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Podcast Summary: Lenny's Podcast - How I AI with Claire Vo
Episode Title
Announcing a brand-new podcast: “How I AI” with Claire Vo 🔥 Episode Description This episode introduces a new podcast, "How I AI," hosted by Claire Vo, an engineer and AI builder. The podcast aims to showcase practical and impactful uses of AI tools in everyday work, providing actionable insights and live demonstrations for listeners looking to enhance their efficiency and skills in AI.
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Key Highlights
- Introduction of "How I AI"
- The podcast's mission is to demystify AI by focusing on practical applications rather than theoretical discussions.
- Each episode features guests who share specific use cases of AI in their work, emphasizing live demonstrations and workflows that listeners can implement immediately.
- The format is designed to be accessible, with episodes lasting about 30 minutes.
- Claire Vo as the Host
- Claire brings extensive experience as an engineer, three-time Chief Product Officer, and AI product builder.
- She is recognized for living the AI experience and sharing her continuous learning with the audience.
- Focus on Real Use Cases
- The podcast prioritizes real-world AI applications over hypothetical scenarios.
- It highlights how various professionals, from product builders to team leaders, can leverage AI to improve their outcomes.
- The Role of AI in Workflows
- AI is portrayed as a tool that can drastically reduce the time taken to complete tasks (e.g., reducing a two-week project to two hours).
- Discussions revolve around the integration of AI into daily tasks and how to adapt workflows to maximize AI's potential.
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Key Discussions & Concepts
- AI Transformation in Work
- The rise of AI is viewed as a major shift in how work is performed, causing excitement and anxiety among professionals.
- The importance of understanding which AI tools to focus on versus those that may not have immediate relevance is emphasized.
- Building with AI
- Sehil Lavingia, CEO of Gumroad, is introduced as the first guest who shares insights on using AI to enhance product development.
- Lavingia discusses the use of AI to automate coding tasks, suggesting that AI can write a significant portion of code, freeing engineers to focus on architecture and design.
- Organizational Adaptation
- The conversation touches on how organizations can adapt to AI tools, addressing cultural shifts and team dynamics.
- There’s a focus on reducing bottlenecks in development processes to maximize the benefits of AI.
- Motivation and Incentives in AI Adoption
- Techniques for motivating teams to adopt AI tools include financial incentives and fostering an engaging work culture.
- Lavingia shares experiences of competitions to encourage team members to use AI in their workflows.
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Takeaways
- AI Readiness: Organizations need to assess their readiness for AI integration and be proactive in training and adapting workflows.
- Continuous Learning: Professionals should stay informed about the latest AI tools and trends to maintain a competitive edge.
- Practical Application: The podcast emphasizes a hands-on approach to AI, encouraging listeners to experiment with tools and incorporate them into their work.
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Conclusion The episode serves as an engaging introduction to "How I AI," providing insights into meaningful AI applications in today's workplace. Claire Vo and her guests aim to empower listeners with the knowledge and tools necessary to thrive in an AI-driven environment.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:04Today I've got something really special for you. You may not realize this, but we're living through one of the most extraordinary moments in history. How we live, how we work, and how we build is all changing with the rise of AI. It's both exciting, but it's also often overwhelming. Manivas are wondering if we're falling behind. What we should be paying attention to and what we can safely ignore, and also just how to best use some of these new tools and technologies in our lives and in our work. That is why I am so unbelievably excited to announce the launch of a new podcast called How I AI with ClareVote.
0:37The mission of Clare's new podcast is to show you how people from all walks of life have figured out how to use AI tools in their day -to -day life to improve both the quality and efficiency of their work. What makes this podcast unique is that it's designed to give you highly practical and actionable tips and tricks and workflows that you can copy and start using immediately. No philosophical debates about the future of humanity or pontification on what might be possible some day. Each episode is going to be about 30 minutes, often shorter. The guests will share one or two specific use cases that they found useful in their work, and they'll be live screen sharing to show you exactly how they do everything that they describe.
1:15I couldn't imagine a more perfect host for this podcast than ClareVote. Clare is an engineer, a three -time cheap product officer, a founder, and on the side has been building her own AI product that's now making six figures. What I love about Clare is that unlike a lot of people online, she doesn't just talk about using AI. She lives and breathes it and builds with it and is constantly sharing everything she's learning online. I can't wait for you to learn from her and from her amazing guests. This is the first ever new podcast under the Lenny's Podcast Network. Depending on how this goes, we may add more podcasts down the road.
1:49And just to be clear, nothing changes with Lenny's Podcast, this is just more free content coming your way every Monday morning. If you're building products, leading teams, starting a company, or just want to learn how to actually use AI in your life, this podcast is for you. What follows is the first episode of the podcast. If you like what you hear, head on over to howiapod .com to find future episodes, and a pro tip for the richest experience, since there's going to be a lot of screen sharing and live demos, you're going to want to watch the video version. So definitely check things out on YouTube or on Spotify, which includes video.
