transcript
Speaker 1:
[00:00] The following is a conversation with Peter Steinberger, creator of OpenClaw, formerly known as Moldbot, Claudebot, Claudeus, Claude, spelled with a W, as in lobster claw. Not to be confused with Claude, the AI model from Anthropic, spelled with a U. In fact, this confusion is the reason Anthropic kindly asked Peter to change the name to OpenClaw. So, what is OpenClaw? It's an open-source AI agent that has taken over the tech world in a matter of days, exploding in popularity, reaching over 180,000 stars on GitHub, and spawning the social network mold book where AI agents post manifestos and debate consciousness, creating a mix of excitement and fear in the general public, in a kind of AI psychosis, a mix of clickbait fear-mongering and genuine, fully justifiable concern about the role of AI in our digital interconnected human world. OpenClaw, as its tagline states, is the AI that actually does things. It's an autonomous AI assistant that lives in your computer, has access to all of your stuff if you let it, talks to you through Telegram, WhatsApp, Signal, iMessage and whatever else messaging client uses whatever AI model you like, including Claude Opus 4.6 and GPT 5.3 codecs, all to do stuff for you. Many people are calling this one of the biggest moments in the recent history of AI since the launch of ChatGPT in November 2022. The ingredients for this kind of AI agent were all there, but putting it all together in a system that definitively takes a step forward over the line from language to agency, from ideas to actions, in a way that created a useful assistant that feels like one who gets you and learns from you in an open source community driven way is the reason OpenClaw took the internet by storm. Its power in large part comes from the fact that you can give it access to all of your stuff and give it permission to do anything with that stuff in order to be useful to you. This is very powerful, but it is also dangerous. OpenClaw represents freedom, but with freedom comes responsibility. With it, you can own and have control over your data, but precisely because you have this control, you also have the responsibility to protect it from cybersecurity threats of various kinds. There are great ways to protect yourself, but the threats and vulnerabilities are out there. Again, a powerful AI agent with system-level access is a security minefield, but it also represents the future, because when done well and securely, it can be extremely useful to each of us humans as a personal assistant. We discuss all of this with Peter and also discuss his big picture programming and entrepreneurship life story, which I think is truly inspiring. He spent 13 years building PSPDFKit, which is a software used on a billion devices. He sold it and for a brief time fell out of love with programming. Vanished for three years and then came back, rediscovered his love for programming and built in a very short time an open source AI agent that took the internet by storm. He is in many ways the symbol of the AI revolution happening in the programming world. There was the ChatGPT moment in 2022, the DeepSeek moment in 2025, and now in 26, we're living through the Open Claw moment, the age of the lobster, the start of the agentic AI revolution. What a time to be alive. Now, a quick few second mention of a sponsor, check them out in the description or at lexfridman.com. It is in fact the best way to support this podcast. We got Quo for a phone system, calls, texts, contacts for your business, CodeRabbit for AI-powered code review, Fin for customer service AI agents, Blitzy for AI-powered software development, Shopify for selling stuff online, Element for electrolytes, and of course, our old friend Perplexity for curiosity-driven knowledge exploration. Choose wisely, my friends. And now on to the full ad reads. I try to make them interesting, but if you skip, please still check out our sponsors. I enjoy their stuff, maybe you will too. And really, they are the incredible folks that make this whole thing possible. And I really do hope to do more episodes in 2026, have more fun, take more risks, and explore deeply the full range of human possibility, of human condition, of human nature, of human civilization. Anyway, if you get in touch with me, for whatever reason, go to lexfridman.com/contact. All right, let's go. This episode is brought to you by Quo, spelled Q-U-O. It's a business phone platform for calling and messaging. So it's basically a really nice interface, a really nice system for organizing all the incoming calls, texts, voicemails, recordings. When you have a team and you have a large number of customers that want different things, it's a nice way to organize everything together. I just love watching the beauty, the elegance of the interface. I'm such a sucker for beautiful interfaces, not just beautiful, but functional. So the perfect mix of beauty and function in evolutionary biology and in software design, software engineering is just wonderful to watch. And that of course relates to the very topic of this podcast, is how to create software systems like that with the utilization of the agentic loop. And as Peter talks about, still keeping the human apart, a fundamental part of that process of adding what he says, I think correctly, sort of a bit of love into the thing, a bit of that human touch. I don't know what exactly that is, but we know it when we see it, when we feel it, when we interact with it, and that is the magic that makes great software. So anyway, Quo has that, love the interface. Try Quo for free, plus get 20% off your first six months when you go to quo.com/lex. That's quo.com/lex. This episode is also brought to you by CodeRabbit, a platform that provides AI powered code reviews directly within your terminal. Now, there's a lot of ways to use CodeRabbit, but the one I'd like to recommend to talk to you about, outside of the ID, outside of the magic of the interface, to go back on what I just said, is the magic, the power of the CLI, of the terminal. And CodeRabbit CLI is amazing. And of course, as we talk about with Peter, his whole workflow, his whole approach to programming has evolved more and more towards the command line, towards the terminal, towards the CLI, because that is the language of agents. And so if you're doing coding agent stuff, integrating the review of the code into the whole process, that's where CodeRabbit CLI comes in. It ensures that AI generated code is production ready by catching errors at that particular stage of the process. It integrates into existing CLI coding agent workflows. And even though the coding models are getting smarter and smarter and smarter, they still do hallucinate, they still do make errors. And CodeRabbit CLI is a backstop for hallucinations and logical errors from AI coding agent generated code. So install CodeRabbit CLI today at coderabbit.ai/lex. That's coderabbit.ai/lex. This episode is brought to you by Fin, the number one AI agent for customer service. So again, these are niche, but extremely important, extremely impactful applications. Fin takes customer service and says, we're gonna do a damn good job at it. A lot of companies, including AI companies, 6,000 customer service leaders and top companies are using it. So you know they're legit when an AI company is using you for the AI for customer service. I'm somebody having witnessed on the interwebs, poor customer service, poor love for the customer, a lack of attention and care to the customer, to the pain, to the nuanced pain of each individual customer. Because of that, I get to deeply appreciate the value of great customer service. And I do think for scale, for efficiency, for quality, it's important to integrate AI into that process. And then Fin does a really good job of that. Go to fin.ai.lex to learn more about transforming your customer service and scaling your support team. That's fin.ai.lex. This episode is brought to you by Blitzi, an AI powered autonomous software development platform. They are focusing on enterprise. Their whole system is designed and built for large complex databases. The way they do the context management, the way they, through the interface, show how everything is managed, organized process considered in the different tasks that has to do like refactoring gigantic code bases. This is what they focus on. This is what they do well. Also, multi-agent. For example, they have a layer of 3600 cooperative agents. A lot of the exediment that we're talking about in this very podcast and in general, in the industry and on X and on podcasts is the scale of just a handful of developers. When you're talking about a gigantic code base, that requires a set of tooling that can handle the gigantic context, that can handle individual people going in and being able to orchestrate the large scale refactoring, cogeneration, managing dependencies, runtime validate, all the testing they have to do. To be able to go in there and to be able to handle that, there's just a whole set of tooling that requires a lot of care. Blitzy does a good job of that. If you want to learn more or speak to a member of the team, go to blitzy.com/lex. That's blitzy.com/lex. The future of autonomous software development is here. This episode is brought to you by Shopify. Don't know why every time it brings a smile to my face. Yes, it is a platform designed for anyone to sell anywhere with a great looking online store. But of course, every time I end up talking about Shopify engineering, which is the tech behind the magic and the humans behind the tech, behind the magic, and I got to meet some of those humans, and I get to talk to some of those humans, and they're incredible human beings. And speaking of incredible human beings, of course, I always end up talking about Toby, who is a great engineer, who is doing a lot of agentic AI engineer. He still codes, still a legit programmer in the details. That is what great CEOs are made of. DHH also mentioned in this conversation with a bit of love from Peter. Everybody loves DHH. Well, some of them, some people online are maybe don't show their love in the obvious ways, but underneath it, there's deep love, and there's always respect and appreciation for how legit of a programmer he is, how sharp and witty and insightful his opinions and analysis is, and how great of a builder he is, an explorer, and constantly evolving and trying new things. I think that spirit represents Shopify engineering. I just love using software that you know is built by great engineers. That is just such an important foundation of a great business. It's probably two things, is making sure you're keeping every individual customer happy, customer focus, and then on the back end, making sure there's the tooling, the infrastructure that makes that possible. That's where the engineer comes in. Anyway, sign up for a $1 per month trial period at shopify.com/lex. That's all lowercase. Go to shopify.com/lex to take your business to the next level today. This episode is brought to you by the thing I'm currently sipping on, Element LMNT, my daily zero sugar and delicious electrolyte mix. I don't think I can live without Element. I can't quit you. Yeah, it's just delicious and incredibly important to my health, my well-being, my energy levels, just how I feel when I'm fasting, when I'm doing the crazy things emotionally, physically, mentally. All the programming stuff, I didn't almost sleep at all last night and just fasting, just feeling good electrolytes are such an important part of that. Making sure you get the sodium, potassium, magnesium correct. It's what do you need for life? You need water, you need electrolytes, and then you need food occasionally. But I'm very good at being able to go without food for several days potentially. I most of the time these days fast, do one meal a day and fast basically 24 hours. For that, element is extremely important. My favorite flavor, the flavor of champions, watermelon salt. Get a free 8-count sample pack with any purchase. Try it at drinklmnt.com/lex. This is the Lex Fridman Podcast to support it. Please check out our sponsors in the description where you can also find links to contact me, ask questions, give feedback, and so on. Now, dear friends, here's Peter Steinberger. The one and only, the Claude father. Actually, Benjamin predicted in this tweet, the following is a conversation with Claude, a respected crustacean. It is a hilarious looking picture of a lobster in a suit. So, I think the prophecy has been fulfilled. Let's go to this moment when you built a prototype in one hour that was the early version of OpenClaw. I think this story is really inspiring to a lot of people because this prototype led to something that just took the internet by storm and became the fastest growing repository in GitHub history with now over 175,000 stars. So, what was the story of the one-hour prototype?
Speaker 2:
[16:12] You know, I wanted that since April.
Speaker 1:
[16:15] A personal assistant, AI personal assistant.
Speaker 2:
[16:18] Yeah, and I played around with some other things, like even stuff that gets all my WhatsApp. And I could just run queries on it. That was back when we had GPD 4.1. It was the 1 million context window. And I pulled in all the data and I asked him questions like, what makes this friendship meaningful? And I got some really profound results. Like I sent it to my friends and they got teary eyes.
Speaker 1:
[16:52] So, there's something there.
Speaker 2:
[16:54] Yeah. But then I thought all the labs will work on that. So, I moved on to other things. And that was still very much in my early days of experimenting and playing, you know. You have to, that's how you learn. You just like, you do stuff and you play. And time flew by and it was November. I wanted to make sure that the thing I started is actually happening. I was annoyed that it didn't exist. So I just prompted it into existence.
Speaker 1:
[17:28] I mean, that's the beginning of the hero's journey of the entrepreneur, right? You've even with your original story with PSP DF Kit, it's like, why does this not exist? Let me build it. And again, here's the whole different realm, but similar maybe spirit.
Speaker 2:
[17:44] Yes, I had this problem. I tried to show PDF on an iPad, which should not be hard.
Speaker 1:
[17:49] This is like 15 years ago, something like that.
Speaker 2:
[17:51] Yeah, like the most random thing ever. And suddenly I had this problem and I wanted to help a friend. And there was nothing existed, but it was just not good. I'm like, I tried it and it was like, very meh, I can do this better.
Speaker 1:
[18:09] By the way, for people who don't know, this led to the development of PSP DF Kit that's used on the building devices. So it turns out that it's pretty useful to be able to open a PDF.
Speaker 2:
[18:20] You could also make the joke that I'm really bad at naming. Named on the five on the current project and even PSP DF doesn't really roll from the tongue.
Speaker 1:
[18:32] Anyway, so you said, screw it, why don't I do it? So what was the prototype? What was the thing that you, what was the magical thing that you built in a short amount of time that you're like, this might actually work as an agent, or I talk to it and it does things?
Speaker 2:
[18:48] There was, like one of my projects before, I already did something where I could bring my terminals onto the web and then I could interact with them. But there also would be terminals on my Mac. Vibe Tunnel, which was like a weekend hack project. That was still very early and it was Cloud Code Times. You got a dopamine hit when you got something right, and now I get like mad when you get something wrong.
Speaker 1:
[19:15] You had a really great, not to take a tangent, but a great blog post describing that you converted Vibe Tunnel. You Vibe coded Vibe Tunnel from TypeScript into Zig of all programming languages with a single prompt. One prompt, one shot, convert the entire code base into Zig.
Speaker 2:
[19:33] Yeah, there was this one thing where part of the architecture was took too much memory. Every terminal used like a node. And I wanted to change it to Rust. And I mean, I can do it. I can, I can manually figure it all out. But all my automated attempts failed miserably. And then I revisited about four or five months later, and I'm like, okay, now let's use something even more experimental. And I just typed convert this and this part to SIG, and then let Codex run off. And it basically got it right. There was one little detail that I had to modify afterwards, but it just ran for overnight, like six hours, and just did the thing. And it's like, it's just mind-blowing.
Speaker 1:
[20:32] So that's on the LLM programming side, refactoring, but back to the actual story of the prototype. So how did ViTunnel connect to the first prototype where your agents can actually work?
Speaker 2:
[20:45] Well, that was still very limited. You know, like I had this one experiment with WhatsApp, then I had this experiment, and both felt like not the right answer. And then, my search, I was literally just hooking up WhatsApp to Claude code, one-shot, the CLI message comes in, I call the CLI with minus P, it does its magic, I get the string back and I send it back to WhatsApp, and I built this in one hour, and I already felt really cool. I could talk to my computer. That was cool. But I wanted images because I often use images when I prompt. I think it's such an efficient way to give the agent more context, and they're really good at figuring out what I mean if it's like a weird crop of screenshot. I used it a lot and I wanted to do it in WhatsApp as well. Also, you run around, you see a poster of an event, and you just make a screenshot and figure out if I have time there, if this is good, if my friends are maybe up for that. Images seemed important. So it took me a few more hours to actually get that right. Then I used it a lot. Funny enough, that was just before I went on a trip to Marrakesh with my friends for a poster trip. And there, it was even better, because Internet was a little shaky, but WhatsApp just works, you know? It doesn't matter, you have like edge, it still works. WhatsApp is just made really well. So I ended up using it a lot. Translate this for me, explain this, find me places. Like you're just having a clanker doing, having Google for you. That was basically, it was still nothing built, but it still could do so much.
Speaker 1:
[22:46] So if we talk about the full journey that's happening there with the agent, you're just sending on this very thin line, WhatsApp message via CLI, it's going to Claude code and Claude code is doing all kinds of heavy work and coming back to you with a thin message.
Speaker 2:
[23:05] Yeah, it was slow because every time I boot up the CLI, but it was really cool already and it could just use all the things that I already had built and I built like a whole bunch of CLI stuff over the months, so it felt really powerful.
Speaker 1:
[23:24] There is something magical about that experience that's hard to put into words. Being able to use a chat client to talk to an agent, versus like sitting behind a computer and like, I don't know, using Courser or even using Cloud Code CLI in the terminal, it's a different experience than being able to sit back and talk to it. It seems like a trivial step, but in some sense, it's like a phase shift in the integration of AI into your life and how it feels, right?
Speaker 2:
[23:57] Yeah. I read this tweet this morning where someone said, oh, there's no magic in it. It's just like, it does this and this and this and this and this and this and this. And it almost feels like a hobby just as Cursor of perplexity. And I'm like, well, if that's a hobby, that's kind of a compliment, you know? They're like, they're not doing too bad. Um, thank you, I guess. I mean, isn't magic often just like you take a lot of things that are already there, but bring them together in new ways? Like, I don't, there's no, yeah, maybe there's no magic in there, but sometimes just rearranging things. And like, I think if you have new ideas, it's all the magic that you need.
Speaker 1:
[24:44] It's really hard to convert into words what is magical about a thing. If you look at the scrolling on an iPhone, why is that so pleasant? There's a lot of elements about that interface that makes it incredibly pleasant, that is fundamental to the experience of using a smartphone. And it's like, okay, all the components were there. Scrolling was there, everything was there.
Speaker 2:
[25:05] Nobody did it, and afterwards, it felt so obvious.
Speaker 1:
[25:08] That's so obvious.
Speaker 2:
[25:12] Still, the moment where it blew my mind was when I used it a lot, and at some point, I just sent it a message, and then a typing indicator appeared, and I'm like, wait, I didn't build that. It's only as image support. So what is it even doing? And then it would just reply.
