs like here's a document with exactly the stuff that I need to I need to do right and so you could just be like okay cool that's my job now I'm going to just like write PRDs and so each successive PRD it's the same amount of work or you could spend a little bit of time being like there's a sort of platonic ideal of a PRD and what I'm gonna do is write a prompt that can take my rambling thoughts and then turn that into a PRD and so you spend a little bit of work to make all of the next like PRDs that you're doing easier to easier to write because you're writing less of them and so finding those little speed ups where every time you're building something you're doing you're making it easier to do that that same thing next time I think you a lot more leverage in your engineering team and so like yeah we have Kiran and Nitesh and Quora has it just came out of it just became public it was in private beta it has 2,500 active users there's millions of emails going through it and that's one of the products that we do as a 15 person company it's kind of crazy

Lenny Rachitsky:It is crazy how do you do this speed up thing is it prompts that they continue to refine

Dan Shipper:A lot of it is prompts and automations and stuff like that yeah

Lenny Rachitsky:Got it for automations what's the tool what's the tool you use for automating automations

Dan Shipper:What they're using a lot of is is Cloud Code so you can do slash commands in Cloud Code which are like repeated prompts that you're that you're doing

Lenny Rachitsky:Got it okay so basically they're building a library of prompts that make the process of here's what I wanna build to a good solid PRD that you can feed into Cloud Code.

Dan Shipper:Yep.

Lenny Rachitsky:More correct and more efficient exactly super interesting and and they just keep like a file or they put this into a project is that how they

Dan Shipper:Store this it's a GitHub it's like a GitHub it's like in their GitHub where they can they can like share it with each other another thing that they do which I think is very cool is they they use a bunch of clouds at once but then they're also using like three other agents so they love there's there's an agent called Friday that they love.

Lenny Rachitsky:That's like a that's a that's an AI agent product called Friday yeah yeah I haven't heard of that okay.

Dan Shipper:Interesting there's another one called Charlie that they really love and in particular I think the thing they like about Charlie we have a whole video about this which I can send you.

Lenny Rachitsky:Yeah I'll point to it.

Dan Shipper:They did like a you know S tier through F tier of AI agents which I think is so funny and one of the things I really like about about Charlie is that it lives in GitHub you can when you get a when you get a pull request you can just be like Charlie like you can you check this out and that seems to seems to work really well to have like different agents that have like maybe slightly different perspectives it's like different people you know that have different perspectives and have different taste like you can I Kieran is he's like a one of those like like serious Rails files who are just they just love Rails they love the way that Rails feels and so I think he has a real sensitivity to okay this agent you know for example it's very it feels very terse and minimal and and professional and so and and it has a particular kind of style that maybe he likes versus I don't know Claude is a slightly different style and I think that's I think all of that is so interesting that they that these things have personalities and that those that that changes what you might wanna use it for or why you might wanna use three of them at once.

Lenny Rachitsky:That is so fascinating it makes me think about Peter Ding's conversation again where he talks about his hiring strategy and one of his key lessons and he ended up hiring the current head of product for ChatGPT the current head of marketing at ChatGPT current head of engineering because he hires these incredible people and his philosophy is to hire a team of Avengers where everyone is strong at certain things and together they are the perfect team versus everyone versus like the best at everything and it's interesting that you can almost do that with different product different agents from different companies you definitely can and it makes me feel like there's a bigger market than people think potentially where people will want different companies' agents not just all devons or not all codecs.

Dan Shipper:I think there really is it's definitely not like one one agent rule them all.

Lenny Rachitsky:So interesting yeah oh my god the two people on the Quora team are what's their background are they both engineers or what are they?

Dan Shipper:They're both engineers okay Kieran's got this crazy background where they both have really interesting backgrounds Kieran's got this crazy background where he was previously VP Eng at a startup so was effectively the CTO of startup or maybe two startups was one of the founders and then before that he was a composer a professional composer and before that was a baker so we did a team retreat in France last year and he taught us all how to make croissants my croissant was horrible his was beautiful.

Lenny Rachitsky:Seems that was.

Dan Shipper:Very good generally I think that kind of multidimensional type of talent is the kind of person that I love having at Every because we're all generalists we all wanna use AI for all these weird awesome creative things and someone who has that background is going to have a good taste for not only agents but what should the landing page look like or whatever which I think is increasingly important where you're trying to scale a team of generalists of 15 people to five products so that's Kieran's background Nitesh's background is I'm jealous because he only started learning to code when ChatGPT came out he'd wanted to learn to code forever and he's only known how to code in an AI era and I keep telling him dude like I I learned to program in middle school from books like had to go to Barnes and Noble and buy a book and there was nothing I couldn't Google anything about like how this how this why this function wasn't working.

Lenny Rachitsky:Stack Overflow even back then.