2:25Now here is the first episode of Howi AI with Clare, but can you do something that used to take two weeks in two hours, and that's like a 40 times speed increase. So that's kind of like the number that I have in my head generally, like what's the most optimistic case if you kind of remove all the bottlenecks, something that would take 40 hours would take one hour. If you're suggesting to us that AI is going to raise the bar on what's possible to do, you are certainly setting the standard. The majority of human engineering will be removing tech debt, such that AI engineers can actually shift features.
2:58It's also scary, I think, which is why I think so many people shy away from this stuff, is like there is a part of why change is uncomfortable, is that change can kill you. There's like a fear of change, it's like job security, right? But the end of the day, I think it's sort of also job insecurity.
3:14Hey everyone, welcome to Howi AI, a podcast on how AI is transforming how we get things done. I'm Clare, product leader and AI obsessive here on a mission to help you build better with these new tools. Today, I have an absolute powerhouse guest, Sehil Lavingia, CEO and founder of Gumroad. If you don't know Gumroad, it's the platform that has helped creators sell over a billion dollars of products directly to their audiences. Sehil has been at the bleeding edge using AI to transform how companies build products in right code, doing everything from open sourcing the entire Gumroad repo to paying his employees thousands of dollars if they can write more AI power code than he does.
3:55Today, he's going to show us exactly how he does it. Let's dive in. This episode is brought to you by EnterPrint. EnterPrint is a customer intelligence platform used by leading CX and product orgs like Canva, Notion, Strava, Hinge and Linear to leverage the voice of the customer and build best in -class products. EnterPrint unifies all customer conversations in real time. From GONG recordings to Zendes tickets to Twitter threads, it makes it available for your team for analysis. What makes EnterPrint unique is its ability to build and update a customer -specific knowledge graph that provides the most granular and accurate categorization of all customer feedback and connects that feedback to critical metrics like revenue and CSAT.
4:39If modernizing your voice of the customer program to a generational upgrade is a 2025 priority, like customer -centric industry leaders Canva, Notion and Linear, reach out to the team at EnterPrint .com slash howiai. That's EN -T -E -R -P -R -E -T .com slash howiai. Hey, so I'm super excited to have you here. And before we dive into the demos, I wanted to call out something that you said a couple days ago, which is Devon, the AI Engineering agent who I also love, is writing 41 % of your PRs right now. And you expect it to go to 80 % by the end of the year. So do you think that's the baseline that we should all be shooting for?
5:28Do you think your way ahead of the curve? Where should we all be compared to that benchmark that you just said? I feel like I tell the team constantly, like we have a lead, you know, but the lead is getting shorter and shorter every day, every week. There's a new model coming out. So I would say, by the end of next year, I would suspect that like every and hearing team and anything company is using cursor and Devon and V0 and all these tools to ship a multiple times faster. And the question is mostly like how my organization adapts such that those people can do so. Like the bottlenecks are shown up in other places.
6:06Like Togi just tweeted about his Shopify AI stuff today. And I think that becomes the question is like how fast can you actually change your organization, your culture, especially when you're remote. It's harder to make these big changes across the org to get people to learn your stuff, to try and fail and cross share learnings, you know, all that, all that kind of stuff. Okay. So we're going to do it one at a time, which is you're going to show us how you actually redesign or build something using these tools. So we'll get your screen up and you can walk us through how you think about things.
6:39Awesome. Yeah. I mean, so I think the coolest thing about all this AI stuff is that you get to spend more time doing what you really enjoy, which to me, and I think you as well, like solving customer problems. And for this product that we build is called Flexile. And it's, you know, you can think of it like a like a store ordeal built specifically for the way that we run the business, which is like hiring a bunch of people. A lot of project based, a lot of hourly based, not the retainer, all sorts of different types of people remote in person full time and let them choose their equity split, manage your cap table, all of that stuff and like the same product.
7:18And one of the reasons I love AI is that I can basically just use the product and instead of running into some issue and being like, Hey, engineering, can you go solve this and then spending all this time like writing up a spec, you know, then putting that into, you know, sending that to a designer, the designer will then do like tomorrow or the next day will then do one of mock. There'll be some back and forth. And then it will go to like next week on Monday. It'll go to an engineer. They might have some questions that goes back to the desire. And by the time it shifts, you know, it makes it to production, even for something relatively trivial, you know, it's been two weeks or something, right?
7:51And so like, can you do something that used to take two weeks in two hours and that's like a 40 times speed increase. So that's kind of like the number that I have in my head generally, like what's like the most optimistic case if you kind of remove all the bottlenecks, something that would take 40 hours would take one hour and thus pretty awesome. So even in this form, like pretty simple, and I built the software. So I'm like, you know, I'm not like saying, oh, it's so terrible. But there's always room to improve. And even on this one screen, which is the contractor invitation page, there's like already a couple things that I noticed.
8:28Like aren't big enough to like really ask someone to do everyone's busy. They have their own stuff that they're working on. But there are like a few things that I noticed. Like for example, the day picker is kind of terrible. Yeah. Like it just uses like the, you know, the native day picker. It's not humanized, you know, you can't type in like next Monday or this Monday or have like a nice day picker, you know, if you go to like Shad Cn. And this is the beauty of open sources, you know, and the YAI is so good, there's a lot of open source. You get like a nice day picker like this, right? It's like nicely humanized and you could do all sorts of cool stuff.