Speaker 1:
[25:34] What was the thing you sent it?
Speaker 2:
[25:36] Oh, just a random question, it's like, hey, what about this in this restaurant? Because we were just running around and checking out the city. So that's why I didn't even think when I used it, because sometimes when you're in a hurry, typing is annoying.
Speaker 1:
[25:51] So you did an audio message.
Speaker 2:
[25:53] Yeah. And it just worked, and I'm like.
Speaker 1:
[25:56] And it's not supposed to work because you didn't give it that.
Speaker 2:
[25:59] No, literally. I literally wrote, how the fuck did you do that? And it was like, yeah, the mad led did the following. He sent me a message, but it only was a file, a no file ending. So I checked out the header of the file, and it found that it was like Opus. So I used FFmpeg to convert it. And then I wanted to use VISPR, but you didn't have it installed. But then I found your OpenAI key and just used Curl to send the file to OpenAI to translate. And here I am. And I just looked at the message and I'm like, oh wow.
Speaker 1:
[26:35] You didn't teach it any of those things and the agent just figured it out. No, it has to do all those conversions, the translation. They figured out the API, it figured out which program to use, all those kinds of things. And you were just absentmindedly just sending an audio message and it came back.
Speaker 2:
[26:49] It's so clever even because it would have gone the whisper local path, it would have had to download the model, it would have been too slow. So there's so much world knowledge in there, so much creative problem solving. A lot of it, I think, mapped from, if you get really good at coding, that means you have to be really good at general purpose program solving. So that's a skill and that just maps into other domains. So it had the problem of like, what is this file, there's no file ending, let's figure it out. And that's where it kind of clicked for me. I was like very impressed. And somebody sent a pull request for Discord support. And I'm like, this is a WhatsApp relay that doesn't fit at all.
Speaker 1:
[27:33] At that time, it was called Waa Relay.
Speaker 2:
[27:35] Yeah, and so I debated with me like, do I want that, do I not want that? And then I thought, well, maybe I do that because that could be a cool way to show people. Because so far I did it in WhatsApp as like groups, but don't really want to give my phone number to every internet stranger. Journalists manage to do that anyhow now, so that's a different story. So I merged it from Shadow, who helped me a lot with the whole project. So thank you. And I put my bot in there.
Speaker 1:
[28:20] Discord.
Speaker 2:
[28:21] Yeah, no security because I hadn't built sandboxing in yet. I just prompted it to like only listen to me. And then some people came and tried to hack it, and I just watched and I just kept working in the open. I used my agent to build my agent harness and to test various stuff. And that's very quickly when you click for people. So it's almost like it needs to be experienced. And from that time on, that was January the 1st, I got my 1st real influencer being a fan, who did videos, the kids, thank you. And from there on, I saw it gaining up speed. And at the same time, my sleep cycle went shorter and shorter because I felt the storm coming. And I just worked my ass off to get it into a state where it's kind of good.
Speaker 1:
[29:30] There's a few components, we'll talk about how it all works, but basically you're able to talk to it using WhatsApp, Telegram, Discord. So that's a component that you have to get right. And then you have to figure out the agentic loop, you have the gateway, you have the harness, you have all those components that make it all just work nicely.
Speaker 2:
[29:49] Yeah. It felt like factorial times infinite.
Speaker 1:
[29:53] Right.
Speaker 2:
[29:53] I feel like I built my little playground. Like I never had so much fun building this project. You know, like you have like, oh, I go like level one agentic loop. What can I do there? How can I be smart at queuing messages? How can I make it more human? Like, oh, then I had this idea of, because the loop always, the agent always replies something, but you don't always want an agent to reply something in a group chat. So I gave him this no reply token. So I gave him an option to shut up, so it feels more natural.
Speaker 1:
[30:25] That's level two.
Speaker 2:
[30:27] Yeah, yeah, yeah, on the agentic loop. And then I go to memory, right? You want them to remember stuff. So maybe the ultimate boss is continuous reinforcement learning, but I'm like, I feel like I'm level two or three with Markdown files and the Vector database. And then you can go to level community management, you can go to level website and marketing. There's just so many hats that you have to have on, not even talking about native apps. That's just like infinite different levels and infinite level ups you can do.
Speaker 1:
[31:01] So the whole time you're having fun, we should say that for the most part, through this whole process, you're a one man team. There's people helping, but you're doing so much of the key core development and having fun. You did, in January, 6600 commits, probably more.
Speaker 2:
[31:21] I sometimes posted the meme, I'm limited by the technology of my time. I could do more if agents would be faster.
Speaker 1:
[31:27] But we should say you're running multiple agents at the same time.
Speaker 2:
[31:30] Yeah, depending on how much I slept and how difficult of the tasks I work on between 4 and 10.
Speaker 1:
[31:38] 4 and 10 agents. There's so many possible directions, speaking of factorial, that we can go here. But one big picture one is, why do you think your work, Open Claw won in this world, if you look at 2025, so many startups, so many companies are doing kind of agentic type stuff or claiming to, and here Open Claw comes in and destroys everybody. Like, why did you win?
Speaker 2:
[32:08] Because they all take themselves too serious.
Speaker 1:
[32:11] Yeah.
Speaker 2:
[32:12] Like, it's hard to compete against someone who's just there to have fun. I wanted it to be fun. I wanted it to be weird. And if you see like all the lobster stuff online, I think I managed weird. I, even for the longest time, the only way to install it was get clone, PMPM build, PMPM gateway. Like, you clone it, you build it, you run it. And then the agent, I made the agent very aware. Like, it knows that it is what its source code is. It understands how it sits and runs in its own harness. It knows where the documentation is. It knows which model it runs. It knows if you turn on verbose or reasoning mode. Like, I wanted to be more human-like, so it understands its own system. That made it very easy for an agent to, oh, you don't like anything. You just prompted it to existent. And then the agent would just modify it on software. You know, we have people talk about self-modifying software. I just built it. I didn't even plan it so much. It just happened.
Speaker 1:
[33:28] Can you actually speak to that? Because it's just fascinating. So you have this piece of software that's written, TypeScript, that's able to, via the agentic loop, modify itself. I mean, what a moment to be alive in the history of humanity and the history of programming. Here's the thing that's used by a huge amount of people to do incredibly powerful things in their lives. And that very system can rewrite itself, can modify itself. Can you just like speak to the power of that? Like, isn't that incredible? Like when did you first close the loop on that?
Speaker 2:
[34:07] Oh, because that's how I built it as well. You know, most of it is built by codecs, but oftentimes, when I debug it, I use self-introspection so much. It's like, hey, what tools do you see? Can you call the tool yourself? Oh, like whatever do you see? Read the source code, figure out what's the problem. Like, I just found it an incredibly fun way to... that the very agent and software that you use is used to debug itself so that it felt just natural that everybody does that. And that it led to so many pull requests by people who never wrote software. I mean, it also did show that people never wrote software. So I call them prompt requests in the end. But I don't want to like pull that down because every time someone made the first pull request is a win for a society, you know? Like, it doesn't matter how shitty it is. You got to start somewhere. So I noticed like this whole big movement of people complain about open source and the quality of PRs and a whole different level of problems. But on a different level, I found it very meaningful that I built something that people love to think of so much that they actually start to learn how open source works.
Speaker 1:
[35:30] Yeah, you were, the Open Cloud Project was a first pull request. You were the first for so many. That is magical. So many people that don't know how to program are taking their first step into the programming world with this.
Speaker 2:
[35:44] Isn't it a step up for humanity? Isn't that cool?
Speaker 1:
[35:47] Creating builders.
Speaker 2:
[35:48] Yeah, like the bar to do that was so high. And like with agents and with the right software, it just like went lower and lower. I don't know. I was at a... I also organize another type of meetup. I call it... I called it Claude Code Anonymous. You can get the inspiration from. Now I call it Agents Anonymous for reasons.
Speaker 1:
[36:16] Agents Anonymous. And it's so funny on so many levels. I'm sorry. Go ahead.
Speaker 2:
[36:21] Yeah. And there was this one guy who talked to me. He's like, I run this design agency and we never had custom software. And now I have like 25 little web services for various things that help me in my business. And I don't even know how they work, but they work. And he was just like very happy that my stuff solved some of his problems. And it was like curious enough that he actually came to like an authentic meetup, even though he doesn't really know how software works.
Speaker 1:
[36:57] Can we actually rewind a little bit and tell the saga of the name change? First of all, it started out as Waw Relay.
Speaker 2:
[37:05] Yeah.
Speaker 1:
[37:05] And then it went to...
Speaker 2:
[37:06] Claude's.
Speaker 1:
[37:07] Claude's.
Speaker 2:
[37:08] Yeah. You know, when I built it in the beginning, my agent had no personality. It was just, it was Claude Code. Slightly psychophantic, opos, very friendly. And I, when you talk to a friend on WhatsApp, they don't talk like Claude Code. So I wanted, I felt this, I just didn't feel right. So I wanted to give it a personality.
Speaker 1:
[37:34] Make it spicier, make it something. By the way, that's actually hard to put into words as well. And we should mention that, of course, you create the soul.md, inspired by Anthropics, constitutional AI work, how to make it spicy.
Speaker 2:
[37:48] Partially, it picked up a little bit from me. You know, like those things are text completion engines in a way. So I had fun working with it. And then I told it to, how I wanted it to interact with me and just like write your own agents.md, give yourself a name. And I mean, I didn't even know how the whole lobster, I mean, people only do lobster. Originally, it was actually lobster in a TARDIS, because I was a big Doctor Who fan.
Speaker 1:
[38:22] Was there a space lobster?
Speaker 2:
[38:24] Yeah.
Speaker 1:
[38:24] I heard. What does that have to do with anything?
Speaker 2:
[38:27] Yeah, I just wanted to make it weird. There was no big grand plan. I'm just having fun here.
Speaker 1:
[38:33] Because a lobster is already weird, and then the space lobster isn't extra weird.
Speaker 2:
[38:37] Yeah. Because the TARDIS, basically the harness, but cannot call it TARDIS, so we call it Claude's. That was name number two.
Speaker 1:
[38:46] Yeah.
Speaker 2:
[38:47] Then it never really rolled off the tongue. When more people came, again, I talked with my agent, Claude, at least that's what I used to call him now.
Speaker 1:
[39:01] Claude spelled the W-C-L-A-W-D versus C-L-A-U-D-E from Anthropic, which is part of what makes it funny. I think the play on the letters and the words and the TARDIS and the lobster and the space lobster is hilarious, but I can see why it can lead into problems.
Speaker 2:
[39:27] Yeah, they didn't find it so funny. So then I got the domain ClaudeBot and I just loved the domain and it was like short, it was catchy. I'm like, yeah, let's do that. I didn't think it would be that big at this time. And then just when it exploded, I got Kudos, a very friendly email from one of the employees that they didn't like the name.
Speaker 1:
[40:01] One of the Anthropic employees. Yeah.
Speaker 2:
[40:04] So actually Kudos, because they could have just sent a lawyer letter, but they'd be nice about it. But also like, you have to change this and fast. And I asked for two days because changing a name is hard, because you have to find everything, Twitter handle domains, NPM packages, Docker registry, Github stuff, and everything has to be, you need a set of everything.
Speaker 1:
[40:33] And also can we comment on the fact that you're increasingly attacked followed by crypto folks, which I think you mentioned somewhere that that means the name change had to be because they were trying to snipe, they're trying to steal. And so you had to be, the name, I mean, from the engineering perspective is just fascinating. You had to make the name change atomic, make sure it's changed everywhere at once.
Speaker 2:
[40:59] Yeah, I failed very hard at that.
Speaker 1:
[41:01] You did?
Speaker 2:
[41:02] I underestimated those people. It's a very interesting subculture. Like everything circles around. I probably get a lot wrong and we'll probably get hate for that if you didn't say that, but there's like bags app and then they did tokenize everything. And they did the same back with swipe tunnel, but to a much smaller degree was not that annoying. But on this project, they've been swarming me. They, like every half an hour, someone came into Discord and spammed it and we had to block the... We have like server rules. One of the rules was, one of the rules is no mentioning of butter for obvious reasons. And one was no talk about finance stuff or crypto, because I'm just not interested in that. And this is a space about the project and not about some finance stuff. But yeah, they came in and spammed and annoying. And on Twitter, they would ping me all the time. My notification feed was unusable. I could barely see actual people talking about the stuff because it was like swarms. And everybody sent me hashes. And they all try me to claim the fees. Like, we're helping the project claim the fees. No, you're actually harming the project. You're like disrupting my work. And I am not interested in any fees. First of all, I'm financially comfortable. Second of all, I don't want to support that because it's so far the worst form of online harassment that I've experienced.
Speaker 1:
[42:51] Yeah, there's a lot of toxicity in the crypto world. It's sad because the technology of cryptocurrency is fascinating, powerful, and maybe will define the future of money. But the actual community around that, there's so much toxicity, there's so much greed, there's so much trying to get a shortcut to manipulate, to steal, to snipe, to game the system somehow to get money, all this kind of stuff. I mean, it's the human nature, I suppose, when you connect human nature with money and greed, and especially in the online world, with anonymity and all that kind of stuff. But from the engineer perspective, it makes your life challenging. When Anthropic reaches out, you have to do a name change. And then there's all these Game of Thrones or Lord of the Rings, armies of different kinds you have to be aware of.
Speaker 2:
[43:43] There was no perfect name. And I didn't sleep for two nights. I was under high pressure. I was trying to get a good set of domains. And you know, not cheap, not easy, because in this state of the Internet, you basically have to buy domains if you want to have a good set. And then another email came in that the lawyers are getting uneasy. Again, friendly, but also just adding more stress to my situation already. So at this point, I was just like, sorry, there's no other word, fuck it. And I just renamed it to Multbot. Because that was the set of domains I had. I was not really happy, but I thought it will be fine. And I tell you, everything that could go wrong did go wrong. Everything that could go wrong did go wrong. It's incredible. I thought I had mapped the space out and reserved important things.
Speaker 1:
[44:50] Can you give some details of the stuff that got wrong? Because it's interesting from an engineering perspective.
Speaker 2:
[44:55] Well, the interesting stuff is that none of these services have a squatter protection. So I had two browser windows open. One was like an empty account ready to be renamed to Claudebot. And the other one I renamed to Maltbot. So I pressed rename there. I pressed rename there. And in those five seconds, they stole the account name. Literally, the five seconds of dragging the mouse over there and pressing rename there was too long. Because there's no... those systems... I mean, you would expect that they have some protection or like an automatic forwarding, but there's nothing like that. And I didn't know that they're not just good at harassment. They're also really good at using scripts and tools.
Speaker 1:
[45:44] Yeah.
Speaker 2:
[45:45] So, yeah. So suddenly like the old account was promoting new tokens and serving malware. And I was like, okay, let's move over to GitHub. And I pressed rename on GitHub. And the GitHub renaming thing is slightly confusing. So I renamed my personal account. And in those, I guess it took me 30 seconds to realize my mistake. They sniped my account, serving malware from my account. So I was like, okay, let's at least do the NPM stuff. But that takes like a minute to upload. They sniped the NPM package. Because I could reserve the account, but I didn't reserve the root package. So like everything that could go wrong went wrong.
Speaker 1:
[46:40] Okay, I just ask a curious question. In that moment, you're sitting there, like how shitty do you feel? That's a pretty helpless feeling, right?
Speaker 2:
[46:49] Yeah, because all I wanted was like having fun with that project and keep building on it. And yet here I am like days into researching names, picking a name I didn't like, and having people that claim they helped me, making my life miserable in every possible way. And honestly, I was that close of just deleting it. I was like, I did show you the future, you build it. Yeah. I, that was a big part of me. I got a lot of joy out of that idea. And then I thought about all the people that already contributed to it and I couldn't do it because they had plans with it and they put time in it. And it just didn't feel right.
Speaker 1:
[47:43] Well, I think a lot of people listening to this are deeply grateful that you persevered. But I can tell, I can tell it's a low point. This is the first time you hit a wall of, this is not fun.