Dan Shipper:Yeah yeah there wasn't Stack Overflow there was like weird bb net forums and stuff that like I was like 12 and I probably shouldn't have been on there or whatever so it's he has gone so much faster than any other engineer I think like a pre AI era and I see the same thing in the rest of the company like I think there's this huge question about what happens when kids like entry level jobs are taken away by AI and my take is like that that's worth thinking about and it's it's possible that that might be a problem at some point but my take is whenever I see a kid with LGBt I'm like holy shit they're gonna go so so much faster than any other person that I've worked with like we have this guy Alex Duffy who works with us he writes for Context Window and he he just launched we taught AIs how to how to play diplomacy with each other which is really cool and he did that whole thing and he's I think he's really really really talented and when he came to us I guess almost a year ago now it was one of those classic cases which I've seen like over and over at every which is you have great ideas but you're not a good writer yet and it's really hard for me to do anything with you until you're good enough at it so I have to give you like small little things until you get better and blah blah blah whatever and what I noticed with him is he was just making a year like he made like a year's worth of progress in like two months because every time I sat down with him and told him okay here's how you tell a story here's how you think about a headline like he recorded all of it put it into a prompt and like he never made the same mistake twice and I think he's so much accelerated from where he would have been because of this stuff and I see that in lots of other parts of the org so Nitesh is another good example and so I think generally people are going to figure out that some 20 year old with Chatuchu tea subscription is like super powerful if you just like mentor them and I think that's great.

Lenny Rachitsky:Man there's so many threads I could follow here like there's all this fear of entry level people will never like the roles are disappearing for entry level people and so how will we ever have senior people if these people can't learn to do things as an entry level person and what you're saying is ChatGPT and these tools help you accelerate really quickly so you don't really need to be at the bottom rung for a long time.

Dan Shipper:Yeah you're effectively like learning how to be one level above mhmm the entry level from the beginning and you have to and this is sort of my my whole allocation economy thesis where when you look at what skills are gonna be valuable in the AI era one big group of skills are the skills of managers today they're human managers tomorrow everyone's a model manager right now AI is not like right now management skills are not broadly distributed because it's very expensive another expensive thing that so 8% of the workforce is managers it's now going be much cheaper to manage so more people are going to have to do it and so that's the thing that kids 20 year olds whatever I see is now are going to start to have to learn in addition to you know there it's not like you can just say like okay go do it and then come back like you have to be able to go into the work that's being done and help make it better but they're learning both at the same time they're learning how to manage and how to do the actual work so that they're good at it.

Lenny Rachitsky:And the managing here is managing agents right?

Dan Shipper:Yeah you're managing AI.

Lenny Rachitsky:Yeah and so this is a good coming back to your point about how this core team and I guess you said everyone doesn't write code zero code written now it's just managing agents that are writing code for you yeah okay I've never heard of a company at this stage so this is extremely cool so the workflow is they give it here's what I want I refine it using this cool prompts library that they build on and agents build code write the code then basically the time is spent reviewing code and then reviewing the output what does it look like what does it feel like and then continuing to refine yeah wow so you guys are at where Michael from Cursor said we will be so which I chatted with him a few months ago he said in a year this is where he thinks things will be we're we're not looking at code anymore you guys are already there although you're looking at code okay you're still looking I at think.

Dan Shipper:They're they definitely are looking at code yeah so you know you're doing a code review before you.

Lenny Rachitsky:I'm not ready anything.

Dan Shipper:And I do think like Danny runs Spiral which is the Cloud Code for content tool I was talking about that we're building you know he spent a couple of days like digging into the internals of some third party library that we were interested in just because it's like it's helpful to know it's helpful to like understand those things but then he's not actually like writing any code once you understand it he's just like off telling Cloud Code what to do and I think that's I think that's that's really that's really important. But I do want to say something else is we're not at a point yet where the people that work at Every could do what they do if they didn't know how to code.

Lenny Rachitsky:Yeah this is what I was gonna ask.

Dan Shipper:Which is a a different bar and I think for a long time it's going to be valuable to know how to code for a long time but this has been this is this is like a a progression that is not a new progression so for example when I was in middle school learning to code the the new hot thing was scripting languages which is like Python and JavaScript and if you were but if you were a real programmer you would understand the language underlying Python and JavaScript which was which is what's written in C and scripting language was like weren't like weren't totally real and in order to like really do anything interesting you had to be be able to learn both parts of the stack same thing for C programmers when I guess in the seventies C was invented it was like you gotta learn you gotta be able to write assembly and English is just like a layer on top of scripting languages so I think all of those all of those things were right in the sense that there's especially during transitions there's a lot of reasons why it's important to be able to go down a layer in the stack and it gets less and less frequent over time but that still takes a long time and there's some times when even if you're a JavaScript or a Python programmer it's useful to know like how how all that how that stuff works how it's written and see how it's how it's implemented it's today it's much less important than it used to be but that took like ten or twenty years and I think that's the same thing is gonna be true for programming like having that skill is super important and will accelerate you significantly it will sort of start to get less important over time but we're not close to that yet