8:59So that's like one thing I noticed that I think is like a really good candidate. For this, I would go straight to deb and I would, you know, it's, it doesn't really really need that much scoping. It's kind of just like replace date widget, you know, date picker in contractor invitation screen with the Shad Cn day picker. We might as well. I mean, the cool thing with Devon is you can like do that while you do other stuff. So there's, there's no risk really. So I can select the flexile repo and you know, say for this specific page, like update the date picker from the browser native. You know, input to Shad Cn import it for acquiring.
9:38I've never actually used this button, but again, this is a good example. Even somebody using this stuff, like you have to constantly like up your gain, learn more. You know, basically, I think this should be really like a rich text like this. Like you can just type into it and you could type in like next Monday, I think recent at a cool demo like this where they have more like a natural language, something like this and you could type in in one hour tomorrow at 9 a .m. These sorts of things or Slack actually has something similar where if you go into a canvas, you know, this is our roadmap. If you type in like Thursday, right?
10:17This is kind of like what I think would be really cool. So I think this is also like I'm going to have Dev and do multiple versions and then we can take a look at how far I've gone on them. But this is kind of how I would generally work is I would just take these forms and say like, you know, build this form. So you're you're putting into V0, you know, use this form using the very descriptive great requirements magical though. And then you're going to use V0 to get a prototype. Yeah. So generally my flow is V0 Dev and cursor is probably how I would say it. Like generally I V0 is my prototyping tool of choice.
11:03And once I have like a really good prototype that I'm happy with, then I go to Dev and if Dev and sort of fails to completely finish, then I open it up in cursor though. I think last week, Dev and launched this pairing mode where you can actually like jump in. And so I haven't really experimented with them yet. But that's presumably I would use something like that going forward where I could actually just jump in and fix the changes. The nice thing is Dev and actually runs, you know, one of the most annoying things about being a developer is just getting set up. You know, just getting your admit, your your developer requirements set up, your and variables, local host.
11:40One of the tips I have for engineering organizations that are large, which is if you can make your environment easy to set up for AI, it's probably a lot easier to set up for new hires. So it pays off to sort of use that as a testing ground for how easy your it is for any new engineer to get started, whether or not AI. So you have V0 in theory going, there it goes. Yeah. Okay. So you have V0 going on building you a prototype. I have a question here, which is, you know, you mentioned Shad Sien as your component library. Was that driven by, you know, using these AI tools and, you know, those those component libraries being out of the box or was that something you were looking at before?
12:23Yeah, it was a huge reason to switch and try to adopt a lot of these tools both. I think it's it's one reason that I think many people haven't really. It hasn't clicked, I guess. The AI stuff they're like, oh, I tried it. It didn't really work. It's not that good. It makes a lot of mistakes. It's you know, basically it's faster for me to do it than to have AI do it. And I found that that's like a lot of it is just like AI is good at certain things. It's a really good at front ends, really good at react. It's really good at tailwind Shads and stuff. So if you're not using those sorts of tools, you're not going to get the value like trying to ship something like this with like rails in the back and end like outwire or whatnot in the front end.
13:00Like these just just doesn't exist. Like you would have to spend all your time just getting this to work. You know, some jQuery calendar thing. You think, you know, that's how government was for a long time. One of the things I wonder is if, you know, engineering leaders will decide on particular transitions or migrations to make just to power this stuff so that their teams can move a little bit faster because they're just seeing themselves be left so far behind compared to those who are maybe using some of these libraries and technologies natively. I actually think that like the majority of human engineering will be removing tech debt such that AI engineers can actually ship features.
13:43Basically like designers will be shipping features because if you think about it, what are they doing? Right? They are thinking about what the features should do. And then engineers are just basically setting up the groundwork, the framework, the defaults, the standards, the LinkedIn, the CI pipeline, the infrastructure, the dev setup, such that designers actually are more and more capable over time, like basically taking their idea. Like if you were a designer, you would like just design this part, you know, you'd design this, but you wouldn't design like all the little interactions in here. Right?
14:15Like you would just design like that because it would just take too long. Oh, you wouldn't even consider it because you didn't play, you know, you didn't, for example, like often you'll have design and they didn't consider a mobile. Okay. So you got this design. Let's take a look at it. It looks pretty good. It has the magical date creation, which is tight. There you go. Type a magical date and it works. So it's not just the design, it's the functionality. And you said the next step for you from V0 isn't to Devon. So how does that transition work? What are you doing? You know, normally I would have a few back and forths here.
14:52You know, you could spend like three or four prompts, like 10, 20 minutes, like really nailing like the interaction, right? You may say like, you know, I'd add a clear button or you know, when you had deleted it should actually delete. And this stuff will get only faster and faster. But once, you know, once you're happy with what you have, normally I would take like the final prompt and I would just paste that into Devon, you know, and I would basically do similar to what I was doing before. And I can see Devon doing it. It's thing having lots of fun. And I could start in you Devon and basically do that, right?