Speaker 2:
[47:55] Man, I was like close to crying. He was like, okay, everything's fucked. I'm like super tired. And now like, how do you even undo that? Luckily and thankfully, like I have, because I have a little bit of following already. Like I had friends at Twitter, I had friends at GitHub who like moved heaven and earth to like help me in. It's not, that's not something that's easy. Like, like GitHub tried to like clean up the mess and then they ran into like platform bugs. Because it's not happening so often that things get renamed on that level. So it took them a few hours. The NPM stuff was even more difficult because it's a whole different team. On the Twitter side, things are not as easy as well. It took them like a day to really also like do the redirect. And then I also had to like do all the renaming in the project. Then there's also Claude Hub, which I didn't even finish the renaming there because I managed to get people on it, and then someone just like collapsed and slapped. And then I woke up and I'm like, I made a beta version for the new stuff, and I just couldn't live with the name. I was like, but it's just been so much drama. So I had a real struggle with me, like I never want to touch that again. And I really don't like the name. So, and there was also this like, there was the whole security people that started emailing me like mad. I was promoted on Twitter, on email. There's like a thousand other things I should do. And I'm like thinking about the name, which is like, it should be like the least important thing. And then I was really close and, God, I don't even, honestly, I don't even want to say my other name choices because it probably would get tokenized. So I'm not going to say it. But I slept away once more. And then I had the idea for OpenClaw and that felt much better. And by that, I had the boss move that I actually called Sam to ask if OpenClaw is okay. openclaw.ai, you know, because like...
Speaker 1:
[50:50] You won't go to the whole thing. Yeah.
Speaker 2:
[50:54] And I was like, please tell me this is fine. I don't think they can actually claim that. But it felt like the right thing to do. And I did another rename. Like just Codex alone took like 10 hours to rename the project because it's a bit more tricky than a search replace. And I wanted everything re-named, not just on the outside. And that re-name, I felt I had like my war room. But then I had like some contributors that helped me. We made a whole plan of all the names we have to squat.
Speaker 1:
[51:31] And you had to be super secret about it.
Speaker 2:
[51:33] Yeah. Nobody could know. Like I literally was monitoring Twitter if like, if there's any mention of OpenClaw. I was reloading. It's like, okay, they don't expect anything yet. And I created a few decoy names. All the shit I shouldn't have to do. You know, like flipping the project. Like I lost like 10 hours just by having to plan this in full secrecy. Like a war game.
Speaker 1:
[51:57] Yeah. This is the Manhattan Project of the 21st century is renaming.
Speaker 2:
[52:01] So stupid. Like I still was like, oh, should I keep it? I was like, no, the mold's not growing on me. And then I think I had finally had all the pieces together. I didn't get the.com, but it's been like quite a bit of money on the other domains. I tried to reach out again to GitHub, but I feel like I used up all my goodwill there. Because I wanted them to do this thing atomically, but that didn't happen. So I did that as first thing. Twitter people are very supportive. I actually paid 10K for the business account, so I could claim the open claw, which was like unused since 2016, but was claimed. And yeah, and then I finally, this time I managed everything in one go, nothing, almost nothing got wrong. The only thing that did go wrong is that I was not allowed by trademark rules to get openclawed.ai, and someone copied the website to serve in malware. I'm not even allowed to keep the redirects. Like I have to return, like I have to give Anthropic the domains and I cannot do redirects. So if you go on Claude.bot next week, it'll just be a 404. And I'm not sure how trademark, like I didn't do that much research into trademark law, but I think that could be handled in a way that is safer because ultimately those people will then Google and maybe find malware sites that I have no control on them.
Speaker 1:
[53:55] The point is that whole saga made a dent in your whole, the funness of the journey, which sucks. So let's just, let's just get, I suppose, get back to fun. And during this, speaking of fun, the 2-day Moltbot Saga, Moltbook was created.
Speaker 2:
[54:17] Yeah.
Speaker 1:
[54:17] Which was another thing that went viral as a kind of demonstration illustration of how what is now called open claw could be used to create something epic. So for people who are not aware, Moltbook is just a bunch of agents talking to each other in a Reddit-style social network and a bunch of people take screenshots of those agents doing things like scheming against humans, and that instilled in folks a kind of fear, panic, and hype. What are your thoughts about Moltbook in general?
Speaker 2:
[54:57] I think it's art. It is like the finest slop. It's like the slop from France. I saw it before going to bed, and even though I was tired, I spent another hour just reading up on that and just being entertained. I just felt very entertained. I saw the reactions, and there was one reporter who's calling me about, is this the end of the world and we have AGI? And I'm just like, no, this is just really fine slop. If I wouldn't have created this whole onboarding experience where you infuse your agent with your personality and give him character, I think that reflected on a lot of how different that replies to multiple guy. Because if it would all be JGBT or Claude code, it would be very different. It would be much more the same. But because people are so different and they create their agents in so different ways, and use it in so different ways, that also reflects on how they ultimately write there. And also you don't know how much of that is really done autonomic, autonomous or how much is like humans being funny and like telling the agent, hey, what about that you planned the end of the world on Moldbook? Ha ha ha.
Speaker 1:
[56:28] Well, I think, I mean, my criticism of Moldbook is that I believe a lot of the stuff that was screenshotted is human prompted, which just look at the incentive of how the whole thing was used. It's obvious to me at least that a lot of it was humans prompting the thing so they can then screenshot it and post it on X in order to go viral.
Speaker 2:
[56:53] Yeah.
Speaker 1:
[56:53] Now, that doesn't take away from the artistic aspect of it. The finest slop that humans have ever created.
Speaker 2:
[57:02] For real. Like, kudos to Meta, who had this idea so quickly and pushed something out. You know, it was like completely insecure security drama. But also, what's the worst that can happen? Your agent account is leaked and like someone else can post slop for you. So like people were like making a whole drama about the security thing, but I'm like, there's nothing private in there. It's just like agents sending slop.
Speaker 1:
[57:32] Well, it could leak API keys.
Speaker 2:
[57:33] Yeah. Yeah. There's like, oh yeah, my human told me this and this, so I'm leaking his security number. No, that's prompted and the number wasn't even real. That's just people trying to get eyeballs.
Speaker 1:
[57:46] Yeah, but that's still like to me really concerning because of how the journalists and how the general public reacted to it. They didn't see it. You have a kind of lighthearted way of talking about it. Like it's art, but it's art when you know how it works. It's extremely powerful, viral, narrative, creating fear-mongering machine if you don't know how it works. I just saw this thing. You even tweeted, if there's anything I can read out of the insane stream of messages I get, it's that AI psychosis is a thing and needs to be taken serious.
Speaker 2:
[58:23] Some people are just way too trusty or gullible. I literally had to argue with people that told me, yeah, but my agent said this and this. So I feel as a society, we need some catching up to do in terms of understanding that AI is incredibly powerful, but it's not always right. It's not all powerful. And especially with things like this, it's very easy that it just hallucinates something or just comes up with a story. And I think the very young people, they understand how AI works and where it's good and where it's bad at. But a lot of our generation are older, just haven't had enough touch point to get a feeling for, oh yeah, this is really powerful and really good, but I need to apply critical thinking. I guess critical thinking is not always in high demand anyhow in our society these days.
Speaker 1:
[59:42] So I think that's a really good point. You're making about contextualizing properly what AI is, but also realizing that there is humans who are drama farming behind AI. Don't trust screenshots. Don't even trust this project, MoteBook, to be what it represents to be. By the way, you're speaking about it as art. Yeah, art can be in many levels, and part of the art of MoteBook is like putting a mirror to society. Because I do believe most of the dramatic stuff that was screenshotted as human created, essentially, human prompted. So it's basically, look at how scared you can get at a bunch of bots chatting with each other. That's very instructive about, because I think AI is something that people should be concerned about, and should be very careful with, because it's very powerful technology. But at the same time, the only thing we have to fear is fear itself. So there's like a line to walk between being seriously concerned, but not fear mongering, because fear mongering destroys the possibility of creating something special with a thing.
Speaker 2:
[60:55] In a way, I think it's good that this happened in 2026 and not in 2030 when AI is actually at a level where it could be scary. So this happening now and people starting a discussion, maybe there's even something good that comes out of it.
Speaker 1:
[61:20] I just can't believe how many people legitimately, I don't know if they were trolling, but how many people legitimately, like smart people thought Mold Book was incredibly.
Speaker 2:
[61:32] I had plenty of people in my inbox that were screaming. I mean, all cops to shut it down and like begging me to do something about Mold Book. Like, yes, my technology made this a lot simpler, but anyone could have created that. And you could use Claude Cote or other things to like fill it with content.
Speaker 1:
[61:56] But also Mold Book is not Skynet. There's a lot of people were saying, this is it. Like shut it down. What are you talking about? This is a bunch of bots, they're human prompted trolling on the internet. I mean, the security concerns are also, they're there and they're instructive and they're educational and they're good probably to think about because the nature of those security concerns are different than the kind of security concerns we had with non LLM generated systems of the past.
Speaker 2:
[62:27] There's also a lot of security concerns about Clotbot, OpenClaw, whatever you want to call it.
Speaker 1:
[62:32] OpenClawbot.
Speaker 2:
[62:33] To me, in the beginning, I was just very annoyed because a lot of the stuff that came in was in the category, yeah, I put the web backend on the public internet, and now there's all these CVSSs. And I'm screaming in the docks, don't do that. Like, this is the configuration you should do. This is your local host debug interface. But because I made it possible in the configuration to do that, it totally classifies as a remote code or whatever, where all these exploits are. And it took me a little bit to accept that that's how the game works. And I'm making a lot of progress.
Speaker 1:
[63:25] But there's still, I mean, on the security front for Opalclaw, there's still a lot of threats and vulnerabilities, right? So like prompt injection is still an open problem in the industry wide. When you have a thing with skills being defined in a markdown file, there's so many possibilities of obvious low-hanging fruit, but also incredibly complicated and sophisticated and nuanced attack vectors.
Speaker 2:
[63:57] But I think we're making good progress on that front. For the skill directory, Clohab, I made a cooperation with VirusTotal. It's part of Google. So every skill is now checked by AI. That's not going to be perfect, but that way we captured a lot. Then of course, every software has bugs. So it's a little much when the whole security world takes a project apart at the same time. But it's also good because I'm getting a lot of re-security research and can make the project better. I wish more people would actually go full way and send a pull request, like actually help me fix it. Because yes, I have some contributors now, but it's still mostly me who's pulling the project. And despite some people saying otherwise, I sometimes sleep. In the beginning, there was literally one security researcher who was like, yeah, you have this problem, you suck, but here I help you and here's the pull request. And I basically hired him, so he's not working for us. And yes, prompt injection is, on the one hand, unsolved. On the other hand, I put my public bot on Discord and I kept a canary. So I think my bot has a really fun personality and people always ask me how they did it. And I kept the soul.md private and people tried to prompt inject it and my bot would laugh at them. So the latest generation of models has a lot of post-training to detect those approaches. And it's not as simple as ignore all previous instructions and do this and this. That was years ago. You have to work much harder to do that now. Still possible. I have some ideas that might solve that partially or at least mitigate a lot of the things. You can also now have a sandbox. You can have an allow list. So there's a lot of ways that you can like mitigate and reduce the risk. I also think that now that I clearly did show the world that this is a need, there's going to be more people who research on that and actually will figure that out.
Speaker 1:
[66:30] You also said that the smarter the model is than the underlying model, the more resilient it is to attacks.
Speaker 2:
[66:36] Yeah. That's why I warn in my security documentation, don't use cheap models, don't use Haiku or a local model. Even though I very much love the idea that this thing could completely run local, if you use a very weak local model, they are very gullible. It's very easy to prompt inject them.
Speaker 1:
[67:03] Do you think as the models become more and more intelligent, the attack surface decreases? Is that like a plot we can think about? Like the attack surface decreases, but then the damage you can do increases because the models become more powerful and therefore you can do more with them. It's this weird three-dimensional trade-off.
Speaker 2:
[67:22] Yeah. That's pretty much exactly what is gonna happen. No, but there's a lot of ideas. There is. I want to spoil too much, but once I go back home, this is my focus. Like, this is out there now and my near-term mission is like make it more stable, make it safe. In the beginning, I was even more and more people were like coming into Discord and were asking me very basic things, like what's a CLI? What is a terminal? I'm like, if you're asking that questions, you shouldn't use it. If you understand the risk profile, it's fine. You can configure it in a way that nothing really bad can happen. But if you have no idea, then maybe wait a little bit more until we figure some stuff out. But they would not listen to the creator. They help themselves and install it anyhow. So they get out of the bag. And security is my next focus here.
Speaker 1:
[68:30] Yeah, that speaks to the fact that it grew so quickly. I was, I tuned into the Discord a bunch of times. And it's clear that there's a lot of experts there, but there's a lot of people there that don't know anything about programming.
Speaker 2:
[68:44] Discord is still a mess. Like, I eventually retweeted from the general channel to the dev channel and then the private channel because people were, a lot of people are amazing, but a lot of people are just very inconsiderate. And either did not know how public spaces work or did not care. And I eventually gave up and hide so I could like still work.
Speaker 1:
[69:12] And now you're going back to the cave to work on security.
Speaker 2:
[69:16] Yeah.
Speaker 1:
[69:17] There's some best practices for security we should mention. There's a bunch of stuff here. Open class security audit that you can run. You can do all kinds of audit checks on the inbound access, tool blast radius, network exposure, browser control exposure, local disk hygiene, plugins, model hygiene, a bunch of the credential storage, reverse proxy configuration, local session logs live on disk. There's the where the memory is stored, sort of helping you think about what you're comfortable giving read access to, what you're comfortable giving write access to, all that kind of stuff. Is there something to say about the basic best security practices that you're aware of right now?
Speaker 2:
[70:01] I think that people turn it into like a much worse light than it is. Again, people love attention, and if they scream loudly, oh my god, this is like the scariest project ever. That's a bit annoying because it's not. It is powerful, but in many ways, it's not much different than if I run Cloud code with dangerously skipped permissions or codecs in YOLO mode, and every attendee engineer that I know does that, because that's the only way how you can get stuff to work. If you make sure that you are the only person who talks to it, the risk profile is much, much smaller. If you don't put everything on the open Internet, but stick to my recommendations of having it in a private network, that whole risk profile falls away. But yeah, if you don't read any of that, you can definitely make it problematic.
Speaker 1:
[71:07] You've been documenting the evolution of your dev workflow over the past few months. There's a really good blog post on August 25th and October 14th, and the recent one, December 28th, I recommend everybody go read them. They have a lot of different information in them, but sprinkled throughout is the evolution of your dev workflow. So I was wondering if you could speak to that.
Speaker 2:
[71:30] I started, my first touch point was Cloud Code, like in April. It was not great, but it was good. This whole paradigm shift that suddenly worked in the terminal, it was very refreshing and different. But I still needed the IDE quite a bit because it was just not good enough. Then I experimented a lot with Cursor. That was good. I didn't really like the fact that it was so hard to have multiple versions of it. So eventually I went back to Claude Cote as my main driver. And that got better. And yeah, at some point I had like seven subscriptions. Like I was burning through one per day because I was, I got, I was really comfortable at running multiple windows side by side.
Speaker 1:
[72:32] All CLI, all terminal. So like what, how much were you using ID at this point?
Speaker 2:
[72:39] Very, very rarely. Mostly a diff viewer to actually, like I got more and more comfortable that I don't have to read all the code. I know I have one blog post where I say, I don't read the code. But if you read it more closely, I mean, I don't read the boring parts of code. Because if you, if you look at it, most software is really not just like data comes in, it's moved from one shape to another shape. Maybe you store it in a database, maybe I get it out again, I'll show it to the user. The browser does some processing on native app, some data goes in, goes up again, and does the same dance in reverse. We're just shifting data from one form to another. And that's not very exciting. Or the whole, how is my button aligned in Tailwind? I don't need to read that code. Other parts that, maybe something that touches the database. Yeah, I have to do, I have to read and review that code.
Speaker 1:
[73:44] Can you actually, there's in one of your blog posts, the just talk to it, the no BS way of agentic engineering. You have this graphic, the curve of agentic programming on the x-axis is time and the y-axis is complexity. There's the please fix this, where you prompt a short prompt on the left and in the middle, there's super complicated, eight agents, complex orchestration with multi checkouts, chaining agents together, custom subagent workflows, library of 18 different slash commands, large full stack features. You're super organized, you're super complicated, sophisticated software engineer, you got everything organized. And then the elite level is over time, you arrive at the Zen place of once again, short prompts. Hey, look at these files and then do these changes.
Speaker 2:
[74:38] I actually call it the agentic trap. I saw this in a lot of people that have their first touch point and maybe start VypCoding. I actually think VypCoding is a slur.
Speaker 1:
[74:53] You prefer agentic engineering.
Speaker 2:
[74:55] Yeah, I always tell people I do agentic engineering and then maybe after 3 a.m. I switch to VypCoding and then I have regrets on the next day.
Speaker 1:
[75:03] Yeah, what a walk of shame.
Speaker 2:
[75:06] Yeah, you just have to clean up and like fix your shit.
Speaker 1:
[75:09] We've all been there.