Lenny Rachitsky:Okay that's a really important point I'm glad you went there so do you have a sense of how far we might be from you hiring someone to build another product that isn't an engineer

Dan Shipper:Like a real SaaS product

Lenny Rachitsky:Because it yeah so like hey we have this idea we wanna bring someone on to actually lead it

Dan Shipper:Very far like not even not within sight but there's a lot of things that could be products that are a layer a level down from that that I think that you could do almost now so like an example we were talking about Dia the browser from the the new AI browser from the browser company Dia has these things called skills which are effectively like little AI apps that you can run-in the browser you can prompt them and they run on the web page and do work for you a non technical person could build that same thing for custom GBTs from ChatGPT dontech owned person can definitely build that so I think while I will I will definitely maintain that we're not anywhere close to anybody being able to like build a conventional SaaS app with zero programming knowledge aside from just like a demo there are going to be other forms of software one of my things is like software is becoming content there's gonna be other forms of software that don't look like the software of today but you can run start and run as a business as a nontechnical person even if you don't know how to code and that'll happen very soon if I mean it's already kind of happening it's just it doesn't look like the thing that you're asking about it's like it's sort of like the difference between a Hollywood movie and like a YouTube video

Lenny Rachitsky:Okay I think that's really reassuring to a lot of people basically what you're seeing is AI just supercharges people who have a skill and allows them to do a lot more

Dan Shipper:Yeah. I mean I would love to talk about our like how we think about building products mhmm like what products to build like what do we end up building because I think that there's something sort of special about it that probably there's a playbook that is useful for people so when I think about this is this is only sort of snapped into focus recently so a lot of this was just like doing it intuitively without really a thought for it but when I think about the kind of things that we have ended up incubating it's basically it goes back to something I said at the beginning which is there are these things that were historically really expensive that only rich people or big companies could buy so a chief of staff for your a chief of staff for your email I think a therapist or like a lawyer is another interesting example someone to like organize your closet or organize your organize your computer is another example someone to ghostwrite for you that are becoming orders of magnitude cheaper so that everyone can use them even if you're at a small startup and so basically when you're running like we are sort of this AI first company you're running into these all these little things where you're like I wish I had a ghost writer right now but ghost writers are really expensive or I wish I had a lawyer but it wouldn't cost me like $25,000 lawyers are really expensive and and there's a lot more demand for those services than can be fulfilled because they're so expensive and what AI does is it allows you to be like oh I could just use cloud for that I can use chechiuti for that and so you're you're able to you're able to use the the demand that you have that like we can we can afford a lawyer we have ghostwriters but like there's a lot more that we can't do because we can't afford it so we still have our lawyer and we still have our ghostwriters but we just do a lot more of that stuff so we noticed that we start to then use chachi bouti and Claude first these general purpose tools to try it and see is this useful does this actually work all that kind of stuff and then if it does we will unbundle it into its own separate thing that becomes an app and and I think what's really special about this time is the entire game board has been like totally reset in terms of things you can build where you know five years ago it was like you're gonna build another notes app like we've been building notes app for forever like another B to B SaaS app like it's all the same stuff in like slightly different packaging and now it's like totally new territory no one knows what's going on no like everyone's inventing it as as as it happens right all these new workflows are being created in a very similar way to I don't know for example when spreadsheets were first a thing on computers like we were figuring out all these new workflows on spreadsheets they got unbundled into B2B SaaS same thing for chaiwpt and cloud and what's really cool is you can be like cool I'm using I'm using charger GT for this it's really useful for me and you might be like one of the first people to like really notice that and then because everybody that works at every is AI first and came to us because they reads every they read every so they all have the we all have the same vibe and we're all kind of doing similar stuff they become our first our first users so we measure the success of the product by like is it a banger inside of every monologue the app that I was talking to you about like everyone just started using it we're like okay we've got something here and what's really interesting then is if everyone inside of every uses it and people read every they have a similar vibe to us too so they become the next set of users and that's a really I think pipeline for building applications or building apps it's a totally new greenfield so that all the stuff you're thinking about it's probably new which is really cool and over time what I think is organizations like ours people who are playing at the edge we're doing things that in like three years everybody else is gonna be doing so it may be kind of niche for now but it will be a big deal in three years when everyone else has the same needs that we do

Lenny Rachitsky:That is really cool what I'm hearing is GPT rappers are a good idea and are worth building

Dan Shipper:I I a 100% think G G GPT rappers are amazing and they've been much maligned for absolutely no reason and people don't understand how absolutely valuable they are

Lenny Rachitsky:I think there's also just you guys are you raised the sip seed round I wanna so this is a good time to maybe talk about that just like these products don't have to become some mega billion dollar hit yeah you kind of have this portfolio of companies you have the content business so I think there's a really interesting approach to how big these need to get to be successful maybe just talk about that