15:28So like on here, on this page, and you reuse the exact same prompt. It'll this form. Yeah, it's often, I mean, sometimes if I'm going back and forth and I learn stuff, like I'm like, for example, this, yeah, I may just add here, you know, like all these are kind of like learnings where I could, it's basically I'm like, oh, my spec could have been better. Like this, these are things that human engineer also would have maybe not done, you know, like I basically just kind of go back and forth and like build basically I'm like, the V0 is kind of clarifying my spec in a way. Do you use any of the code from V0?
16:08Sometimes I do. Like sometimes I'll take this and just use this command. And if I put this and I went into cursor, if I had cursor open on something, if I had to say I had an open on this, for example, I would just go to terminal and I would just paste this right in and it would put in this component. This is for a different reposite to the app. Shats the end, but it would basically like, you know, slot that file in and then I could reference the file and and you can also, I believe, just like, you know, you could, you could, you could share it. And you could literally like, just give the URL effectively, right?
16:45Like this. And you could just say, like, you know, mimic, mimic this, right? You know, you could say more things, you know, sorry, example, I noticed that like in this thing, like I probably don't want the date to change in line. I like this parentheses is kind of weird. I'd probably add like a little note, you know, so I'd be like the putting the date in parallel to sees is kind of weird. But it below the input as a note. Yeah. I love putting I mean, what this does, but for some reason, I feel like I'm vibing with this person, like, they know what I mean when I say note, I mean, like slightly smaller font size, like gray, you know, like, no, like I feel like a desire would get it.
17:30So, you know, this is kind of like what I would give to Devon and and then it would, it would, you know, run off and do its thing. It'll wake up and it'll do all these things. All the stuff that I would basically do, right? Open cursor, get the thing, find the files that need to get changes. But I personally, one of the things I think is really, really important is spending more time in v0. Like I think many people just like, they do a first pass and they basically, I think MVPs are no longer enough. Like you can actually spend like 10, 20, 30, 40 minutes here. If you know that Devon is going to be able to execute, like, sometimes you don't want to spend too much time here because it's just creates work for the engineer, right?
18:09You're like, oh, now I have to think about this and that and this and then all these like little bits that would make the customer feel really good. The user experience would go up and the developer experience would go down, right? But if you know an AI is going to be implementing all of that stuff and they're going to do it into like a very high level of conscientiousness, you might say, oh, by the way, we designed it to like have this or like, you know, different roles, for example, right? Like different roles have different amounts. They'll preview in the drop -down. You know, so one may be like 200 now or one may be like two paper projects, etc.
18:41You know, one may be 250k a year. Just for fun, I might say like one may even have multiple pay rates because I've been exploring this idea, generally. And I think part of the beauty of not doing it yourself is to happy accidents. Like, yeah, I may just take your spec and actually do a benefit with it than you would have. And so yeah, that's kind of how I use it. And then I generally, if you're hosted, you know, depending on the projects, our newer projects are all next jazz, host John Vercell, so they'll even give you like a preview branch, right? Where I mostly love doing front -end stuff with Devon.
19:19Actually, now with the Anthas pairing thing, I could actually go in and like, run Rails console and like check the backend stuff too. But you know, with the preview branches, like I love making changes to anti -work .com because I can test them almost immediately, right? I can be like, you know, let's say a new person joined the company, you know, I can just say, hey, add this person who joined the company. This is their motto. By the way, pick a fun icon that matches for them. Like I didn't pick any of these icons. I would not have made myself a king, for example. I just said, like I basically just asked everyone in Slack, like tell me if you want it to link anywhere and what you're, what you want, you're, you know, you're, you're slogan to be.
20:02And then I asked Devon to actually do it and pick an icon for each person. That brings me to something I was thinking about, which is when you were in V0 and you were asking it to add on features, I was playing the product manager in my brain and I was thinking, oh, in past lives, people would say, no, that scope creep. We're just focused on the date picker or we're just focused on updating this component. We can't kind of scope creep and add more, more features. And what I think, I think is interesting. I'm curious your point of view, is you can really start to go to the edges of some great user experience.
20:39And it's less about how much time will this take or is it too complicated? It's more about what's actually going to work and be useful. Yeah, totally. And like I often, like, I mean, maybe this annoys some people at the company. But like as I'm doing V0 stuff, like on other things, I'll be, I'll like go into the issue and be like, let's see if I have one here. Like I want it to improve the multiple periods for roll, as I mentioned, right? Like this is it. And I'll, you know, I'll be like, I'll just go in here and be like, you know, like this one I ended up, I was like doing something with gusto and I kind of liked it, you know, and I was like, it turned on this.
21:16And it's just free. People can ignore it if they want, but it's like free design research, you know, it's all of a sudden, I have an example of this. This episode is brought to you by Vanta, building a business, achieving ISO 42 .001 compliance shows your customers that you're taking the necessary steps to ensure responsible usage and development of AI. But the process can be time consuming, tedious, and very expensive. With Vanta, achieving compliance can be done in a fraction of the time and at a fraction of the cost. 95 % of the required document templates are prebuilt for you, accelerating the process, helping you demonstrate trustworthy AI practices in scale your business.