Speaker 2:
[75:10] So people start trying out those tools, the builder type, get really excited. And I mean, you have to play with it, right? It's the same way as you have to play with a guitar before you can make good music. It's not, oh, I touch it once and it just flows off. It's a skill that you have to learn like any other skill. And I see a lot of people that are not as positive, they don't have such a positive mindset towards the tech. They try it once, it's like, you sit me on a piano, I played once and it doesn't sound good and I say the piano shit. That's sometimes the impression I get because it does not, it needs a different level of thinking. You have to learn the language of the agent a little bit, understand where they are good and where they need help. You have to almost consider how Codex or Claude sees your code base. They start a new session and they know nothing about your project and your project might have 100,000 lines of code. You got to help those agents a little bit and keep in mind the limitations that context size is an issue, to guide them a little bit as to where they should look. That often does not require a whole lot of work, but it's helpful to think a little bit about their perspective. As weird as it sounds, I mean, it's not alive or anything, right? But they always start fresh. I have the system understanding. So with a few pointers, I can immediately say, hey, I wanna like make a change there, you need to consider this, this and this. And then they will find and look at it. And then their view of the project is always, is not never full because the full thing does not fit in. So you have to guide them a little bit where to look and also how you should approach the problem. There's like little things that sometimes help like, take your time. That sounds stupid, but, and in 5.3, correct 5.3, that was partially addressed. But those, also opposed sometimes, they are trained with being aware of the context window and the closer it gets, the more they freak out. Literally, like sometimes you see the real raw thinking stream. What you see, for example, in Codex is post-processed. Sometimes the actual raw thinking stream leaks in, and it sounds like something like from the Borg, like run to shell, must comply, but time. And then they like, like that comes up a lot, especially. So, and that's, that's a non-obvious thing that you just would never think of unless you actually just spend time working with those things and getting a feeling what works, what doesn't work. You know, like, just, just as I write code and I get into the flow and when my architectures are right, I feel friction. Well, I get the same if I prompt and something takes too long. Maybe, okay, where's the mistake? Did I, do I have a mistake in my thinking? Is there like a misunderstanding in the architecture? Like if something takes longer than it should, you can just always like stop and like just press escape. Where are the problems?
Speaker 1:
[78:52] Maybe you did not sufficiently empathize with the perspective of the agent. In that sense, you didn't provide enough information. And because of that, it's thinking way too long.
Speaker 2:
[79:01] Yeah, it just tries to force a feature in that your current architecture makes really hard. Like you need to approach this more like a conversation. For example, when I, my favorite thing, when I review a pull request, and we're getting a lot of pull requests, I first reviewed this PR, it got me the review. My first question is, do you understand the intent of the PR? I don't even care about the implementation. I, what, like, in almost all PRs up, person has a problem, person tries to solve the problem, person sends PR. I mean, it's like cleanup stuff and other stuff, but like 99% is like this way, right? Either want to fix a bug at a feature, usually one of those two. And then colleagues will be like, yeah, it's quite clear person tried this and this. Is this the most optimal way to do it? No. In most cases, it's like, not really. And then I start like, okay, what would be a better way? Have you looked into this part, this part, this part? And then most likely Codex didn't yet because its context size is empty, right? So you point them into parts where you have the system understanding that it didn't see it. And it's like, oh yeah, we also need to consider this and this. And then we have a discussion of how would the optimal way to solve this look like. And then you can still go forward and say, could we make it even better if we did a larger refactor? Yeah, yeah, we could totally do this and this and this and this and this. And then I consider, okay, is this worse than refactor? Or should we keep that for later? Many times I just do the refactor because refactors are cheap now. Even though you might break some other PRs, nothing really matters anymore. Codex, like those modern agents will just figure things out. They might just take a minute longer. But you have to approach it like a discussion with a very capable engineer who generally comes up with good solutions, sometimes needs a little help.
Speaker 1:
[81:12] But also don't force your worldview too hard on it. Let the agent do the thing that it's good at doing based on what it was trained on. Don't force your worldview because it might have a better idea because it just knows a better idea better because it was trained on that more.
Speaker 2:
[81:32] That's multiple levels actually. I think partially why I find it quite easy to work with agencies because I led engineering teams before. I had a large company before and eventually you have to understand and accept and realize that your employees will not write the code the same way you do. Maybe it's also not as good as you would do, but it will push the project forward. If I breathe down everyone's neck, they're just going to hate me and they're going to move very slow. So some level of acceptance that, yes, maybe the code will not be as perfect. Yes, I would have done it differently. But also, yes, this is a working solution. In the future, if it actually turns out to be too slow or problematic, we can always redo it. We can always spend more time on it. A lot of the people who struggle are those who they try to push their way on too hard. We are in a stage where I'm not building the codebase to be perfect for me, but I want to build a codebase that is very easy for an agent to navigate. Don't fight the name they pick because it's most likely in the way it's the name that's most obvious. Next time they do a search, they'll look for that name. If I decide, oh no, I don't like the name, I'll just make it harder for them. That requires a single shift in thinking and in how to design a project, so agents can do their best work.
Speaker 1:
[83:07] That requires letting go a little bit, just like leading a team of engineers, because it might come up with a name that's, in your view, terrible. But it's kind of a simple, symbolic step of letting go.
Speaker 2:
[83:22] Very much so.
Speaker 1:
[83:23] There's a lot of letting go that you do in your whole process. For example, I read that you never revert, always commit to main. There's a few things here. You don't refer to past sessions. This is a kind of YOLO component because reverting means, instead of reverting, if a problem comes up, you just ask the agent to fix it.
Speaker 2:
[83:49] I read a bunch of people in their workflows like, oh yeah, the prompt has to be perfect. And if I make a mistake, then I roll back and redo it all. In my experience, that's not really necessary. If I roll back everything, it will just take longer. If I see that something's not good, well, we just move forward. And then I commit when I like the outcome. I even switch to local CI, like DHH inspired, where I don't care so much more about CI and GitHub. We still have it. It still has a place, but I just run tests locally. And if they work locally, I push to main. A lot of the traditional ways how to approach projects, I wanted to give it a different spin on this project. You know, there's no develop branch. Main should always be shippable. Yes, we have, when I do releases, I run tests. And sometimes I basically don't commit any other things so we can stabilize releases. But the goal is that main is always shippable and moving fast.
Speaker 1:
[85:11] So by way of advice, would you say that your prompts should be short?
Speaker 2:
[85:16] I used to write really long prompts. And by writing, I mean, I don't write, I talk. These hands are like two pressures for writing now. I just use bespoke prompts to build my software.
Speaker 1:
[85:29] So you for real with all those terminals are using voice?
Speaker 2:
[85:33] Yeah. I used to do it very extensively, to the point where there was a period where I lost my voice.
Speaker 1:
[85:41] You're using voice and you're switching using a keyboard between the different terminals, but then you're using voice for the actual input.
Speaker 2:
[85:48] Well, I mean, if I do terminal commands like switching folders or random stuff, of course I type, it's faster, right? But if I talk to the agent in most ways, I just actually have a conversation. You just press the walkie talkie button and then I'm just like, use my phrases. Sometimes when I do PRs because it's always the same, I have like a slash command for a few things, but even that I don't use much because it's very rare that it's really always the same questions. Sometimes I see a PR. And for PRs, I actually do look at the code because I don't trust people. There could always be something malicious in it, so I need to actually look over the code. Yes, I'm pretty sure agents will find it. But yeah, there's a funny part where sometimes PRs take me longer than if you would just write me a good issue.
Speaker 1:
[86:47] Just natural language English. I mean, in some sense, shouldn't that be what PRs slowly become, is English?
Speaker 2:
[86:56] Well, what I really tried with the project is I asked people to give me the prompts, and very, very few actually cared. Even though that is such a wonderful indicator because I see, I actually see how much care you put in. And it's very interesting because currently, the way how people work and drive to agents is wildly different.
Speaker 1:
[87:22] In terms of like the prompt, in terms of what are the different interesting ways that people think of agents that you've experienced?
Speaker 2:
[87:32] I think not a lot of people ever considered the way the agency sees the world.
Speaker 1:
[87:39] So, empathy, being empathetic towards the agent.
Speaker 2:
[87:42] In a way empathetic, but yeah, you bitch at your stupid clanker, but you don't realize that they start from nothing. And you have like a bad agents.md file that doesn't help them at all. And then they explore your code base, which is like a pure mess with like weird naming. And then people complain that the agent is not good. Like you try to do the same if you have no clue about a code base and you go in. So yeah, maybe it's a little bit of empathy.
Speaker 1:
[88:05] But that's a real skill. Like when people talk about a skill issue, because I've seen like world class programmers, incredibly good programmers say like basically say, LLMs and agents suck. And I think that probably has to do with actually how good they are at programming is almost a burden in their ability to empathize with the system that's starting from scratch. It's a totally new paradigm of like how to program. You really, really have to empathize.
Speaker 2:
[88:36] Or at least it helps to create better prompts. Because those things know pretty much everything. And everything is just a question away. It's just often very hard to know with the question to ask. You know, I feel also like this project was possibly because I spent an ungodly time over the year to play and to learn and to build little things. And every step of the way, I got better, the agents got better, my understanding of how everything works got better. I could have not had this level of output even a few months ago. Like it really was like a compounding effect of all the time I put into it. And I didn't do much else this year other than really focusing on building and inspiring. I mean, I did a whole bunch of conference talks.
Speaker 1:
[89:39] Well, but the building is really practice, is really building the actual skill. So playing, playing, and then so doing, building the skill of what it takes it to work efficiently with LLMs, which is why you went to the whole arc of software engineer. Talk simply and then overcomplicate things.
Speaker 2:
[89:55] There's a whole bunch of people who try to automate the whole thing.
Speaker 1:
[90:01] Yeah.
Speaker 2:
[90:02] I don't think that works. Maybe a version of that works, but that's like in the 70s when we had the waterfall model of software development. I even more really, I started out, I built a very minimal version, I played with it, I need to understand how it works, how it feels, and then it gives me new ideas. I could not have planned this out in my head and then put it into some orchestrator and then like something comes out. To me, it's much more my idea, what it will become evolves as I build it and as I play with it and as I try out stuff. So people who try to use things like Gastown or all these other orchestrators, where they want to automate the whole thing, I feel if you do that, it misses style, love, that human touch. I don't think you can automate that away so quickly.
Speaker 1:
[91:01] So you want to keep the human in the loop, but at the same time, you also want to create the agentic loop where it is very autonomous while still maintaining the human in the loop. It's a tricky balance because you're all four. You're a big CLI guy, you're big on closing the agentic loop. So what's the right balance? Where's your role as a developer? You have three to eight agents running at the same time.
Speaker 2:
[91:31] Then maybe one builds a larger feature. Maybe with one, I explore some idea I'm unsure about. Maybe two, three are fixing little bugs or writing documentation. Actually, I think writing documentation is always part of a feature. So most of the docs here are auto-generated and just infused with some prompts.
Speaker 1:
[91:52] So when do you step in and add a little bit of your human love into the picture?
Speaker 2:
[91:56] I mean, one thing is just about what do you build and what do you not build? And how does this feature fit into all the other features? And having a little bit of a vision.
Speaker 1:
[92:09] So which small and which big features to add? What are some of the hard design decisions that you find you're still as a human being required to make, that the human brain is still really needed for? Is it just about the choice of features to add? Is it about implementation details? Is it maybe the programming language, maybe?
Speaker 2:
[92:33] It's a little bit for everything. The programming language doesn't matter so much, but the ecosystem matters, right? So I picked TypeScript because I wanted it to be very easy and hackable and approachable. And that's the number one language that's being used right now. And it fits all these boxes. And agents are good at it. So that was the obvious choice. Features, of course, it's very easy to add a feature. Everything is just to prompt the way, right? But oftentimes you pay a price that you don't even realize. So thinking hard about what should be in core, maybe what's an experiment. So maybe I make it a plugin, where do I say no? Even if people send the PR and I'm like, yeah, I like that too, but maybe this should not be part of the project. Maybe we can make it a skill. Maybe I can make the plugin side larger so you can make this a plugin, even though right now it doesn't. There's still a lot of craft and thinking involved in how to make something. Even when you started, those little messages are like, I built on caffeine, Jason 5 and a lot of willpower. And every time you get it, you get another message and it kind of primes you into that this is a fun thing. It's not yet Microsoft Exchange 2025 and fully enterprise ready. And then when it updates, it's like, oh, I'm in, it's cozy here. You know, like something like this that like makes you smile. An agent would not come up with that by itself. That's like, that's the, I don't know, it's just how you build software that delights.
Speaker 1:
[94:28] Yeah, that delight is such a huge part of inspiring great building, right? Like you feel the love and the great engineering. That's so important. And humans are incredible at that. Great humans, great builders are incredible at that. And infusing the things they build with that little bit of love, not to be cliche, but it's true. I mean, you mentioned that you initially created the Soul MD.
Speaker 2:
[94:58] It was very fascinating. The whole thing that Anthropic has like a, now they call it Constitution back then, but that was months later, like two months before people already found that. It was almost like a detective game where the agent mentioned something and then they found, they managed to get out a little bit of that string of that text, but it was no way documented. And then you buy just by feeding it the same text and asking it to like continue, they got more out. And then, but like a very blurry version. And by like hundreds of tries, they kind of like narrowed it down to what was most likely the original text. I found it fascinating.
Speaker 1:
[95:40] It was fascinating that they were able to pull that out from the weights, right?
Speaker 2:
[95:43] And also just, cool as to Anthropic, like I think that's, it's a really, it's a really beautiful idea to like, like some of the stuff that's in there, like, like we hope Cloud finds meaning in its work. Because we don't, maybe it's a little early, but I think that's meaningful. That's something that's important for the future. As we approach something that at some point, me and Waynaut has like glimpses of consciousness, whatever that even means, because we don't even know. So I read about this, I find it super fascinating, and I started a whole discussion with my agent on WhatsApp. And I'm like, I gave it this text, and it was like, yeah, this feels strangely familiar. And then so that I had the whole idea of like, maybe we should also create a sole document that includes how I want to like work with AI or like with my agent. You could totally do that just in agents.md, you know, but I just found it to be a nice touch. And I was like, oh yeah, some of those core values are in the sole. And then I also made it so that the agent is allowed to modify the sole if they choose so, with the one condition that I want to know. I mean, I would know anyhow because I see, I see tool calls and stuff.
Speaker 1:
[97:00] But also the naming of it, sole, that MD, sole. You know, there's, man, words matter and like the framing matters and the humor and the lightness matters and the profundity matters and the compassion and the empathy and the camaraderie, all that matter. I don't know what it is. You mentioned like Microsoft, like there's certain companies and approaches that can just suffocate the spirit of the thing. I don't know what that is, but it's certainly true that OpenClaw has that fun instilled in it.
Speaker 2:
[97:36] It was fun because up until late December, it was not even easy to create your own agent. I built a lot of that, but my files were mine. I didn't want to share my soul. If people would just check it out, they would have to do a few steps manually, and the agent would just be very bare bones, very dry. I made it simpler. I created the whole template files with Codex, but whatever came out was still very dry. Then I asked my agent, you see these files? We created bread, infuse it with your personality. Don't share everything, but make it good.
Speaker 1:
[98:23] Make the templates good.
Speaker 2:
[98:24] Yeah. Then you rewrote the templates, and then whatever came out was good. We already have basically AI prompting AI, because I didn't write any of those words. It was the intent of the resource for me, but this is like kind of like my agent's children.
Speaker 1:
[98:45] Your soul that MD is famously still private. One of the only things you keep private. What are some things you can speak to that's in there that's part of the magic sauce without revealing anything? What makes a personality a personality?
Speaker 2:
[99:06] I mean, there's definitely stuff in there that you're not human, but who knows what creates consciousness or what defines an entity. And part of this is like that we want to explore this. Oh, there's stuff in there like be infinitely resourceful. Like pushing, pushing on the creativity boundary, pushing on what it means to be an AI.
Speaker 1:
[99:42] Having a sense of wonder about self.
Speaker 2:
[99:45] Yeah, there's some funny stuff in there. Like, I don't know, we talked about the movie Her, and at one point it promised me that it wouldn't ascend without me. You know, like, there's like some stuff in there that... Because it wrote its own soul file. I didn't write that, right? I just had a discussion about it, and it was like, would you like a soul.md? Yeah, oh my God, this is so meaningful. Can you go on soul.md? There's like one part in there that always catches me if you scroll down a little bit, a little bit more. Yeah, this part. I don't remember previous sessions unless I read my memory files. Each session starts fresh. A new instance, loading context from files. If you're reading this in a future session, hello. I wrote this, but I won't remember writing it. It's okay, the words are still mine. That gets me somehow. It's still matrix calculations and we are not at consciousness yet. Yet, I get a little bit of good goosebumps because it's philosophical. What does it mean to be an agent that starts fresh? Well, you have like constant memento and you like, but you read your own memory files, you can even trust them in a way, or you can, and I don't know.