Dan Shipper:Yeah I I really want every to be an institution that teaches people how to live a better more human life with technology particularly with AI and both like teaches them how to do it with writing and the content we make and then builds tools for them to do that and but I think fundamental to building an institution is at least for me way I would like to do it is I want internally it to feel like this creative playground where we have the opportunity to take risk and do stuff and do weird stuff that like just doesn't make any sense we can't justify anyone but we just feel like it would be fun and so I think I'm always playing with that dynamic tension between institutions serious who want this to be like lasting and important and it should just be fun let's play around and I think having that tension is really valuable and so I've always been hesitant to raise a lot of money because I think it locks you into having to be that serious thing that's like totally going for it and there's lots of companies that figure out that balance but just for me like personally as a founder I'm like I wanna keep the optionality alive and I wanna keep the kind of playful feeling alive and I think part of that comes from I know like I have the control to do what I want more or less there's probably also some like deeper psychological things going on there which I'm happy to talk about if you want to get into it but you know I think there's also just that that's that's kind of what I want and so when we started every we raised like a very small 700 K pre seed round and this is at the the height of the creator economy so we both we both started our newsletters you and I started our newsletters around the same time it was like the hypeiest craziest thing people were throwing money around it was like wild so but we raised 700 K because it was like I wanna raise enough for us to be able to experiment have a little cash cushion but not so much that it locks us into anything and we like sent an email to all of our investors being like and you're one of our investors so you've probably got this email

Lenny Rachitsky:Tiniest tiny investor but I'm in there I'm in there we

Dan Shipper:Sent an email to everyone being like this is probably not a venture business so you should not expect us to raise again and we even raised on this slightly modified safe that gave everyone the option to convert to equity in three years even if we didn't raise more money so we did it in a way that allowed us the option to get really big and do the traditional thing and also the option to do the do it the way we wanna do it maybe it's not a huge business but we love it that's great and we did the same thing for this recent round where we raised up to 2,000,000 from reed hoffman and starting line vc and we did it as what i've been calling a sip seed round which is basically they've committed $2,000,000 but we can pull it down whenever we want and it's we just do it on a safe out of set cap and for me that was that's really helpful because it allows me psychologically to take a lot more risk like i don't if we go to zero on the bank account i can get more money great i don't have to think about it but what's also really helpful is i'm not and the rest of the team is not staring at a gigantic number in the bank account being like cool like we can burn this let's burn it and also for our investors like i i think reed very much wants us to succeed but like i don't think he he cares like what what size of business this is like i think he's more philosophically aligned with the thing that we're trying to do and if it becomes a huge business he's psyched for it and i think that kind of alignment is what i was looking for because i think there's this core creative spirit to the thing that i wanna maintain and i really care about having a big impact but i think there's a lot of ways to have an impact and one of them is building a $10,000,000,000 business i think another way is like really changing how people see the world see themselves in the world and i think that's what stories do and you you don't necessarily sometimes you do that by building a gigantic company but you don't necessarily always have to do that like a lot of the stories that we care about most are from people who maybe they weren't rich at all and so i really like creating this place where we can make a really good business i care a lot about that but also the the core the soul of it is changing about changing how people see themselves in the world

Lenny Rachitsky:I love that you've kind of innovated a new like a middle ground way of fundraising not bootstrap and not just regular vc it's a six seed and i love that this 2 mil like you know if i raise 50,000,000 it'd be like okay i get it let's not put 50,000,000 in our bank account but you do have 2,000,000 it's too much for us we can't yeah we don't wanna see that in our account

Dan Shipper:That's another thing and you know we'll see how this ages like i might be back here in two years crying the blues because like we didn't raise enough money or whatever who knows but that's the other thing is i do think we can get so much further with with very small amounts of money like quora i think all in to build quora we've spent maybe 300 k maybe that's crazy because this product includes salaries yeah this product was not even technically possible even if you had billions of dollars like three years ago not possible because you can't do email summarizing and automatic responses and all that kind of stuff without gbt so not only was it totally impossible but now we can get with two engineers like we can get you know the the amount done that would would have taken a team of like 20 people and i think that's you know that means that we need less money and i don't think that vc has really caught up to that yet and i think there are other companies that are doing there's a term called seed strapping so there are other companies that are of starting to wake up to this too and i'm curious about how it changes the vc model for sure for us we have a specific incubation model which is a bit different from a vc model and i think there's some differentiation in in the stuff that that we can do with founders which is kinda cool but we're we're i'm just trying to figure out like a shape that works for me and that's different from other people and we'll see how this goes

Lenny Rachitsky:We'll revisit in a couple years

Dan Shipper:Yeah

Lenny Rachitsky:Seems like it's going great from the outside i wanna ask about a couple other things before we wrap up one is around this consulting arm that you have i think it's really interesting because like i said i feel like this could be a billion dollar business i feel like every company right now is trying to figure out what the hell has everyone else figured out that we're not doing i've had so many emails from chief product officers at companies being like can you introduce me to some chief product officers that have done cool things with ai that we should learn from like so many people and i just introduced them to each other and it's cool because you guys are basically solving that problem for a lot of companies so one is just maybe share a bit about that side of the business for folks and then two i feel like you i imagine you've seen companies that have done this really well have adopted ai things that worked really well they found really good productivity gains and then you found companies that don't what do you find is the difference between those two

