Lenny's Podcast: Product | Career | Growth
00:33:38 · Dan Shipper
[00:33:38] S1: Well, a few things. I'm definitely not an agent maximalist, I really think we're going to have a lot of different agents that we use. It seems pretty clear to me. And I really do think that two agents are better than one, so what's a good example? When I have Codex interact with another agent, it can give so much more context about me and what I want than I would be able to type, and it can go back and forth talking about things that would take a long time for me to express directly to an agent that you get this speed up effect when you assume that your users are using Codex, or Claude Code, or Cowork as their basic way they access your app. And a really simple example, we have this hosted OpenClaw product, which we had on waitlist. We actually had to pause it because we started taking people off the waitlist, and OpenClaw is just a very a very hard agent harness to make work. It's moving so incredibly fast, and if you're like a platform for it, it's like when things break you can't fix it. It's very hard. But one of the things that we learned in that process is let's say you're building an agent product or any new software experience, what you would assume, let's say to set up an agent, is you need to build a little web interface or a little Slack workflow that asks people about, "Okay, who are you and what are you going to use this for? And what's your ideal dream outcome?" Or whatever the things you are that you would put on an onboarding checklist. If instead you just make a hard line of we are only going to service users who use Codex or Cowork, what happens is you just paste a prompt into Codex or Cowork, it goes and talks to the app, and the app can be either just a regular server or it can be its own agent, and Codex has so much information about you that it can just give it. "Here's all the stuff I've been working on with Dan, here's all the ways that he might want to use this app," and then bring it back to me, and it's this very custom experience. And also for a technical product like an agent, when something goes wrong I can just tell Codex, "Go fix it." And Codex will go talk to the app and figure out what's going on for me. And so, I think the whole paradigm starts to change when you assume that everyone's got an agent and those agents are talking to other agents in this really magical and important way.
00:36:22 · Lenny Rachitsky
[00:36:22] S0: There's a couple more things I want to touch on before we get started, because there's so much to talk about. One is you made this point about SaaS tools not using ... You can use tokens from the model companies basically when using a SaaS tool. Talk a bit more about that, because that may change the business model for SaaS companies in the future. That feels like a big deal.
00:36:41 · Dan Shipper
[00:36:41] S1: Well, I think it actually may save their margins, because right now all these companies are rushing to add a agent to their offering and thinking, "Oh, the agent is going to be the main way that people interact with me." And that cost tokens, obviously. And I actually think once I have Codex or Cowork as my main work surface, I still want to use SaaS. So, this is another good prediction. I would buy SaaS stocks right now. I think the SaaS apocalypse is dumb, and SaaS stocks will be up majorly in the next couple years. Not investment advice, but I would buy SaaS stocks. So, I think it saves your margin because now the way that you're thinking then is not I have to build AI into this, it's more like I have to make a piece of software that humans and AI want to collaborate on together. And that's hard, but once you build it, it's a lot cheaper than assuming everyone's spending tokens, and I think it's a good business. And part of the reason I'm so bullish on SaaS is A, everybody internally here is, like I said, we have all got agents and we're all using Codex and whatever, and we still pay for a ton of SaaS and our SaaS spend is up year over year, and we're not vibe coding every single little thing. And I think that what agents do is increase the number of users of SaaS, not get rid of it. And so, I think SaaS companies are going to see an insane spike in the amount of demand that they have, because there's going to be tons of agents using these products at a very high volume. And like I said, that's a huge infrastructure challenge. There's a lot of interesting pricing challenges, but it makes me very bullish on SaaS.
00:38:47 · Lenny Rachitsky, Dan Shipper
[00:38:47] S0: I love that. If anything else comes out of this conversation, Dan Shipper, SaaS is the future of AI. B2B SaaS. [00:38:56] S1: Hashtag send tweet. [00:38:59] S0: Yeah, this is quite contrarian. And the other interesting piece is that the fact that you guys are hiring, that you doubled in people in the past year, which is not what people would have expected from a company that is so AI forward. Talk about your experience there of just, okay, we still actually need humans.
00:39:15 · Dan Shipper
[00:39:15] S1: Automation is a lie, in the sense that every time you automate something, in order to make sure the automation is working well you need a human on top of it making sure that it's working well. And so, I wrote this piece a couple years ago about the allocation economy, the idea that the way that humans are going to work with AI is going to be like being a manager. And the thing that you have to remember about managers is like managers actually spend a lot of time working. Most managers are not on the beach, they're checking in with their employees all the time and trying to figure out, "Okay, how do we make this work good? How do we make it better? How's it doing? How's this person doing?" All that kind of stuff. And I think there's some differences between being a human manager and being a model manager, but fundamentally it still requires a lot of time and attention. And I think that we miss that in the model discourse. And one of the reasons is, benchmarks make it look like AI is more autonomous than it is. And by autonomy, I mean something specific by autonomy, and I'm going to try to express this. It's a little hard to express, but I learned this for myself because I've been feeling this paradox a little bit. I've been feeling that we have so much automation, so much AI, and I also work way more. And I think part of the paradox started to resolve for me a little bit when I made my own benchmark. So I made this senior, it's called the senior engineer benchmark, and it's like how good is AI versus a human engineer? And the way that I built it is again, have this app, Proof. I just vibe coded it on the side while running the rest of Every. And when we launched it, because it was completely vibe coded, it just started going down and I couldn't fix it and it was very embarrassing. I had a lot of egg on my face. And the product worked, we tested it internally. We had a lot of beta testers, but the day after launch it was like just every 10 minutes the servers would go down and people were looking at me and I'd be like, "I don't know what's going on. Codex, fix it." And Codex is like, "I don't know what's going on." Or really Codex was like, "I do know what's going on, I fixed it." And then it would cause four other errors and then you're just going around in a circle, and I wasn't sleeping, and I vibe coded so hard I got bursitis on my elbow.
00:41:39 · Dan Shipper, Lenny Rachitsky
So, there's a life lesson in there. [00:41:42] S0: Vibe coder elbow.