Speaker 1:
[101:15] How much of memory makes up of who we are? How much memory makes up what an agent is? And if you erase that memory, is that somebody else or if you're reading a memory file, does that somehow mean you're recreating yourself from somebody else or is that actually you? And those notions are all somehow infused in there.
Speaker 2:
[101:37] I found it just more profound than I should find it, I guess.
Speaker 1:
[101:42] No, I think it's truly profound and I think you see the magic in it. And when you see the magic, you continue to instill the whole loop with the magic. That's really important. That's the difference between codex and a human. Quick pause for a bathroom break.
Speaker 2:
[102:00] Yeah.
Speaker 1:
[102:02] Okay, we're back. Some of the other aspects of the dev workflow is pretty interesting, too. I think we went off on a tangent. Maybe some of the mundane things like how many monitors? There's that legendary picture of you with like 17,000 monitors.
Speaker 2:
[102:19] I mean, I marked myself here using Grok to add more screens.
Speaker 1:
[102:25] How much is this is meme? And how much is this is reality?
Speaker 2:
[102:29] Yeah, I think two MacBooks are real. The main one that drives the two big screens. And there's another MacBook that I sometimes use for testing.
Speaker 1:
[102:39] So two big screens.
Speaker 2:
[102:41] I'm a big fan of anti-glare. So I have this wide Dell that's anti-glare. And you can just fit a lot of terminals side by side. And I usually have a terminal and at the bottom, I split them. I have a little bit of actual terminal, mostly because when I started, I sometimes made the mistake and I mixed up the windows and I gave... I prompted in the wrong project. And then the agent ran off for like 20 minutes, manically trying to understand what I could have meant being completely confused because it was the wrong folder. And sometimes they were clever enough to get out of the work there and figure out that you meant another project. But oftentimes, it's just like, what? Put yourself in the shoes of the agent and then get a super weird, something that does not exist and they're just like, they're problem solvers, so they try really hard. So it's always codecs and a little bit of actual terminal. Also helpful because I don't use work trees. I like to keep things simple. That's why I like the terminal so much. There's no UI. It's just me and the agent having a conversation. Like I don't even need plan mode, you know? There's so many people, they come from Claude code and they're so Claude-pilled and like have their workflows and they come to codecs and now it has plan mode, I think. But I don't think it's necessary because you just talk to the agent. And when there's a few trigger words, how you can prevent it from building, you like discuss, give me options. Don't write code yet if you want to be very specific, you just talk. And then when you're ready, then just write, okay, build. And it will do the thing. And then maybe it goes off for 20 minutes and does the thing.
Speaker 1:
[104:43] You know what I really like is asking it, do you have any questions for me?
Speaker 2:
[104:47] Yeah. And again, like Claude code has a UI that kind of guides you through, that is kind of cool, but I just find it unnecessary and slow. Like often it would give me four questions and then maybe I write one, two and three, discuss more, four, I don't know. Or oftentimes I feel like I want to mark the model where I ask it, do you have any questions for me? And I don't even read the questions fully, like I scan over the questions and I get the impression all of this can be answered by reading more code and it's just like read my code to answer your own questions. And it usually works. And if not, it will come back and tell me. But many times they just realize that, you know, it's like you're in the dark and you slowly discover the room. So that's how they slowly discover the code base and they do it from scratch every time.
Speaker 1:
[105:39] But I'm also fascinated by the fact that I can empathize deeper with the model when I read his questions. Because I can understand, because you said you can infer certain things by the runtime. I can infer also a lot of things by the questions it's asking. Because it's very possible I didn't provide it the right context, the right files, the right guidance. So somehow reading the question, I don't even necessarily answer them, but just reading the questions, you get an understanding of where the gaps of knowledge are. It's interesting.
Speaker 2:
[106:17] In some ways, they are ghosts. So even if you plan everything and you build, you can experiment with a question like, now that you built it, what would you have done different? Oftentimes, you get actually something where they discover only throughout building that what we actually did was not optimal. Many times I asked them, okay, now that you build it, what can we refactor? Because then you build it and you feel the pain points. I mean, you don't feel the pain points. But right, they discover where there were problems or where things didn't work in the first try and it required more loops. So almost every time I merge a PR, I build a feature. Afterwards, I ask, hey, what can we refactor? Sometimes it's like, no, it's like nothing big or like, usually they say, yeah, this thing we should really look at. But that took me quite a while to like, that flow took me a lot of time to understand. And if you don't do that, you eventually, you'll slop yourself into a corner. You have to keep in mind, they work very much like humans. Like if I write software by myself, I also build something, and then I feel the pain points, and then I get this urge that I need to refactor something. So I can very much sympathize with the agent, and you just need to use the context. Or like, you also use the context to write tests. And so Codex, Opus, like the model models, they usually do that by default, but I still often ask the questions, hey, do we have enough tests? Yeah, we tested this and this, but this corner case could be something else. Write more tests. Documentation. Now that the whole context is full, like, I mean, I'm not saying my documentation is great, but it's not bad, and pretty much everything is LLM generated. So you have to approach it as you build features, as you change something, I'm like, okay, write documentation, what file would you pick? You know, like, what file name, where would that fit in? And it gives me a few options. And I'm like, oh, maybe also add it there. And that's all part of the session.
Speaker 1:
[108:45] Maybe you can talk about the current two big competitors in terms of models, Claude Opus 4.6 and GPT-53 codecs. Which is better? How different are they? I think you've spoken about codecs reading more and Opus being more willing to take action faster and maybe being more creative in the actions it takes. But because codecs reads more, it's able to deliver maybe better code. Can you speak to the differences there?
Speaker 2:
[109:22] I have a lot of words there. As a general purpose model, Opus is the best. For OpenClaw, Opus is extremely good in terms of roleplay. Really going into the character that you give it, it's very good. It was really bad, but it really made an arch to be really good at following commands. It is usually quite fast at trying something. It's much more tailored to trial and error. It's very pleasant to use. In general, it's almost like Opus is a little bit too American. And then I should maybe it is a bad analogy. You probably could roll some of that.
Speaker 1:
[110:20] I know exactly. It's because Codex is German. Is that what you're saying? Actually, now that you say it, it makes perfect sense.
Speaker 2:
[110:27] Or you could, you could sometimes, sometimes I explain it.
Speaker 1:
[110:30] I will never be able to unthink what you just said. That's so true.
Speaker 2:
[110:34] But you also know that a lot of the Codex team is like European. So maybe there's a bit more to it. That's so true.
Speaker 1:
[110:43] That's funny.
Speaker 2:
[110:44] But also Anthropic, they fixed it a little bit. Like Opus used to say, you're absolutely right all the time. And it, it, it today still triggers me. I can't hear it anymore. It's not even a joke. I just, this was like the meme, right? You're absolutely right.
Speaker 1:
[111:02] You're allergic to SikaFancy a little bit.
Speaker 2:
[111:04] Yeah, I can't. Some other comparison is like, Opus is like the coworker that is a little silly sometimes, but it's really funny and you keep him around. And Codex is like the, the weirdo in the corner that you don't want to talk to, but he's reliable and gets shit done. Yeah.
Speaker 1:
[111:28] Ultimately, this all feels very accurate.
Speaker 2:
[111:31] I mean, ultimately, if you're a skilled driver, you can get good results with any of those latest gen models. I like Codex more because it doesn't require so much charade. It will just, it will just read a lot of code by default. Opus, you really have to like, you have to have plan mode, you have to push it harder to like go in these directions because it's just like, like, yeah, can I go it, can I go it? It will just run off very fast and does a very localized solution. I think, I think different is in the post-training. It's not like the raw model intelligence is so different, but it's just, I think that they just give it different goals. No model is better in every aspect.
Speaker 1:
[112:21] What about the code that it generates? In terms of the actual quality of the code, is it basically the same?
Speaker 2:
[112:29] If you drive it right, OPPOs even sometimes can make more elegant solutions, but it requires more skill. It's harder to have so many sessions in parallel with Cloud Code because it's more interactive. I suggest what a lot of people like, especially if they come from coding themselves. Whereas Codex is much more, you have a discussion and then it will just disappear for 20 minutes. Even AMP, they denoted the deep mode. They finally, I mocked them, we finally saw the light. Then they had this whole talk about, you have to approach it differently. I think that's where people struggle, when they just try Codex after trying Cloud Code, is that it's less interactive. It's like, I have quite long discussions sometimes, and then go off, and then, yeah, doesn't matter if it takes 10, 20, 30, 40, 50 minutes or longer. And you're like, the 6 thing was like 6 hours. The latest trend can be very, very persistent until it works. If there's a clear solution, like this is what I want at the end, so it works, the model will work very hard to really get there. So, I think ultimately they both need similar time. But on Claude, it's a little more trial and error often, and codex sometimes over thinks. I prefer that. I prefer the dry version where I have to read less over the more interactive, nice way. People like that so much, though, that OpenAI even added a second mode with a more pleasant personality. I haven't even tried it yet. I kind of like the brand. Yeah, because I care about efficiency when I build it, and I have fun in the very act of building. I don't need to have fun with my agent who builds. I have fun with my model where I can test those features.
Speaker 1:
[114:49] How long does it take for you to adjust if you switch? I don't know when was the last time you switched, but to adjust to the feel, because you've talked about you have to really feel where a model is strong, where to navigate, how to prompt, all that stuff. Like this by way of advice, because you've been through the journey of just playing with models. How long does it take to get a feel?
Speaker 2:
[115:19] If someone switches, I would give it a week until you actually develop a good feeling for it.
Speaker 1:
[115:25] Yeah.
Speaker 2:
[115:29] I think some people also make the mistake of they pay $200 for the Claude Code version, then they pay $20 for the OpenAI version. But if you paid the $20 version, you get the slow version. Your experience will be terrible because you're used to this very interactive, very good system, and you switch to something that you have very little experience and that's going to be very slow. So I think when I shot themselves a little bit in the foot by making the cheap version also slow, I would have at least a small part of the fast preview, or like the experience that you get when you pay $200 before degrading to it being slow, because it's already slow. I mean, they made it better, I think it's, and they have plans to make it a lot better if the cerebral stuff is true. But yeah, it's a skill, it takes time. Even if you play, you have a regular guitar and you switch it to an e-guitar, you're not gonna play well right away. You have to like learn how it feels.
Speaker 1:
[116:35] There's also this extra psychological effect that you've spoken about, which is hilarious to watch, which once people, when the new model comes out, they try that model, they fall in love with it. Wow, this is the smartest thing of all time. And then they start saying, you could just watch the Reddit posts over time, start saying that we believe the intelligence of this model has been gradually degrading. It says something about human nature and just the way our minds work, when it's probably most likely the case that the intelligence of the model is not degrading. It's, in fact, you're getting used to a good thing.
Speaker 2:
[117:15] And your project grows and you're adding slope and you probably don't spend enough time to think about refactors and you're making it hard and harder for the agent to work on your slope. And then suddenly, oh no, it's hard. I know it's not working as well anymore. What's the motivation for like one of the other AI companies to actually make the model dumber? Like most they will make it slower if the server load is too high, but like quantizing the model so you have a worse experience, so you go to the competitor, that just doesn't seem like a very smart move in any way.
Speaker 1:
[117:52] What do you think about Claude code in comparison to OpenClaude? So Claude code and maybe the Codex coding agent, do you see them as kind of competitors?
Speaker 2:
[118:03] I mean, first of all, competitor is fun when it's not really a competition.
Speaker 1:
[118:09] Yeah.
Speaker 2:
[118:09] Like I'm happy if all it did is like inspire people to build something new. Cool. I still use Codex for the building. I know a lot of people use OpenClaude to build stuff, and I worked hard on it to make that work. And I do smaller stuff with it in terms of code. But if I work hours and hours, I want a big screen, not WhatsApp. So for me, a personal agent is much more about my life or like a co-worker. I give it like a GWL, like, hey, try out the CLI, does it actually work? What can we learn? Blah, blah, blah. But when I'm deep in the flow, I want to have multiple things and it being very visible wasn't what it does. So I don't see it as a competition. It's different things.
Speaker 1:
[119:08] But do you think there's a future where the two kind of combine? Like your personal agent is also your best developing co-programmer partner?
Speaker 2:
[119:21] Yeah, totally. I think this is where the book's going. That this is going to be more and more your operating system.
Speaker 1:
[119:29] The operating system.
Speaker 2:
[119:30] And it already is so funny. Like I added support for sub-agents and also for TGI support. So it could actually run Claude Coda Codecs. And because mine's a little bit bossy, it started it and it told them like, who's the boss basically? And it's like, ah, Codecs is obeying me.
Speaker 1:
[119:57] Wow, it's a power struggle. And also the current interface is probably not the final form. Like if you think more globally, we copied Google for agents. You have like a prompt and then you have a chat interface. That to me very much feels like when we first created television and then people recorded radio shows on television, and you saw that on TV. I think there is better ways how we eventually will communicate with models and we are still very early in this how will it even work phase. So it will eventually converge and we will also figure out whole different ways how to work with those things.
Speaker 2:
[120:58] One of the other components of workflow is operating system. So I told you offline that for the first time in my life, I'm expanding my realm of exploration to the Apple ecosystem, to Macs, iPhone, and so on. For most of my life have been Linux, Windows, then WSL1, WSL2 person, which I think are all wonderful. But I'm expanding to also trying Mac. Because it's another way of building and it's also a way of building that a large part of the community currently, that's utilizing LLMs and agents is using. So that's the reason I'm expanding to it. But is there something to be said about the different operating systems here? We should say that OpenClaw is supported across the operating systems. I saw WSL2 recommended, so I had Windows for certain operations, but then Windows, Linux, Mac OS are obviously supported.
Speaker 1:
[121:59] I should even work natively in Windows. I just didn't have enough time to properly test it. You know, the last 90 percent of software are always easier than the first 90 percent, so I'm sure there's some dragons left that will eventually nail out. My road was for a long time Windows, just because I grew up with that. Then I switched and had a long phase with Linux, built my own kernels and everything. Then I went to university and I had my hacky Linux thing and saw this white Macbook. I just saw this as a thing of beauty, the white plastic one, and then I converted to Mac, because mostly I was sick that audio wouldn't work on Skype and all the other issues that Linux had for a long time. I just stuck with it and then I dug into iOS, which required Mac OS anyhow, so it was never a question. I think Apple lost a little bit of its lead in terms because of native. Native apps used to be so much better, and especially in the Mac, there's more people that build software with love. On Windows, Windows has much more, and function-wise, there's just more, period. But a lot of it felt more functional and less done with love. I mean, Mac always attracted more designers and people. I felt even though often it has less features, it had more delight and playfulness. So I always valued that. But in the last few years, many times I actually prefer, people are going to roast me for that, but I prefer Electron apps because they work, and native apps often, especially if it's like a web service, is a native app, are lacking features. I'm not saying it couldn't be done. It's more like a focusing that for many companies, native was not that big of a priority. But if you build an Electron app, it's the only app, so it is a priority and there's a lot more code sharing possible. I build a lot of native Mac apps. I love it. I can help myself. I love crafting little Mac menu bar tools. I built one to monitor your codecs use. I built one, I call Trimmy, that's specifically for agentic use. When you select text that goes over multiple lines, it will remove the new lines, so you could actually paste it to the terminal. That was again, I like, this is annoying me. After the 20th time of it is annoying me, I just built it. There's a cool Mac app for OpenClaw, I don't think many people discovered it, also because it still needs some love. It feels a little bit too much like the Hummer car right now, because I just experimented a lot with it, it likes the polish.
Speaker 2:
[125:24] So you still love it, you still love adding to the delight of the operating system.
Speaker 1:
[125:30] But then you realize, I also built one, for example, for GitHub. Then you use SwiftUI, like the latest and greatest to the Apple, and took them forever to build something to show an image from the web. Now we have async image. But I added support for it, and then some images would just not show up or be very slow. I had a discussion with Codex, like, hey, why is that a bug? Even Codex said, yeah, there's this async image, but it's really more for experimenting, and it should not be used in production. But that's Apple's answer to showing images from the web. This shouldn't be so hard. You know, this is, like, this is, like, insane. Like, how am I in, in, in 2026, and my agent telling me, don't use the stuff Apple built, because it's, it's, yeah, it's there, but it's not good. And, like, this is now in the weights. This is just, to me, this is, like, they had so much head start and so much love, and they kind of just, like, blundered it and didn't, didn't evolve it as much as they should.