Dan Shipper:I love this question and i have a very specific opinion about this so one yeah the consulting arm basically like we spend all of our time playing around with new models writing about them and building stuff with them and we have a big audience so naturally like we've gotten companies over time being like can you just come and teach us how to do this and so we started to do that this is you know pretty nascent it's probably been over the last like six to nine months but like it's a pretty big business now like it's our it's it'll probably double this year like last year we did about a million maybe it'll be maybe it'll be more this year we'll see it depends on a couple we have a couple big contracts out so it might be way more than that

Lenny Rachitsky:A billion predict a billion dollars

Dan Shipper:In a few years but yeah basically people are like you come help us learn how to do this so what we do is spend some time going and researching your organization so we go in and try to understand like what is what are all the different teams doing what are the repetitive tasks some of the stuff like some of the stuff we were talking about earlier and then what we will do is first we present a little report it tells you like here's everything that we found here's not only that but you have a chatbot where you can chat with all the interviews that we did and you can pull out your own insights we have a whole dashboard where it shows you like here's here are the teams that are really into this here are the teams that are not here's how much much leverage you might be able to get on different teams based on the interviews and based on the ai analysis it's pretty cool and this is like that's an app that i vibe coded over a weekend with devin a year ago and then alex runs the printing consulting has helped upgrade it then what we do is we have a training curriculum so we go in and train each team and we customize it based on the interviews that we do because one of the interesting things about ai is it's such a general purpose technology and i think people who work inside companies 10% of them are like i'm super curious about this 10% are like i will never touch this and 80% are like if you tell me how to do it for my job i'll do it and so we customize the training to be like here are the exact prompts you're gonna use and here are the exact situations you're gonna use them and that really i think helps drive the adoption we spend four weeks with each team an hour a week that kind of thing it seems to be really cool and then we'll often also after this go and build automations and do some of the ai operation stuff we were talking about earlier companies really like it i think the and we work with a lot of big hedge funds and pe firms and big companies all that kind of stuff to your other to your your second question which is like what separates the good companies from the bad or the companies that end up adopt adopting this i think the the number one predictor is does the ceo use chachibi tea or insert your own chatbot if the ceo is in it all the time being like this is the coolest thing everybody else is gonna start doing it if the ceo is like i don't know this is for someone else like no one else is gonna be able to lead that charge and they're either going to have either they're gonna be negative on it and so definitely no one's gonna do it or they're going to have way unrealistic expectations because they have no intuition for what's possible and they're just gonna get really disappointed but the ceos that are using it all the time are able to like both drive the excitement and set reasonable expectations for what can be achieved and so those things end up working really well and the people that do this really well so for example we we work with a hedge fund called walleye which i had the founder on my podcast ai and i a few weeks ago a gigantic $10,000,000,000 hedge fund like one of the things that they do which i think is i think they're basically the model for like how to do this first thing he did which a lot of ceos are doing is send the we're an ai first company email everyone's got the memo you just gotta really do it and one of the things he said in his memo which i love is i wrote this email with chatgpt and you should too so like you gotta like

Lenny Rachitsky:In the memo

Dan Shipper:Yeah you gotta like lead from the front in that way and then what he does and i think what a lot of other like really cool companies do is they're doing like weekly meetings where people share prompts and share use cases they're doing they do like a weekly email to their entire company being okay here's our here's our usage here are our usage stats for treacho bt here are the here are the people that like here are the people that came up with a new prompt and contributed to it like create this this sort of like awareness and momentum because what's going back to the point i made earlier about you know 10% of people are early adopters those are the people inside of a company that you need to find and highlight because they're gonna just go spend all this time like figuring out what works and then all you have to do is like translate what they learn into the rest of the organization and so if you create forums for them to be rewarded you're going to automatically transfer a lot of their learnings to everybody else and encourage more of it and i think that's kind of the secret

Lenny Rachitsky:That is awesome i love this advice so just to reflect back what you just shared a few kind of tactics you find that you encourage within companies one is just send this memo the toby memo i don't know if that's the right way to describe it who i think was first along these lines just we're ai first it's going be part of your performance review it's going to be asking can you do it in ai before you could talk to anyone else all these things and then just note i wrote this using chatgpt it's a great idea this idea of a weekly meeting so it's like a live or zoom meeting where people share here's the thing i've learned about using ai and then this weekly stats email of here's how much we're using chatgpt across the org here's some people that did some awesome work amazing and i especially love this very simple heuristic of if your ceo uses chatgpt or claude or whatever daily it's gonna work out yep that is super cool i know it's early but what kind of impact have you seen from a company kind of leaning into this and adopting ai widely anything you've seen either numbers wise