21:57Start with Vanta's free ISO 42 .001 checklist, which gives you a breakdown of the compliance process in the road ahead. Download it at vanta .com slash how I AI. That's vantta .com slash how I AI for the free compliance for AI checklist. You know, I see you as an individual being able to add this and fix that and update, you know, the homepage and all those things and use Devon sort of asynchronously. I'm curious how you've made this work at the team level. Like, what are the actual operational pieces that have to be in place for this to not degrade into chaos and then what about just culture makes this work for you all?
22:42Yeah, I mean, first off, it's not easy. Change is uncomfortable, right? It requires work and energy and biologically, I feel like we're starting to save our energy all the time. So you have to, you know, you have to motivate people, you have to make it exciting. You know, there's a reason like colleges and classes are in person, right? Like, there's a, it's like fun to train together. You know, it's easier to go to the gym in a gym than like at home in your bedroom, right? Part of it is doing it myself too. You know, like if your manager, you're annoying boss is telling you to do something. It's different than like leading from the front a little bit.
23:16I often do like screen shares. Actually, like I recorded these videos and I recorded this one with Josh Pigford on YouTube, which is like three hours long. And I basically did it because I wanted to, I was like, this isn't, you know, got a lot of views actually. Like I, I, yeah, that's how important I felt to us, not just for me, but for everybody. But I was like, basically recorded it for the team. I had my team in mind as I was doing it. Like, check out how cool it is. Like, imagine once we switched to tailwind, like how fast we can, you know, do this kind of thing and like how, you know, it sort of is part of that bringing the energy.
23:48We also financially motivated people. So there's a couple times here. I'll find you an example of a Devon competition we did. So we did this competition where we did 30, 33 ,000 dollars split amongst whomever opens and merges more Devon PRs than me over the course of May. So, you know, it's kind of a fun way to like motivate people to learn. It's time bound. And I actually did pretty well. Let's see the results. So I got, I got fourth. I opened 27 PRs with Devon. And then three people beat me. So it's, and I, you know, I do a lot of easy wins, you know, so like it props to all the engineers who, who, who did it.
24:30But yeah, I, this is all my, all my Devon PRs. A lot of people, like there's no way you use Devon. Like you're making it up. You're just trying to like go viral or whatever. I'm like, not really like I'm just trying to like help people be more productive. I didn't know that was controversial. But you know, there's like a lot of small things. I can remove this part of the homepage. There was this like recap that we do in Slack that's generated by AI that recaps like everything that shipped last week. And so I said, Hey Devon, could you, you know, like, for example, these two things don't really need to be here because there's nothing under them, right?
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25:00So I just said, Hey, Devon, like, could you like, you know, only show the products that actually have shipments and like hide the other ones? And also like some of these aren't really shipments. Like this one is only the back end. The front end hasn't shipped yet. So like, make sure, you know, the update the AI prompt that we're using for this, which by the way, I've never seen. Like I just, I just know that there's an AI prompt that's, you know, involved. And you know, and that's actually what this, what this one is, right? So it found this like weekly, you know, recap and it, it, you know, it made these changes and they created this PR.
25:33So we can actually go in and see this GR and we can confirm my, my suspicion or not, which is, oh, turns out there's a prompt. So it could primarily on shipments, feature improvements and bug fixes, right? Prioritize these categories. And then it also did something here, which is if we looked, it did this, it added a filter. So, you know, basically only the projects that have more than one. The thing that I would critique about myself is that ideally we would have a test. And maybe there is a test that I don't know about. So this is when the human would come in. I don't normally just hit merge on these things.
26:08You know, I would normally send this to somebody else and be like, Hey, I did my best shot at this. And you could see here for the factory, phaptonic, the party, and then I, I pasted a, pasted this, the link to the update. You know, I would normally like say, Hey, yeah, and you make sure this looks good to you. And if there are any tests that meet updating. And personally, I think this is way better that like someone has done most of the work for you. And basically, I think humans will start the process. I think of it like flying a plane. Like humans will take off, decide where to go and land typically.
26:47You know, do QA in this context. But, you know, not actually build right all this code. Like look up, like, for example, you know, like dot filter versus dot trim or dot clean or like every language is different. Right. But overall, I know rough amount of software architecture that like this is, you know, this is the right solution. Right. To this problem, you're just adding a simple filter that we're just things. And ideally, there would be a test. So I would have even higher confidence that this has done what it what it should, you know, one thing I was going to call out on the code you just wrote showed was I find that these AI engineering tools are pretty good engineering citizens.
27:29And that their code is well commented. They call out when you know, there's a little bit document doc strings and things like that that make it easier to parse some of those those changes. Okay. So this is what we kicked off with. It's the native date picker released with the Shad CN1. Yeah. So the core problem I have here, which I guess is I need to make sure it works. Okay. So you're showing the time lapse of Devon here, which is basically of screen recording of every single step along the way right now you're in the in the terminal and the IDE. So you can actually play step by step how Devon got all this code done.
28:13It looks like it hasn't here. You know, really thinning and thought and planning. Exactly. And then the part that I'm looking for and hopefully it did it is that it would run it would run the app locally and it often does this, but sometimes if you have a complex app and we just open source this so that it may have like broken. But it would actually run the browser in its little local box and then it would test it. So let me ask it to do that around the browser and it's awake. So it should pretty quickly start doing doing that and it's this is Devon right here Devon box Mr. Devon. And also we can watch it on this one right it's doing it's it's little thing.