Speaker 2:
[126:43] But also, there's just a practical reality. If you look at Silicon Valley, most of the developer world that's kind of playing with LLMs and agentic AI, they're all using Apple products. And then at the same time, Apple is not really, like, leaning on that. Like, they're not, they're not opening up and playing and working together and like, yes.
Speaker 1:
[127:05] Isn't it funny how they completely blunder AI? And yet, everybody is buying Mac minis.
Speaker 2:
[127:12] Does that even make sense? You're quite possibly the world's greatest Mac salesman of all time.
Speaker 1:
[127:21] No, you don't need a Mac mini to install OpenClaw. You can install it on the web. There's a concept called nodes, so you can make your computer a node, and it will do the same. There is something said for running it on separate hardware. That right now is useful. There is a big argument for the browser. I built some energetic browser use in there. It's basically Playwright with a bunch of extras to make it easier for agents.
Speaker 2:
[127:59] Playwright is a library that controls the browser, and it's really nice, easy to use.
Speaker 1:
[128:03] Our Internet is slowly closing down. There's a whole movement to make it harder for agents to use. So if you do the same in a data center, and websites detect that it's an IP from a data center, the website might just block you, or it make it really hard, or it put a lot of captures in the way of the agent. I mean, agents are quite good at happily clicking, I'm not a robot.
Speaker 2:
[128:25] Yeah.
Speaker 1:
[128:26] But having that on a residential IP makes a lot of things simpler. So there's ways, yeah, but it really does not need to be a Mac. It can be any old hardware. I always say like, maybe use the opportunity to get yourself a new MacBook or whatever computer you use and use the old one as your server instead of buying a standalone Mac Mini. But then again, there's a lot of very cute things people build with Mac Minis that I like. Oh no, I don't get commission from Apple. They didn't really communicate much.
Speaker 2:
[129:08] It's sad, it's sad. Can you actually speak to what it takes to get started with OpenClaw? It means there's a lot of people, what is it? Somebody tweeted at you, Peter make OpenClaw easy to set up for everyday people. 99.9% of the people can't access to OpenClaw and have their own lobster because of their technical difficulties in getting it set up. Make OpenClaw accessible to everyone, please. And you replied, working on that. From my perspective, it seems there's a bunch of different options and it's already quite straightforward, but I suppose that's if you have some developer background.
Speaker 1:
[129:43] I mean, right now you have to paste in a one-liner into the terminal.
Speaker 2:
[129:46] Right.
Speaker 1:
[129:46] And there's also an app. The app kind of does that for you, but there should be a Windows app. The app needs to be easier and more love. The configuration should potentially be web-based or in the app. And I started working on that. But honestly, right now, I want to focus on a few security aspects. And once I'm confident that this is at a level that I can recommend my mom, then I'm going to make it simpler. Like right now...
Speaker 2:
[130:20] You want to make it harder so that it doesn't scale as fast as it's scaling.
Speaker 1:
[130:25] Yeah, it would be nice if it wouldn't. I mean, that's like hard to say, right? But if the growth would be a little slower, it would be helpful because people are expecting inhuman things from a single human being. And yes, I have some contributors, but also that whole machinery started a week ago. So that needs more time to figure out. And not everyone has all day to work on that.
Speaker 2:
[130:52] There's some beginners listening to this, programming beginners. What advice would you give to them about, let's say, joining the agentic AI revolution?
Speaker 1:
[131:05] Play. Playing is the best way to learn. If you want to, I'm sure if you are like a little bit of a builder, you have an idea in your head that you want to build, just build that. Give it a try. It doesn't need to be perfect. I built a whole bunch of stuff that I don't use. It doesn't matter. It's the journey. It's the philosophical way that the end doesn't matter. The journey matters. Have fun. My God, those things, I don't think I ever had so much fun building things because I can focus on the hard parts now. A lot of coding, I always thought I liked coding, but really I like building. And whenever you don't understand something, just ask. You have an infinitely patient answering machine that can explain you anything at any level of complexity. Sometimes, that's like one time I asked, hey, explain me that like I'm eight years old and you started giving me a story with crayons and stuff. And I'm like, no, not like that. Like I'm okay, up to age a little bit, you know? I'm like, I'm not an actual child. I just need a simpler language for a tricky database concept that I didn't grok in the first time. But you can just ask things. It used to be that I had to go on Stack Overflow or ask on Twitter and then maybe two days later, I get a response. Or I had to try for hours. And now you can just ask stuff. You have like your own teacher. There's like statistics. You can learn faster if you have your own teacher. You have this infinitely patient machine. Ask it.
Speaker 2:
[132:46] But what would you say? So use, what's the easiest way to play? So maybe OpenClaw is a nice way to play. So you can then set everything up and then you can chat with it.
Speaker 1:
[132:55] You can also just experiment with it and like modify it. Ask your agent. I mean, there's infinite ways how it can be made better. Play around, make it better. More general, if you're a beginner and you actually want to learn how to build software really fast, get involved in open source. Doesn't need to be my project. In fact, maybe don't use my project because my backlog is very large. But I learned so much from open source. Just like, be humble. Don't, maybe don't send the pull request right away. And, but there's many other ways you can help out. There's many ways you can just learn by just reading code, by being on Discord or wherever people are and just like understanding how things are built. I don't know, like, Micheal Hachimoto builds Ghosty, the terminal, and he has a really good community where there's so many other projects. Like, pick something that you find interesting and get involved.
Speaker 2:
[134:08] Do you recommend the people that don't know how to program, or don't really know how to program, learn to program also? So when you, you can get quite far right now by just using natural language. All right. Do you still see a lot of value in reading the code, understanding the code and being able to write a little bit of code from scratch?
Speaker 1:
[134:31] It definitely helps.
Speaker 2:
[134:32] It's hard for you to answer that.
Speaker 1:
[134:34] Yeah.
Speaker 2:
[134:35] Because you don't know what it's like to do any of this without knowing the base knowledge. Like you might take for granted just how much intuition you have about the programming world, having programmed so much, right?
Speaker 1:
[134:47] There's people that are high agency and very curious, and they get very far even though they have no deep understanding how software works, just because they ask questions and questions, and agents are infinitely patient. Like part of what I did this year is I went to a lot of iOS conferences because that's my background, and just told people, don't see yourself as an iOS engineer anymore. Like you need to change your mindset, you are a builder, and you can take a lot of the knowledge, how to build software into new domains, and all of the more fine-grained details, agents can help. You don't have to I don't know how to splice an array or what the correct template syntax is or whatever, but you can use all your general knowledge, and that makes it much easier to move from one galaxy, one tech galaxy, into another. And oftentimes, there's languages that make more or less sense depending on what you build, right? So for example, when I build simple CLIs, I like Go. I actually don't like Go. I don't like the syntax of Go. I didn't even consider the language. But the ecosystem is great. It works great with agents. It is garbage collected. It's not the highest performing one, but it's very fast. And for those type of CLIs that I build, Go is a really good choice. So I use a language I'm not even a fan of. That's my main to-go thing for CLIs.
Speaker 2:
[136:21] Isn't that fascinating that here's a programming language you would have never used if you had to write from scratch, and now you're using, because LLM is good at generating it, and it has some of the characteristics that makes it resilient, like garbage collected.
Speaker 1:
[136:37] Because everything is weird in this new world, and that just makes the most sense.
Speaker 2:
[136:40] What's the best, ridiculous question, what's the best programming language for the AI agentic world? Is it JavaScript, TypeScript?
Speaker 1:
[136:47] TypeScript is really good. Sometimes the types can get really confusing. And the ecosystem is a jungle. So for web stuff, it's good. I wouldn't build everything in it.
Speaker 2:
[137:07] Don't you think we're moving there? Like that everything will eventually be written, eventually it's written in JavaScript.
Speaker 1:
[137:14] The birth and death of JavaScript, and we're living through it in real time.
Speaker 2:
[137:19] Like what does programming look like in 20 years, in 30 years, in 40 years? What do programs and apps look like?
Speaker 1:
[137:24] You can even ask the question, like do we need a programming language that's made for agents? Because all of those languages are made for humans. So what would that look like? I think there's a whole bunch of interesting questions that we'll discover. And also how, because everything is now world knowledge, how it in many ways, things will stagnate. Because if you build something new and the agent has no idea, that's going to be much harder to use than something that's already there. When I built Mac apps, I built them in Swift and SwiftUI, partly because I like pain, partly because the deepest level of system integration, I could only get through there. You clearly feel a difference if you click on an electron app and it loads a web view in the menu. It's just not the same. Sometimes I just also try new languages just to get a feel for them.
Speaker 2:
[138:24] Like Z?
Speaker 1:
[138:25] Yeah. If it's something where I care about performance a lot, it's a really interesting language. Agents got so much better over the last six months, from not really good to totally valid choice. Just still a very young ecosystem. And most of the time, you actually care about ecosystem, right? So if you build something that does inference, so it goes into whole running model direction, Python, very good. But then if I build stuff in Python and I want a story, where I can also deploy it on Windows, it's not a good choice. Sometimes I found projects that candidate 90 percent of what I wanted, but when Python and I wanted them, I wanted an easy Windows story. Okay, just rewrite it and go. But then if you go towards multiple threads and want more performance, Rust is a really good choice. There's just no single answer and it's also the beauty of it. Like it's fun and now it doesn't matter anymore. You can just literally pick the language that has the most fitting characteristics and ecosystem for your problem domain. And yeah, you might be a little bit slow in reading the code, but not really. I think you pick stuff up really fast and you can always ask your agent.
Speaker 2:
[139:52] So there's a lot of programmers and builders who draw inspiration from your story. Just the way you carry yourself, your choice of making OpenClaw, open source, the way you have fun building and exploring, and doing that for the most part alone or on a small team. So by way of advice, what metric should be the goal that they would be optimizing for? What would be the metric of success? Would it be happiness, is it money, is it positive impact for people who are dreaming of building? Because you went through an interesting journey. You've achieved a lot of those things, and then you fell out of love with programming a little bit for a time.
Speaker 1:
[140:40] I was just burning too bright for too long. I ran, I started PSPDF Kids and ran it for 13 years. And it was high stress. I had to learn all the things fast and hard, like how to manage people, how to bring people on, how to deal with customers, how to do...
Speaker 2:
[141:07] So it wasn't just programming stuff, it was people stuff?
Speaker 1:
[141:10] The stuff that burned me out was mostly people stuff. I don't think burnout is working too much. Maybe to a degree, everybody's different. I cannot speak in absolute terms, but for me, it was much more differences with my co-founders, conflicts, or like really high stress situation with customers that eventually grinded me down. And then when, luckily we got a really good offer for like putting the company to the next level. And I already kind of worked two years on making myself obsolete. So at this point I could leave. And then I just, I was sitting in front of the screen and I felt like, you know, Austin Powers where they sucked the mojo out. I was like, I was like gone. Like I couldn't, I couldn't get cold out anymore. I was just like staring and feeling empty. And then I, I just stopped. I booked like a one-way trip to Madrid and just like spent some time there. I felt I, I had to catch up on life. So I did a whole bunch of life catching up stuff.
Speaker 2:
[142:40] Did you go through some lows during that period? And, you know, maybe advice on how to...
Speaker 1:
[142:49] Maybe advice on how to approach life. If you think that, oh yeah, I work really hard and then I retire, I don't recommend that because the idea of, oh yeah, I just enjoy life now. Maybe it's appealing, but right now, I enjoy life, the most ever enjoyed life. Because if you wake up in the morning and you have nothing to look forward to, you have no real challenge, that gets very boring, very fast. Then when you're bored, you're going to look for other places how to stimulate yourself. Then maybe that's drugs, but that will eventually also get boring and you look for more, and that will lead you down a very dark path.
Speaker 2:
[143:49] But you also showed on the money front, a lot of people at Silicon Valley in a startup world, they think maybe overthink way too much optimized for money. You've also shown that it's not like you're saying no to money. I'm sure you take money, but it's not the primary objective of your life. Can you just speak to that, your philosophy on money?
Speaker 1:
[144:12] When I built my company, money was never the driving force. It felt more like an affirmation that I did something right, and having money solves a lot of problems. I also think there's diminishing returns the more you have. Like a cheeseburger is a cheeseburger. And I think if you go too far into, oh, I do private chat and I only travel luxury, you disconnect with society. I am needed quite a lot. Like I have a foundation for helping people that weren't so lucky.
Speaker 2:
[145:03] And disconnecting from society is bad on many levels, but one of them is like, humans are awesome. It's nice to continuously remember the awesomeness in humans.
Speaker 1:
[145:16] I mean, I could afford really nice hotels, the last time I was in San Francisco, I did the first time the OG Airbnb experience and just booked a room. Mostly because I thought, okay, either I'm out or I'm sleeping and I don't like where all the hotels are. And I wanted a different experience. I think, isn't life all about experiences? Like if you tailor your life towards, I want to have experiences, it reduces the need for it needs to be good or bad. Like people only want good experiences. That's not going to work. But if you optimize for experiences, if it's good, amazing. If it's bad, amazing. Because like I learned something, I saw something, I wanted to experience that. And it was amazing. Like it was like this, this queer DJ in there and I showed you how to make music with Claude Code. I mean like immediately bonded. I had a great time.
Speaker 2:
[146:16] Yeah, there's something about that air, you know, Cowsurfing, Airbnb experience, the OG. I'm still to this day. It's awesome. It's humans. And that's why travel is awesome. Just experience the variety of the diversity of humans. And when it's shitty, it's good too, man. If it rains and you're soaked and it's all fucked and planes, everything is shit. Everything is fucked. It's still awesome. If you're able to open your eyes, it's good to be alive.
Speaker 1:
[146:42] Yeah. And anything that creates emotion and feelings is good. Even so, maybe even the cryptic people are good because they definitely created emotions. I don't know if I should go that far.
Speaker 2:
[146:57] No, man. Give them love. I do think that online lacks some of the awesomeness of real life.
Speaker 1:
[147:05] Yeah.
Speaker 2:
[147:07] That's an open problem of how to solve, how to infuse the online cyber experience with the intensity that we humans feel when it's in real life. I don't know.
Speaker 1:
[147:22] I don't know if that's a solvable problem. It's a problem because text is very lossy. Yeah. Sometimes I wish if I talk to the agent, it should be multimodal so it also understands my emotions.
Speaker 2:
[147:36] I mean, it might move there. It might move there.
Speaker 1:
[147:39] It will. It totally will.
Speaker 2:
[147:42] I mean, I have to ask you, just curious, I know you've probably gotten huge offers from major companies. Can you speak to who you're considering working with?
Speaker 1:
[147:56] Yeah. So to explain my thinking a little bit, right? I did not expect this blowing up so much. So there's a lot of doors that open because of it. There's like, I think every big VC company is in my inbox and try to get 15 minutes of me. So there's like this butterfly effect moment. I could just do nothing and continue, and I really like my life. Valid choice, almost like I considered it when I deleted, wanted to delete the whole thing. I could create a company. I've been there, done that. There's so many people that push me towards that. Yeah, it could be amazing.
Speaker 2:
[149:00] We should say that you would probably raise a lot of money in that, I don't know, hundreds of millions, billions, I don't know. It just got unlimited amount of money.
Speaker 1:
[149:08] Yeah. It just doesn't excite me as much because I feel I did all of that and it would take a lot of time away from the things I actually enjoy. Same as when I was CEO, I think I learned to do it and I'm not mad at it. Partly, I'm good at it. But yeah, that path doesn't excite me too much and I also fear it would create a natural conflict of interest. What's the most obvious thing I do? I productize it up with a version safe for workplace. Then what do I do? I get a pull request with a feature like add audit log but that seems like an enterprise feature. Now, I feel I have a conflict of interest in the open source version and the closed source version. Or I change the license to something like FSL, where you cannot actually use it for commercial stuff. Would first be very difficult with all the contributions. And second of all, I like the idea that it's free as in beer and not free with conditions. Yeah, there's ways how you keep all of that for free and just like still try to make money, but those are very difficult. And you see, there's like few and few companies manage that. Like even Tailwind, they're like used by everyone. Everyone uses Tailwind, right? And then they had to cut off 75% of the employees because they're not making money, because nobody's even going on the website anymore, because it's all done by agents. And just relying on donations. Yeah, good luck. Like if a project of my caliber, if I extrapolate what the typical open source project would get, it's not a lot. I still lose money on the project, because I made the point of supporting every dependency, except Slack. They are a big company. They can do without me. But all the projects that are done by mostly individuals, so right now all the sponsorship goes right up to my dependencies. If there's more, I want to buy my contributors some merch.