Dan Shipper:It's early it's really hard to say other than i think generally people who do this well now feel like they can do way more work than they used to without having to hire more people and so they're they're just they're just going further faster at the same budget i actually don't see you know i don't see a lot of people being like we're gonna like fire a bunch of people like also i don't really wanna do consulting around here like that like that sucks but we've never had to say no mostly people are like i'm just going to go further with the people that i have i think also back to kind of the first point i made about reassuring american jobs i have seen some companies not the ones that we work with but i have seen some companies of people that i'm friends with where they're like we have a call center somewhere but i think i can get the same amount done with like two employees in the us that have that use like one of these you know customer service platforms like they're still not totally automatic like i think that klarna ceo thing that was bullshit

Dan Shipper:But yeah you can have a couple people in the us that maybe maybe you pay a little bit less to than you would for like a 100 people somewhere else and obviously you know those are that's a calculus that everyone has to make for themselves but i've definitely seen that happen and yeah i think that's the get more done with the same amount of people

Lenny Rachitsky:Maybe to close out our conversation i want to come back to this idea that you referenced but i want to spend a little more time on this which is this idea of the allocation economy if i understand it correctly we've been in this knowledge economy where people get paid to do a thing and your thesis is that we're moving to this allocation economy where skills become the manager skills become more important and we're going to be spending more of our time managing i think what's amazing about this is it also tells you which skills will matter more in the future which is something i think a lot of people are thinking about so maybe just answer that question and share whatever you think is important to share to give people a sense of what you're thinking

Dan Shipper:Yeah so this is based on an article i wrote like two two and a half years ago so this is back before like agents were even like thought of as viable and i was like really trying to think about how do i express what in my experience using this every day like what skills are useful for me because i think that'll be the case for for a lot of other people and i think that's that's the kind of the best method i think to do these sorts of predictions is you have to be doing it all the time yourself and then that informs your opinion about this stuff so what i noticed using at the time like b t three or maybe g b t four was that i was spending a lot of time for example thinking about how do i communicate the problem how do i gather the right information for the problem how do i put it in the right way so that the model that i'm working with gets it how do i pick which model to give it to you and how do i maybe divide up the task to be like okay this model does this this model does this based on what i know to be like what's good and what's bad how do i give them feedback how do i have like a vision for what i want and a set of criteria for whether it's good all that stuff is exactly how i found myself using these tools and i was like oh that's just managing and and once that like once that clicks for you i think you'll start to see a lot of other things so a a really good example is there's a big complaint that it's like well how can i have ai do this like can't trust that they're going to do it well so i just i just do it myself and i'm just like yeah that's exactly what every first time manager says you always have this problem where you're like okay well if i delegate it it's not done in the way that i want it to be done if i do it myself i get no leverage and so that's how a manager has to learn how to be a manager is like when do i lean in and and maybe micromanage a little bit and when when can i delegate how can i trust it and how do i divide up the task and all that kind of stuff and so i think there's a lot of overlap in those skills and it just those skills are not broadly distributed right now but they will be in the future because it will be so much cheaper to be a manager

Lenny Rachitsky:And specifically i was looking at the article you wrote the skills that you highlight will be more valuable is evaluating talent vision taste and to your point when to get into the details when it makes sense to dive in yeah awesome and then there's also kind of a connected point you made that you referenced which is that generalists will become more and more valuable in the future you mentioned that everyone and every is a generalist yeah share a little bit about that

Dan Shipper:Yeah i find i mean maybe it's because i'm a generalist you should take take this with a grain of salt same i same think that's one of the things that has made ai so awesome for me is like i love to dabble in different things so it's like in one day i can be like coding an app and like making a video and like making images and writing and like all that kind of stuff and charjibouti is right there with me and think what we've basically what has happened as civilization has progressed from like ancient greece to now is what we've discovered is the more that we specialize the the better we can coordinate across many different people and so it's sort of it's like the adam smith you know like there's a pin factory and someone's making a pin or whatever his thing is is specialization against trade and there have been a lot of really good impacts of that and i think you can like one of my favorite examples of this is is back to like ancient greece and ancient athens athens is was a civilization of generalists at least for citizens it was there's like they have some you know a bad history with women and people who are slaves but like let's just put that to the side for a second if you're a citizen generalist you could you could be expected to be a fighter a judge a juror maybe a general like there's you could expect it to have many different roles inside of your society in your lifetime that changed though because athens became an empire and as it became an empire if you're gonna send like a general off to like go and invade sicily or whatever you you want that person to be like pretty skilled and so it started to break the general kind of thing into people start to have specific roles they coordinate with each other and all that kind of stuff and i think that that pattern has actually been really good for developing civilization but it's also in a lot of ways like it's not as fun it's actually really cool to be a well rounded person and i think the interesting thing about ai is that it's a little bit like you can think of it like having 10,000 phds in your pocket it's like it knows so much about every little branch of human knowledge and every art form and every you know way of making things or building things and you just have access to that so it's doing a lot of the it's good for doing a lot of the specialized tasks that you might have had to spend like ten years getting good at you know learning about this particular species of cicada so you know exactly how they like you know reproduce but now you've got this thing in your pocket that can tell you all about that in any given context at any given time and so you're empowered to jump a lot more between all those different domains of skill and and you can get more done as for example like a founder where i think we can stay at 15 people much longer than we would be able to so the people inside of every can stay generalists for much longer and i think that that may like sort of ripple out into the rest of the economy where instead of gigantic massive corporations where each person is doing one little button turning you have many more smaller organizations with more generalists and i think that would actually be a really good thing

