Y Combinator Startup Podcast
00:21:33 · Peter Steinberger
I also need to give NVIDIA a special shout out, because they were very early, and they simply asked me what I need, and then they sent people to take over much of their security work. And I think it was somewhere in May, around my birthday, where I had this feeling that things are starting to feel good again, where the joy of building for me was coming back. And, yeah, somewhere in the press, the press decoyed an OpenClaw killer every other week. At some point, think I counted 20 of them. There's even a literally a project called OpenClaw Killer. It's an uninstaller, which is totally unnecessary because we have an uninstaller, but you know. But none of the killer stories ever picked up what this is actually about. Open source. My source of inspiration is being annoyed. These days, I get annoyed when I have to use software where I can't just send a prompt to my agent to change it. That's the fun part that's coming back. It's hard to compete with someone who's just there having fun. Fun is velocity. The weeks I enjoyed building, the product got visibly better. The weeks I didn't, we shipped config options. Question five. What's next? Some people in the audience might be like, is this finally the part where he talks about graphs? First of all, I'm super happy with where we are with the foundation. Our mission is to bring people closer to AI, and things are changing so fast. For many people, it feels scary. I'm proud of one thing that OpenClaw achieved. And that for many people, it moved AI from this thing that's like nebulous and scary into something that is fun and weird, you know, lobsters and all of that. And they'll keep pushing there. Keep building a great ecosystem of open source software with events that bring people together and with education. We have 10 people now on payroll. We're hiring a few more roles, including a CEO. Second of all, I kinda made Claw a noun. You know, cup party dropped the open. Satya says enterprise grade Claws in Microsoft's Keynote. There are 33,000 Claw named repositories. If we are in a simulation, we are certainly in one of the weirder ones that won't get shut down. I dig this part of the future. Third, we still don't have an agent that's always on, always syncing. There's still so much to do.
00:24:31 · Peter Steinberger
The landscape and the tech in AI are evolving faster than the software that we build around, and that's an opportunity for all of you. Our workflows are also evolving. Like the vision I had early on, where we shouldn't think about session or compaction. The world is finally, the models, tech is finally getting to a stage where this is becoming a reality. We're entering a world where we finally move on from the text, text only interfaces to voice and multimodality. Just yesterday, we got a hack working that your Claw can now FaceTime you. And this is kinda what matters why OpenClaw exists at all. Every lab will sell you an agent. OpenClaw is the alternative. Open source, runs everywhere, works with any model. And if you run local models, your data never has to leave your device. Your agent, your machine, your life. That's not even my thesis. That's Garry's, you know? We just chipped it first. So we also finally are building OpenClaw with OpenClaw again, but this time with a twist where everyone sees each other session on a team server, and there's a claw that knows what everyone else is working on, and also can also take over orchestration of the work. And we are finally leaving this slowly, this weird blip in the future where people work in terminals and run around with their laptops open because the agent needs to keep working. If you only remember three things. Number one, don't stop having fun. Find is the ultimate driver so you can you can get the best ideas. Number two, listen to your gut. And also, fix the things that annoy you. It might just become the next big thing. And number three, stay focused. You know, another podcast is not what will make you win. Live in the future, build what's missing, and when they write your obituary, keep shipping, it confuses them. Now these were five questions. I'm sure you have many more, and I think we have plenty of time for QA.
00:27:00 · S1, Peter Steinberger
[00:27:00] S1: So, first it was agents, then loops, then graphs. How are you building these days? [00:27:06] S0: I mean, was always sessions, right? But in the beginning you had to like actually care that like you would clean, and like you would make sure that your instructions are coherent. And these days it's more like my sessions are topics, clearing a session sometimes even a disadvantage because there's so much information in there that helps the agent. But the big thing, the thing that shifted is, I try to make the agent more proactive work for me. So when I shift my attention to something, I don't wanna read issues, I wanna see fully reviewed and tested PRs. Maybe I like the feature, maybe I don't, but like I don't want to like split my attention. At the same time at work, if you come to me and you tell me this feature idea, I'm gonna get mad at you. Like, it's so easy that you just discuss the feature idea with an agent, you build it, you make screenshots, you let me play with it. That way if it's good, we can like immediately iterate it, but most of the time people will figure out why it's not good and not even come to me. [00:28:28] S1: What comes after graphs? And what's next for OpenClaw?
00:28:28 · S1, Peter Steinberger
[00:28:28] S1: What comes after graphs? And what's next for OpenClaw? [00:28:33] S0: I know, like, sometimes I like to shit post on a Sunday, and then like my Twitter explodes. But also, it's not a shit post. Right? So anytime you you you know what we as engineers did for the longest time? We built automations to make our life easier. That's like, that's been going on since our profession exists. So if you design, call it loop, call it graph, call it workflow, it's kinda all the same. If you design something that gets a trigger or gets an input and does something for you, and maybe there's a decision in the way, boom, there's your graph. It's not it's not magical, even though like, you know, I favorited some of those graph engineering posts because I'm kinda curious what their opinion is that it would be. In in my world, it's just like, it's just a better way of our automation story that we did for so long already. [00:29:39] S1: In a world of build fast, ship fast, how to make sure that what you build is still reliable and scalable?
00:29:39 · S1, Peter Steinberger
[00:29:39] S1: In a world of build fast, ship fast, how to make sure that what you build is still reliable and scalable? [00:29:47] S0: Yeah, that's the part I messed up for a while because I was not was not focused, and the models were not really good at testing. I think that the models are really good now. We have, we not just have sessions that remember, we have orchestration trained into models so they really understand and know to use sub agents. We have computer use, we have browser use, like all of that together is like your perfect Q and A environment. Like I did that yesterday where I spin up codecs, use 12 sub agents, understand my project, break it down into features, and then each sub agent would like stress test the feature or code review feature, and then inform the other session where to focus testing on. So we're not yet at the point where you can automate everything. You'll still need to do some manual click throughs so that you know how it feels, but like for a lot of the typical bugs that users will encounter, you can actually now, you can prompt your way and you get very far. [00:31:04] S1: Okay. AI tools. What's your decision you made purely for speeds early that you still live with today?
00:31:04 · S1, Peter Steinberger
[00:31:04] S1: Okay. AI tools. What's your decision you made purely for speeds early that you still live with today? [00:31:12] S0: I think that was really early in in deciding that I don't read all the code. I see code review more as risk management. You know, sometimes you touch a system that is scary. You kinda wanna like read a little bit closer, and other times you build UI. Do I really care the UI is built if it looks correct? No. So you kinda, you glance over or you simply accept that it looks right. Part of it is just like you develop a little bit of a feeling how long something should take. So if I do a small tweak that should like change how dragging works, and it takes three hours, I know something's wrong. I'll look closely. But otherwise, part of code review is simply like observing, looking how big a change is and trusting your gut. [00:32:09] S1: Okay. AI tools make it easy to build a product in a weekend now, but building isn't the hard part, getting people to use this. How would you go from a working prototype to your first 10 real users today? [00:32:25] S0: Well, I think that was part of what I addressed in my talk. User number one should be you, and my users two to 20 were friends. So I'm sure you have some people that would actually test your stuff, but you need to be the first user. If you don't you don't get excited about what you're building, it'll probably not make sense.