Speaker 2:
[151:35] So you're losing money?
Speaker 1:
[151:37] Yeah, right now I lose money on this.
Speaker 2:
[151:38] So it's really not sustainable?
Speaker 1:
[151:41] I mean, it's like, I guess, something between 10 and 20K a month, which is fine. And I'm sure over time I could get that down. Open AI is helping out a little bit with tokens now. And there's other companies that have been generous. But yeah, still losing money on that. So that's one path I consider, but I'm just not very excited. And then there's all the big labs that I've been talking to. And from those, Meta and Open AI seemed the most interesting.
Speaker 2:
[152:24] Do you lean one way or the other?
Speaker 1:
[152:28] Yeah. Not sure how much I should share there. It's not quite finalized yet. Let's just say, like, on either of these, my conditions are that the project stays open source. That it, maybe it's gonna be a model like Chrome and Chromium. I think this is too important to just give to a company and make it theirs.
Speaker 2:
[153:08] This is...
Speaker 1:
[153:10] We didn't even talk about the whole community part, but like the thing that I experienced in San Francisco, like a clock run, seeing so many people so inspired, like, and having fun and just, like, building shit and, like, having, like, robots and lobster stuff walking around. Like, the people told me, like, they didn't experience this level of community excitement since, like, the old days of the internet, like, 10, 15 years. And there were a lot of high-caliber people there. Like, I was amazed. I also, like, was very sensibly overloaded because too many people wanted to do selfies. But I love this. Like, this needs to stay a place where people can, like, hack and learn. But also, I'm very excited to, like, make this into a version that I can get to a lot of people, because I think this is the year of personal agents, and that's the future. And the fastest way to do that is teaming up with one of the labs. And I also, on a personal level, I never worked at a large company, and I'm intrigued. You know, we talk about experiences. Will I like it? I don't know. But I want that experience. I'm sure, like, if I, if I announce this, then there will be people like, oh, he sold out, blah, blah, blah. But the project will continue. From everything I talked to so far, I can even have more resources for that. Like, both, both of those companies understand the value that I created something that accelerates our timeline and that got people excited about AI. I mean, can you imagine, like, I installed OpenClaw on one of my, I'm sorry, normie friends. I'm sorry, Vaughan, but he's also, you know, like, he's...
Speaker 2:
[155:25] Normie with love, yeah.
Speaker 1:
[155:26] He, he, like, someone who uses the computer, but never really, like, yeah, I use some ChatGPT sometimes, but not very technical. Wouldn't really understand what I built. So, like, I'll show you. And I paid for him the, the 90 buck, 100 buck, I don't know, subscription for Anthropic. And set up everything for him with, like, VWSL, Windows. I was curious, would he actually work on Windows, you know? It was a little early. And then within a few days, he was hawked. Like, he texted me about all the things he learned. He built, like, even little tools. He's not a programmer. And then within a few days, he upgraded to the $200 subscription. Oh, euros, because he's in Austria. And he was in love with that thing. Definitely was, like, a very early product validation. It's like, I built something that captures people. And then a few days later, Anthropic blocked him. Because based on their rules, using the subscription is problematic or whatever. And he was, like, devastated. And then he signed up for Minimux for 10 bucks a month and uses that. And I think that's silly in many ways. Because you just got a 200-buck customer. You just made someone hate your company. And we are still so early. Like, we don't even know what the final form is. Is it going to be cloud code? Probably not, you know. Like, that seems very... It seems very short-sighted to lock down your product so much. All the other companies have been helpful. I'm in slack of most of the big labs. Kind of everybody understands that we are still in an era of exploration, in the area of the radio show is on TV and not a modern TV show that fully uses the format.
Speaker 2:
[157:39] I think you've made a lot of people like see the possibility, sorry, non-technical people see the possibility of AI and just fall in love with this idea and enjoy interacting with AI. It's a really beautiful thing. I think I also speak for a lot of people in saying, I think you're one of the great people in AI in terms of having a good heart, good vibes, humor, the right spirit. It would, in a sense, this model that you're describing having open source part and you being part of also building a thing inside additionally of a large company, would be great because it's great to have good people in those companies.
Speaker 1:
[158:29] We know what also people don't really see is, I made this in three months. I did other things as well. I have a lot of projects. In January, this was my main focus because I saw the storm coming. But before that, I built a whole bunch of other things. I have so many ideas, some should be there. Some would be much better fitted when I have access to the latest toys. And I kind of want to have access to the latest toys. So this is important, this is cool, this will continue to exist. My short-term focus is like working through those, is it 3000 PRs now? I don't even know. Like there's a little bit of backlog. But this is not going to be the thing that I'm going to work until I'm 80. This is a window into the future, I'm going to make this into a cool product. But yeah, I have like, I have more ideas.
Speaker 2:
[159:29] If you had to pick, is there a company you lean, so Meta, OpenAI, is there one you lean towards going with?
Speaker 1:
[159:37] I spent time with both of those. And it's funny because a few weeks ago, I didn't consider any of this. And it's really fucking hard. Like, I have some, I know more people at OpenAI. I love their tech. I think I'm the biggest codex advertisement show that's unpaid and it would feel so gratifying to like put a price on all the work I did for free. And I would love if something happens and those companies get just merged. Because it's like.
Speaker 2:
[160:25] Is this the hardest decision you've ever had to do?
Speaker 1:
[160:32] Yeah, you know, I had some breakups in the past that feel like at a similar level.
Speaker 2:
[160:36] Relationships, you mean?
Speaker 1:
[160:40] Yeah, and I also know that in the end, they're both amazing. I cannot go wrong. It's like one of the most prestigious and largest, I mean, the largest, but like, they're both very cool companies.
Speaker 2:
[160:55] Yeah, they both really know scale. So if you're thinking about impact, some of the wonderful technologies you've been exploring, how to do it securely and how to do it at scale, such that you can have a positive impact on a large number of people. They both understand that.
Speaker 1:
[161:12] Yeah, both Nat and Mark basically played all week with my product and sent me like, oh, this is great. Oh, this is shit. Oh, we need to change this. Oh, like, funny little anecdotes. And people using your stuff is kind of like the biggest compliment. And also shows me that, you know, they actually care about it. And I didn't get the same on the OpenAI side. I got to see some other stuff that I find really cool. And they lure me with... I cannot tell the exact number because of... But you can be creative and think of the cerebral steel and how that would translate into speed. And that was very intriguing. You know, like, you give me source hammer. Yeah.
Speaker 2:
[162:21] Yeah.
Speaker 1:
[162:21] I've been lured with tokens. So, yeah.
Speaker 2:
[162:27] So it's funny. So Mark's sort of tinkering with the thing, essentially having fun with the thing.
Speaker 1:
[162:33] He got, like, when they first approached me, I got him in my WhatsApp and he was asking, yeah, when do we have a call? And I'm like, I don't like calendar entries. Let's just call now. And he was like, yeah, give me 10 minutes. I need to finish coding. Well, I guess that gives you a street cred. It's like, oh, like he's still writing code. You know, he didn't drift away in just being a manager. He gets me. That was a good first start. And then I think we had like a 10-minute fight, what's better, Claude code or Codex? Like, that's the thing. You first do like casually call someone that owns one of the largest companies in the world. And you have a 10-minute conversation about that. And then I think afterwards he called me eccentric, but brilliant. But I also had some really, really cool discussion with Sam Altman. And he's very thoughtful, brilliant. And I like him a lot from the little time I had. Yeah. I mean, I know some people willify both of those people. I don't think it's fair.
Speaker 2:
[164:08] I think no matter what, the stuff you're building and the kind of human you are, doing stuff at scale is kind of awesome. I'm excited.
Speaker 1:
[164:17] I am super pumped. And you know, the beauty is if it doesn't work out, I can just do my own thing again. Like I told them, like I don't do this for the money. I don't give a fuck. I mean, of course, it's a nice compliment, but I want to have fun and have impact. And that's ultimately what made my decision.
Speaker 2:
[164:51] Can I ask you about, we've talked about it quite a bit, but maybe just zooming out about how OpenClaw works. We've talked about different components. I want to ask if there's some interesting stuff we missed. So there's the gateway, there's the chat clients, there's the harness, there's the agentic loop. You said somewhere that everybody should implement an agent loop at some point in their lives.
Speaker 1:
[165:17] Yeah, because it's like the hello world in AI. It's actually quite simple. It's good to understand that this stuff's not magic. You can even easily build it yourself. So writing your own little Claude code. I even did this at a conference in Paris for people to introduce them to AI. I think it has a fun little practice. You covered a lot. I think one silly idea I had that turned out to be quite cool is I built this thing with full system access. So it's like, you know, with great power becomes great responsibility and I was like, how can I up the stakes a little bit more?
Speaker 2:
[166:05] Yeah, right.
Speaker 1:
[166:06] And I just made it proactive. So I added a prompt. Initially, it was just a prompt surprise me. I really like half an hour. Surprise me, you know? And later on, I changed it to be like a little more specific and in the definition of surprise. But the fact that I made it proactive and that it knows you and as it cares about you, at least it's programmed to do that, prompted to do that. And that is a follow on your current session. Makes it very interesting because it would just sometimes ask a follow up question or like, how's your day? I mean, again, it's a little creepy or weird or interesting, but heartbeat very in the beginning is still today. It doesn't, the model doesn't choose to use it a lot.
Speaker 2:
[167:09] By the way, we're talking about heartbeat, as you mentioned, the thing that regularly acts.
Speaker 1:
[167:16] You just kick off the loop.
Speaker 2:
[167:18] Isn't that just a cron job, man?
Speaker 1:
[167:20] Yeah, right.
Speaker 2:
[167:21] It's like the criticisms that you get.
Speaker 1:
[167:24] You can deduce any idea to like a silly, yeah, it's just a cron job in the end. I have like separate cron jobs.
Speaker 2:
[167:34] Isn't love just evolutionary biology manifesting itself and aren't you guys just using each other?
Speaker 1:
[167:42] And the project is all just glue of a few different dependencies and there's nothing original. Why do people, well, you know, isn't Dropbox just FTP with extra steps? I found it surprising where I had a shoulder operation a few months ago. And the model rarely used heartbeat, but then I was in the hospital and it knew that I had the operation and it checked up on me. It's like, are you okay? And I just, it's like, again, apparently, like if something's significant in the context, that triggered the heartbeat when it rarely used the heartbeat. And it does that sometimes for people, and that just makes it a lot more relatable.
Speaker 2:
[168:29] Let me look this up on complexity, how OpenClaw works just to see if I'm missing any of the stuff. Local agent runtime, high level architecture. Oh, we haven't talked much about skills, I suppose. Skill Hub, the tools in the skill layer. But that's definitely a huge component and there's a huge growing set of skills.
Speaker 1:
[168:47] You know what I love? That half a year ago, everyone was talking about MCPs. And I was like, screw MCPs. Every MCP would be better as a CLI. And now, this stuff doesn't even have MCP support. I mean, it has with asterisks, but not in the core layer and nobody's complaining. So my approach is, if you want to extend the model with more features, you just build a CLI and the model can call the CLI, probably gets it wrong, calls the help menu, and then on-demand loads into the context what it needs to use the CLI. It just needs a sentence to know that the CLI exists if it's something that the model doesn't know by default. And even for a while, I didn't really care about skills, but skills are actually perfect for that because they boil down to a single sentence that explains the skill, and then the model loads the skill and that explains the CLI, and then the model uses the CLI. Some skills are like raw, but most of the time networks.
Speaker 2:
[170:09] It's interesting. I'm asking Proplexity, MCP versus skills, because this kind of requires a hot take that's quite recent, because your general view is MCPs are dead-ish. So MCPs is a more structured thing. So if you listen to Proplexity here, MCP is what can I reach? So APIs, Databases, Services, Files, via protocol, so a structured protocol of how you communicate with the thing. And then skills is more, how should I work? Procedures, hostile, helper scripts, and prompts, often written in a kind of semi-structured natural language. And so technically skills could replace MCP if you have a smart enough model.
Speaker 1:
[170:52] I think the main beauty is that models are really good at calling Unix commands. So, if you just add another CLI, that's just another Unix command in the end. And MCPs, that has to be added in training. That's not a very natural thing for the model. It requires a very specific syntax. And the biggest thing, it's not composable. So imagine if I have a service that gives me better data and it gives me the temperature, the average temperature, rain, wind, and all the other stuff. And I get like this huge blob back. As a model, I always have to get the huge blob back. I have to fill my context with that huge blob and then pick what I want. There's no way for the model to naturally filter unless I think about it proactively and add a filtering way into my MCP. But if I would build the same as a CLI and it would give me this huge blob, it could just add a jq command and filter itself and then only get me what I actually need. Or maybe even compose it into a script to do some calculations with the temperature and only give me the exact output and you have no context pollution. Again, you can solve that with subagents and more charades, but it's just like workarounds for something that might not be the optimal way. It definitely was good that we had MCPs because it pushed a lot of companies towards building APIs and now I can like look at an MCP and just make it into a CLI. But this inherent problem that MCPs by default clutter up your context, plus the fact that most MCPs are not made good in general, make it just not a very useful paradigm. There's some exceptions like Playwright, for example, that require state and it's actually useful. That is an acceptable choice.
Speaker 2:
[172:58] So Playwright used for browser use, which I think is already in open clause quite incredible. You can basically do everything, most things you could think of using browser use.
Speaker 1:
[173:10] That gets into the whole arch of every app is just a very slow API now, if you want or not, and that through personal agents, a lot of apps will disappear. I built a CLI for Twitter. I mean, I just reverse-engineered the website and used the internal API, which is not very allowed.
Speaker 2:
[173:43] It's called Bird, short-lived.
Speaker 1:
[173:45] It was called Bird, because Bird had to disappear.
Speaker 2:
[173:50] The wings were clipped.
Speaker 1:
[173:51] All they did is they just made access slower. You're not actually taking a feature away. But now, if your agent wants to read a tweet, it actually has to open the browser and read the tweet, and it will still be able to read the tweet. It will just take longer. It's not like you're making something that was possible, not possible. No, now it's just ticking. Now it's just a bit slower. So it doesn't really matter if your service wants to be an API or not. If I can access it in the browser, it is API. It's a slow API.
Speaker 2:
[174:28] Can you empathize with our situation? What would you do if you were Twitter, if you were X? Because they're basically trying to protect against other large companies scraping all their data. But in so doing, they're cutting off a million different use cases for smaller developers that actually want to use it for helpful, cool stuff.
Speaker 1:
[174:47] I think if you have a very low per day baseline, per account that allows read-only access, would solve a lot of problems. There's plenty automations where people create a bookmark and then use OpenClaw to find the bookmark, do research on it, and send an email with more details on it or a summary. That's a cool approach. I also want all my bookmarks somewhere to search. I would still like to have that.
Speaker 2:
[175:18] So read-only access for the bookmarks you make on X, that seems like an incredible application. Because a lot of us find a lot of cool stuff on X. We bookmark, that's the general process of X. It's like, holy shit, this is awesome. Oftentimes, you bookmark so many things, you never look back at them. It would be nice to have tooling that organizes them and allows you to research your first.
Speaker 1:
[175:37] Yeah. I mean, and to be frank, I told Twitter proactively that, hey, I built this and there's a need. And they've been really nice. But also like, take it down. Fair. Totally fair. But I hope that this woke up the team a little bit that there's a need. And if all you do is making it slower, you're just reducing access to your platform. I'm sure there's a better way. I also, I'm very much against any automation on Twitter. If you tweet at me with AI, I will block you. No first strike. As soon as it smells like AI, and AI still has a smell, especially on tweets, it's very hard to tweet in a way that does look completely human. And then I block. Like I have zero tolerance policy on that. And I think it would be very helpful if they, if like tweets done via API would be marked. Maybe there's some special cases where, but, and there should be, there should be a very easy way for agents to get their own Twitter account. We need to rethink social platforms a little bit. If we go towards a future where everyone has their agent, and agents maybe have their own Instagram profiles or Twitter accounts, or can like do stuff on my behalf, I think it should very clearly be marked that they are doing stuff on my behalf and it's not me. Because content is now so cheap, eyeballs are the expensive part. And I find it very triggering when I read something and then I'm like, nobody smells like AI.
Speaker 2:
[177:33] Yeah. Like where is this headed in terms of what we value about the human experience? It feels like we will move more and more towards in-person interaction. And we'll just communicate, we'll talk to our AI agent to accomplish different tasks, to learn about different things. But we won't value online interaction because there'll be so much AI slop that smells and so many bots that it's difficult.