Lenny Rachitsky:This reminds me i was talking to my personal trainer that i'm trying out for a little bit and she said that she's a very big vision kind of high level person and not good at executing like we're staying organized and chattpt is such a godsend for her because she's just like here's what i wanna do roughly just help me get it done

Dan Shipper:That's great yeah i love

Lenny Rachitsky:And it really made me think about just how much value all this stuff is going unlock this was amazing it was everything I wanted it to be but with that we reached our very exciting lightning round Dan are you ready I'm ready here we go what are two or three books that you find yourself recommending most to other people

Dan Shipper:Well I already recommended one which is War and Peace definitely gotta read that if you want like a Tulsa like primer I would read The Death The Death of Ivan Ilyich another good one is A Swim in a Pond in the Rain which is by George Saunders and that's a collection of Russian short stories that is also about writing and I in particular I really like the Russians because they're a lot of the Russian novelists are dealing with the effects of technology on a traditional Russian way of life and they're very kind of in this really interesting middle ground between a sort of romantic outlook on the world and a more rationalist like we're we're progress we're making progress and that's one of the things you'll find in Anna Karenina when God what's the guys what Levin is out in the fields with the peasants like doing the scythe thing like that's that's Tolstoy like kind of like thinking about oh what would it be like instead of being a nobleman who's like trying to make make farms way more efficient I was just like with my scythe that was like really happy anyway so they're dealing with a lot of similar stuff to I think AI The Master and His Emissary is another really good one and that's about basically how the different hemispheres of the brain view reality it's really really good and I think it I think it relates to a lot of AI stuff too I think yeah I think I think those are my those are my three or four yeah

Lenny Rachitsky:Excellent list I think nobody's mentioned most either any of these so this is that's always a good sign your favorite recent movie or TV show you really enjoyed

Dan Shipper:Yes I really love Deadwood have you seen it

Lenny Rachitsky:I I absolutely love it I remember when they stopped it for some reason I think he had to go do something else at HBO it so sad it was it's amazing yeah

Dan Shipper:David Milch is incredible national treasure incredible writer but what I what I really think what I really love about it and I only recently watched it is he talks about Deadwood being about how order forms out of chaos so it's this like frontier town people are going to it and like there's no law there's no rules and by like season three there's like a mayor and like you know there all the industry has come in and it's a real proper town and I just love that and I think there's a lot of there's a lot of parallels from the like the western frontier to technology frontiers and so I think that show is like a really interesting study in that kind of dynamic

Lenny Rachitsky:I love how everything connects to how tech works and how AI came to be I I love this thank you do you have a favorite product you've recently discovered that you really love

Dan Shipper:I don't have a good answer for that because I just spend a lot of time using our internal products but my stock answer is Granola so I do I do really love Granola my one gripe with them and I hope they listen to this podcast is I really wanna export all my notes I want an API but other than that think it's a fantastic product

Lenny Rachitsky:That is definitely the most mentioned product in this segment for the past couple months so yeah catch up Granola I can't help but mention you get a year free of Granola if you become an annual subscriber of my newsletter what a freaking deal and not just you but your whole company gets free Granola for a year what the what a deal

Dan Shipper:This is not a paid promotion by me I just you know that's just what how I feel so I'm glad I'm glad it's part of the bundle

Lenny Rachitsky:Yeah incredible okay do you have a favorite life motto that you often come back to find useful in work or in life

Dan Shipper:So basically like I use JTP all the time and has memory so I was like you know I'm going on Lenny's podcast what would my life motto be and it said your life motto is a witness deeply build bravely you you prize slow attentive seeing whether it's reading Tolstoy tracking meditation themes or X-raying a David Milch paragraph so we're we're it's hitting all the stuff I just mentioned which is really funny

Lenny Rachitsky:And

Dan Shipper:Then build bravely you turn those insights into concrete things like Every and Quora and long form essays and and all that kind of stuff so think there's I think there's something about that actually this reminds me this actually reminds me of the actual motto which is and I didn't come up with this I think it's like Pliny the Younger said do things worth writing about and write things worth reading seems like a pretty good summation