28:56So because I used magical it in quotes it assumed is that I wanted to call it magical. And you can see we actually open source it recently. So it's I always working on an old repo which is my guess is why it's not working exactly right. So now there are two things I decided so you know replace this input the standard input with the type date with this new component that's definitely correct. And then it created this this component where it goes through and it it replaces it. So the thing that looks so wrong here is it doesn't it doesn't look like there's any AI magic. So something sort of making which maybe it doesn't need to.
29:37Maybe it's smart enough to know if I just type in today tomorrow or yesterday, but you know it this probably wouldn't work if I said like three Sundays from now, but maybe that's fine. Maybe that's not actually what anyone would would really do. This maybe even as a good example is something that to your point like I think AI has really good hygiene engineer hygiene where it is on a on a micro level like it's a better engineer. Yep. Then human engineer would be. So you have to spend more time on like the architecture and like the planning aspect of it making sure your execution is correct like calling it magical date picker.
30:11Maybe it's not the correct approach. I would probably call it natural language date picker or something like that because magical doesn't really give you any insight into what's magical about it. But besides that my guess is like this code, this parts natural language is actually like probably really really robust, really good. Even this magical look like check out the math on this guy, you know, I'm like whoa. Pretty simple, but like how long would it you know how many times would you have to tweak it to like oh, I you know like I got it wrong. This is like fancy ad days function like it's pretty pretty clever how it's doing how it's doing that.
30:51Find index. It's getting all you know, it's basically figuring out like when you type next Monday, it's like three days and you're adding the days to get to the right right day in the calendar and it's parsing the day based on it's like that's like this would be like a you know two years ago this would be like a so impressive for like there to be almost like an engineering challenge, you know, like I would hire an engineer based on this, which is now they would just go to chat GPT and be like and yeah, it would it would it would work. So what you could do is to go back to the V0 if you really wanted to enhance this, you know, you could just sort of take this component and actually working on a way to like embedded, you know, bring up component back into V0 and then you could like iterate on it and the UX like a designer could even do that with V0 and then you could then pull it back in to the code base.
31:38So you could kind of like do a lot of this like customer focus iteration, you know, on the you know, wizzy wig way basically like dream waiver, you know, versus like like in code, I mean like this you have to think so hard to understand like what how do you and for the user experience looking at this, right? The amount of like brain power and it just hurts my head. What I think about is imagine that an engineer took this and went a week away and came back and said here I built your magical natural language, you know, day picker and you said no that's not really what I want. It feels like such an expensive iteration to throw out that cone and do something new, whereas you you can iterate that on that, you know, in a couple minutes or a couple hours over and over and not feel like you're wasting, you know, time and expense and people's honestly, people's like motivation and energy, I think about that a lot as well.
32:36Yeah, if you spend two weeks on something and you're you know, you're annoying CEO, it's like no, that's not what I meant. It's like you know, and then you got to spend you got to go for a long walk in a coffee bag before you're back to work, right? So it's so much better to like really spend time, you know, two or before. Yeah, I just leaned in so we got redesigned from V0 on this new employee onboarding and not only did it get new features, but you got a beautiful update on the date picker with some suggested common time frames in there. Yeah, this is super smart. Like and all I did, by the way, I just had build a really dope natural language day picker for an HR product onboarding form.
33:23So probably the critical piece is like HR, right? So it's like building it in the context of the problem you're trying to solve, which is, you know, if you're if you're if you're building like like a party planning tool, you'd probably have like Christmas or you know, like whatever, what you know, but in this case, yeah, next Monday and two weeks, you know, probably it's going to be next Monday. That's my guess is that is the most common, you know, but you could say actually where, you know, we're we're based in a, you know, a country in which like we work we start on Sundays or Tuesdays and you know, and you could do all sorts of interesting things or we're in a, you know, a place in which our date, you know, we put the day before the month or whatever.
34:06And so yeah, just just yeah, just a great opportunity to like really push the envelope and really spend more time, even I love this, but the first name and last name next to each other. So you can read it out nicely. So we just watched you ship in a new component, build a magical and now dope date picker for your employee onboarding tool. You showed us how to get this done across your org and you prove that you're at least in the top five people shipping P .Harsva D .E .V. or with Devon at at the company. Oh, by the way, this is merged. We got emerged. So it looks like a, it's like a big no mistakes.
34:51So yeah, next week, it'll be better. Like think about that. Would have been like, you know, at least 24 hours. So that's like a nice 10x speed increase. This is a lot about engineering at Gumroad. And you said, you know, 41 % of your peers are being written by Devon. You're writing code. You know, what org is AI coming for next for the 80 % of the work you think is going to be started by agents. I mean, I think you could see, you know, if you think about what are the orgs that exist, you know, it's like design, product, engineering, customer support, sales, marketing. And I really, I don't know, I actually was probably more optimistic on like full automation.