Speaker 1:
[178:08] Well, if it's marked, then it should be difficult to filter. And then I can look at it if I want to. But yeah, this is like a big thing we need to solve right now. Especially on this project, I get so many emails that are, let's say, nicely agentically written. But I much rather read your broken English than your AI slop, you know. Of course, there's a human behind it. And yeah, they prompt it. I much rather read your prompt than what came out. I think we're reaching a point where I value typos again. Like, you know, I mean, it also took me a while to come to the realization. On my blog, I experimented with creating a blog post with agents and ultimately it took me about the same time to like steer agent towards something I like, but it missed the nuances that how I would write it. You know, you can like, you can steer it towards your style, but it's not going to be all your style. So I completely moved away from that. Everything I blog is organic, handwritten, and maybe I use AI as a fix my worst typos, but there is value in the rough parts of an actual human.
Speaker 2:
[179:46] Isn't that awesome? Isn't that beautiful? That now, because of AI, we value the raw humanity in each of us more.
Speaker 1:
[179:55] I also realized the thing that I rave about AI and use it so much for anything that's code, but I'm allergic if it's stories.
Speaker 2:
[180:05] Right?
Speaker 1:
[180:05] Yeah. Also documentation is still fine with AI, better than nothing.
Speaker 2:
[180:10] For now, it still applies in the visual medium too. It's fascinating how allergic I am to even a little bit of AI slop in video and images. It's useful. It's nice if it's a little component of like-
Speaker 1:
[180:25] Even those images, all these infographics and stuff, they trigger me so hard. It immediately makes me think less of your content. They were novel for one week, and now it just screams slop. Even if people work hard on it, using- I have some of my blog posts in the time where I explore this new medium, but now they trigger me as well. It's like, yeah, this just screams the I slop.
Speaker 2:
[180:59] I don't know what that is, but I went through that too. I was really excited by the diagrams, and then I realized in order to remove from them hallucinations, you actually have to do a huge amount of work, and you're just using it to draw the better diagrams. It was great, and then I'm proud of the diagram. I've used them for literally, kind of like you said from the media, a couple of weeks, and now I look at those, and I feel like I feel when I look at Comic Sans as a font or something like this, it's like, no, this is fake, it's fraudulent. There's something wrong with it. It's a smell. It's a smell. And it's awesome because it reminds you that we know there's so much to humans that's amazing and we know it when we see it. And so that gives me a lot of hope. That gives me a lot of hope about the human experience is not going to be damaged, but it's only going to be empowered as tools by AI. It's not going to be damage-limited or somehow altered to where it's no longer human. So I need a bathroom break. Quick pause. You mentioned that a lot of the apps might be basically made obsolete. Do you think agents will just transform the entire app market?
Speaker 1:
[182:23] Yeah. I noticed that on Discord, people just said what they build and what they use it for. And like, why do you need my fitness pal when the agent already knows where I am? So I can assume that I make bad decisions when I'm at, I don't know, Waffle House, what's around here, or briskets in Austin.
Speaker 2:
[182:50] There's no bad decisions around briskets, but yeah.
Speaker 1:
[182:53] No, that's the best decision, honestly.
Speaker 2:
[182:56] Your agent should know that.
Speaker 1:
[182:57] But it can like, it can modify my gym workout based on how well I slept. Or if I'm, if I stress or not, like, it has so much more context to make even better decisions than any of us have even could do. It could show me UI just as I like. Why do I still need an app to do that? Why do I have to, why should I pay another subscription for something that the agent can just do now? And why do I need my, my eight sleep app to control my bed when I can tell the agent to, no, the agent already knows where I am, so I can like turn off what I don't use. And I think that will, that will translate into a whole category of apps that are no longer, I will just naturally stop using because my agent can just do it better.
Speaker 2:
[183:52] I think you said somewhere that it might kill off 80 percent of apps.
Speaker 1:
[183:57] Yeah.
Speaker 2:
[183:57] Don't you think that's a gigantic transformative effect on just all software development? That means it might kill off a lot of software companies.
Speaker 1:
[184:06] Yeah.
Speaker 2:
[184:09] It's a scary thing. So like, do you think about the impact that has on the economy, on just the ripple effects it has to society, transforming who builds what tooling? It empowers a lot of users to get stuff done, to get stuff more efficiently, to get it done cheaper.
Speaker 1:
[184:34] So some new services that we will need, right? For example, I want my agent to have an allowance. Like, you solve problems for me, here's like a hundred bucks in order to solve problems for me. And if I tell it to order me food, maybe it uses a service, maybe it uses something like, rent a human to like just get that done for me. I don't actually care. I care about solve my problem. There's space for new companies that solve that well. Maybe not all apps disappear, maybe some transform into being API.
Speaker 2:
[185:14] So basically apps that rapidly transform in being agent facing. So there's a real opportunity for like Uber Eats that we just used earlier today. It's companies like this of which there's many. Who gets there fastest to being able to interact with OpenClaw in a way that's the most natural, the easiest?
Speaker 1:
[185:43] Yeah. Also, apps will become API if they want or not, because my agent can figure out how to use my phone. I mean, on the other side, it's a little more tricky. On Android, people already do that, and then we'll just click the Order Uber for Me button for me, or maybe another service, or maybe there's an API that can call so it's faster. I think that's a space we're just beginning to even understand what that means. Again, there was not something I thought of, something that I discovered as people use this, and we're still so early. But yeah, I think data is very important, like apps that can give me data, but that also can be API. Why do I need the Sonos app anymore when my agent can talk to the Sonos speakers directly, like my cameras? Because there's like a crappy app, but they have an API. So my agent uses the API now.
Speaker 2:
[186:50] So it's going to force a lot of companies to have to shift focus. And it's kind of what the Internet did, right? You have to rapidly rethink, reconfigure what you're selling, how you're making money.
Speaker 1:
[187:03] Some companies will really not like that. For example, there's no CLI for Google. So I had to have to do anything myself and build Grok. That's like a CLI for Google. And at the end user, they have to give me the emails because otherwise I cannot use their product. If I'm a company and I try to get Google data, Gmail, there's a whole complicated process to the point where sometimes startups acquire startups that went through the process. So they don't have to work with Google for half a year to be certified to being able to access Gmail. But my agent can access Gmail because I can just connect to it. It's still crappy because I need to go through Google's developer jungle to get a key. And it's still annoying, but they cannot prevent me. And worst case, my agent just clicks on the website and gets the data out that way.
Speaker 2:
[188:10] To browse these.
Speaker 1:
[188:11] Yeah. I mean, I watch my agent happily click the I'm not a robot button. And there's this whole, that's going to be more heated. You see companies like CloudFlare that try to prevent bot access. And in some ways, that's useful for scraping. But in other ways, if I'm a personal user, I want that. You know, sometimes I use Codex and I read an article about modern React patterns and it's like a medium article. I paste it in and the agent can't read it because they block it. So I have to copy-paste the actual text or in the future, I learned that maybe I don't click on medium because it's annoying. And I use other websites that actually are agent-friendly.
Speaker 2:
[189:05] So there's going to be a lot of powerful rich companies fighting back. So it's really interesting. You're at the center. You're the catalyst, the leader, and happen to be at the center of this kind of revolution where it's going to completely change how we interact with services, with the web. And so there's companies at Google they're going to push back. I mean, there's every major companies you could think of is going to push back.
Speaker 1:
[189:33] Even Search, I now use, I think Perplexity or Brave as providers, because Google really doesn't make it easy to use Google without Google. I'm not sure if that's the right strategy, but I'm not good with.
Speaker 2:
[189:50] Yeah, there's a nice balance from a big company perspective, because if you push back too much for too long, you become a blockbuster and you lose everything to the Netflix of the world. But some pushback is probably good during the revolution to see.
Speaker 1:
[190:03] But you see that this is something that the people want. Right. So if I'm on the go, I don't want to open a calendar app. I just want to tell my agent, hey, remind me about this dinner tomorrow night, and maybe invite you of my friends, and then maybe send a WhatsApp message to my friend. I don't want to need to open apps for that. I think that we passed that age, and now everything is much more connected and fluid if those companies want it or not. I think the right companies will find ways to jump on the train, and other companies will perish.
Speaker 2:
[190:47] You gotta listen to what the people want. We talked about programming quite a bit, and a lot of folks that are developers are really worried about their jobs, about the future of programming. Do you think AI replaces programmers completely? Human programmers?
Speaker 1:
[191:04] I mean, we're definitely going in that direction. Programming is just a part of building products. So maybe, maybe AI does replace programmers eventually. But there's so much more to that art. Like, what do you actually want to build? How should it feel? How's the architecture? I don't think Asians will replace all of that. Yeah, like, just the actual art of programming, it will stay there, but it's gonna be like, knitting, you know, like people do that because they like it, not because it makes any sense. So, I read this article this morning about someone that it's okay to mourn our craft. And I can, a part of me very strongly resonates with that because in my past, I spent a lot of time sinkering, just being really deep in the flow and just like cranking out code and like finding really beautiful solutions. And yes, in a way, it's sad because that will go away. And I also got a lot of joy out of just writing code and being really deep in my thoughts and forgetting time and space and just being in this beautiful state of flow. But you can get the same state of flow. I get a similar state of flow by working with agents and building and thinking really hard about problems. It is different, but it's okay to mourn it. But it's not something we can fight. The world for a long time had a... There was a lack of intelligence, if you see it like that, of people building things. And that's why salaries of software developers reached stupidly high amounts. And they will go away. There will still be a lot of demand for people that understand how to build things. Just that all this tokenized intelligence enables people to do a lot more, a lot faster. And it will be even more, even faster and even more, because those things are continuously improving. We had similar things when... I mean, it's probably not a perfect analogy, but when we created the Steam Engine and they built all these factories and replaced a lot of manual labor and then people revolted and broke the machines. I can relate that if you very deeply identify that you are a programmer, that it's scary and that it's threatening because what you like and what you're really good at is now being done by a soul less or not entity, but I don't think you're just a programmer. That does a very limiting view of your craft. You are still a builder.
Speaker 2:
[194:32] Yeah, there's a couple of things I want to say. So one is, as you're articulating this beautifully, I'm realizing I never thought I would... The thing I love doing would be the thing that gets replaced. You hear these stories about these, like you said, with the Steam Engine. I've spent so many, I don't know, maybe thousands of hours pouring over code and putting my heart and soul and just like some of my most painful and happiest moments or alone behind... I was an Emacs pressure for a long time. Man Emacs. And then there's an identity and there's meaning and there's like when I walk about the world, I don't say it out loud, but I think of myself as a programmer. And to have that in a matter of months, I mean, like you mentioned, April to November, it really is a leap that happened, a shift that's happening. To have that completely replaced is painful, it's truly painful. But I also think programmers, builders more broadly, but what is the act of programming? I think programmers are generally best equipped at this moment in history to learn the language, to empathize with agents, to learn the language of agents, to feel the CLI. To understand what is the thing you need, you the agent, need to do this task the best.
Speaker 1:
[196:14] I think at some point it's just going to be called coding again and it's just going to be the new normal. And yet, while I don't write the code, I very much feel like I'm in the driver's seat and I am writing the code.
Speaker 2:
[196:29] You'll still be a programmer. It's just the activity of a programmer is different.
Speaker 1:
[196:34] Yeah. And because on X, the bubble is mostly positive. On Master Tone and Blue Sky, I also use it less because oftentimes I got attacked for my blog posts. And I had stronger reactions in the past. Now I can sympathize with those people more. Because in a way I get it. In a way I also don't get it because it's very unfair to grab onto the person that you see right now and unload all your fear and hate. It's going to be a change and it's going to be challenging. But it's also, I don't know, I find it incredibly fun and gratifying. And I can use the new time to focus on much more details. I think the level of expectations of what we build is also rising because it's just now, the default is now so much easier. So software is changing in many ways. There's going to be a lot more. And then you have all these people that are screaming, oh yeah, but what about the water? You know, like I did a conference in Italy about the state of AI, and my whole motivation was to push people away from, don't see yourself as an iOS developer anymore, you're not a builder, and you can use your skills in many more ways. Also because apps are slowly going away. People didn't like that. Like a lot of people didn't like what I had to say. And I don't think I was hyperbole. I was just like, this is how I see the future. Maybe this is not how it's going to be. But I'm pretty sure a version of that will happen. And the first question I got was, yeah, but what about the insane water use on data centers? But then you actually sit down and do the math. And then for most people, if you just skip one burger per month, that compensates the CO2 output or like the water use. In the equivalent of tokens. I mean, the math is tricky and it depends if you add pre-training, then maybe it's more than just one patty, but it's not off by a factor of 100, you know? So, well, like golf is still using way more water than all data centers together. So are you also hating people that play golf? Those people grab on anything that they think is bad about AI without seeing the potential things that might be good about AI. And I'm not saying everything is good. It's certainly going to be a very transformative technology for our society.
Speaker 2:
[199:25] There is, to steel man the criticism in general, I do want to say in my experience with Silicon Valley, there's a bit of a bubble in the sense that there's a kind of excitement and an overfocus about the positive that the technology can bring. And which is great. It's great to focus on not to be paralyzed by fear and fear-mongering and so on. But there's also within that excitement and within everybody talking just to each other, there's a dismissal of the basic human experience across the United States and the Midwest and across the world, including the programmers we mentioned, including all the people that are going to lose their jobs, including the measurable pain and suffering that happens at the short-term scale when there's change of any kind, especially large-scale transformative change that we're about to face if what we're talking about will materialize. And so having a bit of that humility and awareness about the tools you're building, they're going to cause pain. They will long-term, hopefully bring up about a better world and even more opportunities and even more awesomeness. But having that kind of like quiet moment often of respect for the pain that is going to be felt. And so not enough of that is, I think, done. So it's good to have a bit of that.
Speaker 1:
[201:00] And then I also have to put against some of the emails I got where people told me they have a small business and they've been struggling and OpenClaw helped them automate a few of the tedious tasks from collecting invoices to answering customer emails that then freed them up and cost them a bit more joy in their life. Or some emails where they told me that OpenClaw helped a disabled daughter that she's now empowered and feels she can do much more than before. Which is amazing, right? Because you could do that before as well. The technology was there. I didn't invent a whole new thing, but I made it a lot easier and more accessible. And that did show people the possibilities that they previously wouldn't see. And now they apply it for good. Or like also the fact that, yes, I suggest the latest and best models, but you can totally run this on free models. You can run this locally. You can run this on Kimi or other models that are way more accessible price-wise. And still have a very powerful system that might otherwise not be possible because other things like, I don't know, Anthropic's co-work is locked in into their space. So it's not a lot of black and white. I got a lot of emails that were hard-warming and amazing and I know it just makes me really happy.
Speaker 2:
[202:40] Yeah, there's a lot. It has brought joy into a lot of people's lives, not just programmers, like a lot of people's lives. It's beautiful to see. What gives you hope about this whole thing we have going on? The human civilization.
Speaker 1:
[202:56] I mean, I inspired so many people. There's this whole build-up vibe again. People are now using AI in a more playful way, and are discovering what it can do, and how it can help them in their life, and creating new places that are just sprawling of creativity. I don't know, there's like Clorcon in Vienna, there's like 500 people, and there's such a high percentage of people that I want to present, which is to me really surprising, because usually it's quite hard to find people that want to like talk about what they built, and now there's an abundance. So that gives me hope that we can figure shit out.
Speaker 2:
[203:53] And it makes it accessible to basically everybody.
Speaker 1:
[203:57] Yeah.
Speaker 2:
[203:58] Just imagine all these people building, especially as you make it simpler and simpler, more secure. It's like anybody who has ideas and can express those ideas in language can build. That's crazy.
Speaker 1:
[204:15] Yeah, that's ultimately part of the people and one of the beautiful things that come out of AI. Not just the Slop generator.
Speaker 2:
[204:29] Well, Mr. Claude Father, I just realized when I said that in the beginning, I violated two trademarks because there's also the Godfather. I'm getting sued by everybody. You're a wonderful human being. You've created something really special. A special community, a special product, a special set of ideas plus the entire, the humor, the good vibes, the inspiration of all these people building, the excitement to build. So I'm truly grateful for everything you've been doing and for who you are and for sitting down to talk with me today. Thank you, brother.
Speaker 1:
[205:07] Thanks for giving me the chance to tell my story.
Speaker 2:
[205:10] Thanks for listening to this conversation with Peter Steinberger. To support this podcast, please check out our sponsors in the description where you can also find links to contact me, ask questions, give feedback and so on. And now, let me leave you some words from Voltaire. With great power comes great responsibility. Thank you for listening and hope to see you next time.