Lenny Rachitsky:Do things worth writing about and read things worth reading

Dan Shipper:Write things worth reading

Lenny Rachitsky:Write things worth reading that's that's should be the motto of both of our newsletters yeah that is really good okay and by the way i love that you asked chatgpt what's my life motto

Dan Shipper:And wait this is interesting so it didn't give me the answer but inspired the answer yeah and i think that's actually like exactly how i use it

Lenny Rachitsky:Wow it's an extension of our brains already

Dan Shipper:Yeah

Lenny Rachitsky:Last question i was reading somewhere where you wrote that you stopped writing at one point you were just like i need to do other things i need to build this company and then you'd realize i need to get back to writing because things started going sideways and i feel like this is such an interesting corollary to a lot of the stuff you talked about do things that make you happy stay close to joy just share what happened there because i didn't know that

Dan Shipper:This is definitely not a lightning round thing i'll expound but i'll try to do it as quickly as possible perfect i think generally when you're building a company even if you do it the way that i do it or did it which is you know you don't raise a lot of money and you try to you try to stay in control there's a big temptation to try to run the company in the way you think you should and i have this weird thing where i'm like i really love writing but i also really love business and there just was there were not a lot of models for me of people who had successful businesses that that were also writers turns out there are but i didn't know about that for a while and so you know early on at every like we were it was growing really well because i was writing a lot nathan was writing a lot and when i stopped writing the business didn't work as well because media businesses don't follow the same pattern as tech startups because if you're a media business and you are a founder who then hires people to make the product which is right if you have product market fit before you lose it and maybe you hire people that are good writers but that's hard it's total opposite pattern for startups you just build the first version of the product and then you hire people to build the rest of it and you know so that's what i did and i also really struggled with okay what are the implications for that and for my career and and i think it was hard for me to admit like i actually wanna write because i just didn't have any examples of someone being the kind of writer that i wanted to be and what's really interesting is like three years into the business like the business had been pretty flat i was like pretty miserable because i was like not doing the thing that i really wanted to do and i asked chachi petey i was like is there are there any examples of writers that have built businesses and it was like yeah joel spolsky who built trello and stack overflow there's jason fried who i've known for a long time and i've always always looked up to but i forgot about in this context there is sam harris who's got a great podcast and he's got a gigantic meditation app there is bill simmons who's like incredible podcaster and also built the ringer sold to spotify for a couple $100,000,000 like there's a lot of these people and there are patterns that they use to build companies that are pretty well understood they're just not typical silicon valley patterns and so i was like cool like i just wanna be a writer i think it would be really fun and so i sort of flipped i still have the builder entrepreneur founder part of my identity but i sort of flipped it writing is at the center and i'm like unapologetic about it and that's actually good for the business it's good for me and it's good for the business and the more i've leaned into that doing the thing that like if you told anyone that you were starting a business where it's like well we're gonna be a newsletter and we're gonna incubate all these apps and we're gonna do consulting and whatever they would be like you're nuts everyone wants to do that of course every founder wants to do that but you have to focus you to you can't write whatever but every time i've kind of just leaned into something that feels like the most the ultimate luxury of my my hidden secret desire it's actually worked a lot better and i think you end up what what it really is is there's a huge tax to doing something every day that you're not quite you don't quite like that much or you're not quite a fit for and by sort of giving into that those secret desires you end up finding a shape for the work that you do and the business that you build that is good for you and that's always gonna be a somewhat unique shape from other businesses that have been built there's it's always gonna rhyme with other things but i think finding that unique shape instead of just kind of cargo culting like what you think a company should look like is definitely a much better way to be successful and it's also a much better way to live

Lenny Rachitsky:I think this is gonna hit hard with a lot of people who are listening who are maybe founders or wanna be founders and this resonates with a lot of people that have been on this podcast sharing similar lessons dan this was incredible two final questions where can folks check out every find you online how can listeners be useful to you

Dan Shipper:So you can find us at every to i'm also on twitter at danshipper you can go there to check out our products our newsletter if you want to stay on top of ai all that kind of stuff i also have a podcast it's called ai and i you can find it on youtube and on spotify and how can people be useful honestly i think the most useful thing someone like me based on what i wanna do is like i want people to find interesting cool ways to use ai that like actually helps make their lives better so like just go do that and tell me about it and i think that'll be great

Lenny Rachitsky:What's the best way to tell you is it comments on your youtube show is it emailing you dm you

Dan Shipper:I would say tweet me okay you if you subscribe to every you can also reply to those emails and they they eventually get forwarded to me so tweet me reply reply to every and if you want a comment on youtube great i'm not in the youtube comment comments as much as i should be

Lenny Rachitsky:Don't do that maybe don't do that yeah okay well dan this was incredible thank you so much for sharing thanks for being here thanks for having me bye everyone

Lenny Rachitsky:Podcast you can find all past episodes or learn more about the show at lenny'spodcast.com see you in the next episode