35:28I don't think we're going to really get there for a long time. There's just always like a higher level abstraction that you get to operate at. So you know, there will be, for example, like I think there's a lot more marketing automation that could happen in terms of like suggested tweets. You know, it could just watch what's happening in GitHub. It could like suggest, hey, this thing, we, you know, we have a content framework. We should host about this feature right now. I noticed myself having to like, you know, say, hey, this thing shipped in GitHub. By the way, only half of the chip, only the backend.
35:57There's still all this nuance that I think, you know, marketing could get like a lot more efficient sales too, I think. Like, for example, there are all these people who sign up, you know, they show up in our database basically, right? And they're just emails, right? You go to flex style, you sign up. But there's I think a lot more automation, you know, if someone signs up to flex style with like style and you're a time is calm, you know, you could sort of queue up an email to them. There's so much focus on customer support. We even built our own customer support product with AI, which is great.
36:26You know, you can, you can talk to AI and it'll help you out. But this is all like reactive, you know? Well, what if I'm just browsing the page? And, you know, it knows that I'm in New York from IP, you know, and you can wave at me and, you know, it could be like, hey, what's up? I was New York. It's kind of cold out there. It's kind of raining. No. And you'd be like, oh, yeah, it is, it is raining in New York. Why do you care? And you can have a conversation. And, you know, they're like, well, you know, it's kind of nice to be able to like talk about the problems customers are facing. So yeah, I mean, there's, I think sales like making more, making support more about sales, making it more proactive.
37:06I think making design more about product, making engineering more about architecture, you know, I think there's always going to be more and more stuff to do. I may, maybe even like, like, like prioritization, I think I spend a lot of my time, like, you know, for example, like going through GitHub and saying, okay, we have all these tasks. We have like 27 things like, what do we build first? And right now it's like in my head, basically, I've seen all these things go live or maybe even a better example more people would relate to would become road. You know, we have this big road map. And, you know, I basically, I think I'm pretty good at this, but the reason I'm good at this is because I've seen every single thing ship.
37:45And so I kind of can very quickly sort of be like, okay, this is, this is, you know, going to generate like, you know, maybe a hundred to two hundred thousand dollars in value for creators, creator earnings, this will probably generate like three hundred four hundred K. But then I have to also put on my engineering hat and say, okay, this is going to take like 40 hours of an engineer's time. This is going to take 300 hours of an, you know, and like, do all this math, which you can go to business school, learn about bite and like all these things. And I could totally imagine, like, you know, a button here that's like a magical rank, right?
38:17And then it just like sort of goes through and maybe you should actually know that because you missed out this fact, it's actually much harder to ship or we don't yet use shats the end. So actually, you're underestimating this. And it could like, reprioritize it, right? And you could do all sorts of interesting things. That's like a huge, I mean, think about how many people at these large companies, especially like they're spending so much of their time on strategy, quote, unquote, which is really just prioritization, right? And what we do is we just email all creators. And we just put together a list of things.
38:49And I just, we just sent this Google doc to like our top 200 creators in 2024. And we kind of like rank this based on what they wanted from us because it turns out like they're the ones paying our bills, right? And we started shipping and imagine, I could take all it in all that data. I mean, all their sales volume, we have access to right in our database. And you could somehow kind of like get a good, good sense of like, okay, what feedback should we be listening to? And you know, you can imagine like you just hit a button that says like, yeah, you know, assigned to Devin, right? You know, and then boom is done.
39:25I mean, that's another weird thing though, right? It's like, well, if, if, if AI gets so good, why do you need to do everything? That why, why, what's the point in prioritization? Part of the organization is a function of like limited resources. So that's the whole thing. It's like, I really, I mean, I would love to be in place where I come to the office and I have no idea what's going to happen. Like I have no idea what we should even be building. And we spend time as a team like thinking about like, what should we build? Like we got like, there's nothing, there's no issues in get in, in get.
39:52Yeah. Like because every issue is solved. So, you know, it's clear to wear an inbox zero. And so it's like, okay, well, what do we do? And then we sit around and talk and pontificate and eat lunch. And you know, we really have to think hard about like, oh, we should do something totally radical. Like open source, the whole thing, you know, like things that like an AI probably wouldn't suggest that it wouldn't be in the in the next token prediction or even in the reasoning models. We're like, okay, we should do really advanced content customization options. Okay, like what is that? Okay, let's go design and v0, watch that and do a lot of research.
40:28You know, I think research is obviously going to get a lot better with with AI, but still humans have to go talk to people, ask them questions, user research, design research, market research. I think sales will always be important. I think marketing, like I think marketing will be one of those things where like the average marketing, like AI will get so good at marketing that like the level of what's interesting to a human. Like kind of like that, you know, that meme of the Saratoga Springs guy drinking the water and whatever, obviously like putting banana on his face. Like to me, that's like a sign of how good AI is that like that level of content production is now necessary to go viral.
41:06Like it's insane. I can't imagine like how the like you took to make it just it's so funny. Like it's so thoughtful and so many funny different little like Easter eggs, you know, and I think that like that's kind of what will need to happen is just like you have to like up the game more and more and more like you know right now artists can post like a painting on Instagram and people will be like, oh amazing painting. But like in five years, it's going to be like you need to like post the freaking movie. It's like that's just what people will expect. Like hey, we just want to see you're like 30 minutes side -firing movie that you did.
41:36And that's just like for free, sorry. I just know that's what that's what that's what our gov, you know, that's what's happened to our our gov -mean system. Or we can spend like a whole day talking about like how do we get better at recommending products on Gumroad? Is there a totally different kind of, you know, expect recommendation experience that's like much more AI -driven and much more natural language than just like a marketplace of you know, feed of products? Or you can remember things about your your tastes, your preferences, you know, it can learn from you or launching a community feature pretty excited about this next, not later this week, which is pretty big, but we, you know, there's just tons of yeah, I mean who knows.
42:11I mean, it's exciting. It's also scary, I think, which is why I think so many people shy away from this stuff. It's like there is this like part of part of why changes uncomfortable is that like change can kill you, you know, like there's like a fear of change, like, you know, it's like job security, right? But at the end of the day, I think it's sort of also job insecurity. Like we don't know if like what we do will continue to be valuable. I can say for sure, if you're, if you're suggesting to us that AI is going to raise the bar on what's possible to do, you are certainly setting the standard.
42:42I think you're showing an entirely new way for teams to build. You're showing an entirely way for a leader to show up and actually contribute to the work product of the company, which I think is really inspirational. And then I think you're also showing, look, you just have to go learn these things and try things and, you know, you're going to get in a loop, but over time, you can actually become one of these leaders that's on the leading edge as opposed to lagging edge. So I think it's great. And I think you're setting the standard for how if you do orgs are going to operate in the future, if not, if not companies.
43:15So we're going to we're going to wrap up with a quick lightning round to question. If you can encourage people to learn just one of all all your toys here, you just showed just one that you think is the highest impact, which one would it be? VZero, honestly, maybe this is biased, I think, because I spent so much time in product. I think of our more of an engineer. I think cursors agent mode is pretty crazy. I think if you're like a CEO of a company, I think Devon is like the most impressive, like the fact that you can just be in Slack and just talk to it. And it will it will do this. It's crazy.
43:51So I think a lot of it depends on like your role in the, you know, what you value and what you think is the most important. But VZero, I think it's just like the lowest hanging fruit. I think everyone is kind of familiar with sigma. And I think a lot of people think that like, you know, okay, now people, no one questions that they I can code even though a year ago, people were like, say, oh, we can't code or whatever. But now people are like, oh, we can't design. It doesn't have taste, you know, and so it's just like really, you know, like design a really nice onboarding wizard or a bank, you know, and like watch it do a better than you will hide from a bank than any bank has, you know.
44:24So I think that this is like something anyone can do. A kid could like have fun with this. So I would say, I probably dominate V zero. And then, you know, the cool thing about V zero is it shows you what's possible. And so then if you want to execute on it, then you have to like learn all the other, all the other tools. The other nice thing about V zero is that it comes with a URL. So you could build like a tick -tock toe and send it to your friend and play tick -tock toe, which is a kind of a nice, you know, a replator bolt on you or lovable like they, they're, there's just so many. We've talked a lot about how you are setting up incentives like bounties to get people to use AI or learn AI.
45:04But how do you get AI to do what you want? So I found that everybody has their own tactic like their mean, they offer money. What is your strategy for getting AI to listen to you when it's in a little bit of a loop? I mean, honestly capital letters, not even like a mean way, hopefully, hopefully it doesn't take it the wrong way. But I just think it's like it is, kind of like, it's kind of old school, I guess, you know, you have like literally like lower case and upper case. And like, it's just a really easy way of saying like this part is really important. Like, please do not ignore this specific part.
45:41There's another hack that I love called et cetera. So if you want a list of things, you can name like two of them and then just say et cetera. And it will often like riff. It's really fun to just like be like, it's kind of like a test, you know, it's like you've come up with two or three, but you need 10. It's kind of a nice way of letting it like be more more more creative. So well, this has been incredible. And we have to wrap by showing you have not only redesigned your own product, but you've taken on the baking industry by generating onboarding for a neo bank, apparently here in in v zero.
46:19I really appreciate you giving us a real look at how you're building with AI, both as individual as a team. I think you're definitely going to inspire tons of people to rethink how they show up at work. And I think if you folks are going to be looking over their shoulder, thinking that you're about to lap them once or twice on from some of this building. So thank you so much for the time. Where can people find you and how can they be helpful to you? Yeah, you can find me on on Twitter slash x. My handle is at shl. And helpful. I don't know. Just anytime you see something I've said that you disagree with or think of my thoughts could be approved upon just replied.
47:01Let me know. Dm me. I'm always looking to get feedback and improve my thinking. So I just appreciate everyone tuning in and I'm excited to see what everyone builds. Thank you so much. Thank you. Thanks so much for watching. If you enjoyed this show, please like and subscribe here on YouTube or even better leave us a comment with your thoughts. You can also find this podcast on Apple podcasts, Spotify, or your favorite podcast app. Please consider leaving us a rating and review, which will help others find the show. You can see all our episodes and learn more about the show at howiipod .com. See you next time.
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