Lenny's Podcast: Product | Career | Growth
00:07:01 · Dan Shipper, Lenny Rachitsky
At that time we ran maybe two or three. And from that point on, we just started shifting to a world where no one was looking at the code. Everybody was talking to their computer in English, using Claude Code in the terminal. And so I was able to see like, "Ooh, this is starting to happen." And then because my job is a little bit to just push and play with stuff, I was like, "I wonder if I could use this for my writing. How could I do that?" And then it just starts to unfold and you're like, "Okay, this is not ready yet, but it's obviously useful for me." One of the things that we talk about internally is what I call the reach test, which is like, when you wake up in the morning, do you reach for it organically? [00:07:48] S0: I love this combination of you are using the latest stuff. And I think this is, as you said, maybe an underrated skill, is you're good at being self-aware of here's what's weird and new and different and interesting. So that's a really cool combination, partly because you have to write about it and you write about it. So I think that's the perfect recipe for someone having a sense of where things are going. [00:09:39] S1: Lenny, my only ask is we come on a year from now and then you score it. I want to score it. [00:09:45] S0: Okay. So this is a year from now. Okay. Okay. Is this like your predictions for, in a year, this is what it's going to look like? Or this is like the emerging future?
00:09:45 · Lenny Rachitsky, Dan Shipper
[00:09:45] S0: Okay. So this is a year from now. Okay. Okay. Is this like your predictions for, in a year, this is what it's going to look like? Or this is like the emerging future? [00:09:58] S1: I will probably say, I don't have an exact timeline. I think most of the stuff that I'm going to talk about will be pretty apparent within a year, but it may take longer than that. [00:10:07] S0: Okay. [inaudible 00:10:08]. [00:10:08] S1: So it should within at least a year be not obviously wrong. It should seem like it's moving in that direction to count. [00:10:16] S0: Okay. May of 2027, we will review your predictions. [00:10:22] S1: Amazing. [00:10:24] S0: Okay. I love this. Okay. So let's dive in. What are some predictions for how the way we work is going to change in the coming year?
00:10:29 · Dan Shipper
[00:10:29] S1: One of my favorite questions, because I think if you look at the benchmarks, you're just looking at, okay, yeah, AI is going to just take all of our jobs, basically. METR has this really cool benchmark where it's like it measures how long the newest models can do tasks autonomously and it's like, oh, it can, what's it called? Oh, Mythos preview, the big anthropic model that everyone's so worried about, it can do tasks of 17 hours at 50% accuracy. It's like, holy shit, that's crazy. And I think it is real. It's true and the progress, model progress is going up exponentially. And my experience and my feeling is that we will look back in a year and say we actually have a lot more work to do. Humans have a lot more work to do, even as models get better at doing work. And there's a really interesting paradox there. And my big prediction of how work will change or how you will be doing work in a year is it's going to bifurcate in this in two main ways, how you use agents. One is you're going to be doing, I think what we figured you would be doing five years ago when we thought about how work with AI works, which is everyone's going to have at least in their company, at least one agent that they talk to, that can do work, that they can offload work to. And we'll talk about what that looks like, but it's essentially like OpenClaw. Second is that most of the work that you do is actually going to happen on your computer, in an environment like Codex or Claude Cowork. That becomes the operating system for ... It becomes a operating system for how you do all of your work, whether that's your email, the documents you create, all that stuff. It's going to be on that kind of surface. That's becoming the clear competitive landscape. I want to go in order of those two. So the first one is you're going to have agents you delegate to probably in Slack, but anywhere. First thing that's interesting about that one is it's not clear what the architecture is going to be like for that. Is everyone going to have an agent? Is every team going to have an agent? Is it going to be just one agent? Do agents specialize? Is there this parallel shadow org chart?
00:13:04 · Dan Shipper, Lenny Rachitsky
And when OpenClaw first came out, everyone internally at Every adopted it and I was very convinced that it would be everyone has their own agent and there's some really interesting things about that world of a parallel org chart. Agents in that world become little reflections of you, which is really cool and really interesting. It's like if you ever ... Did you ever read the Golden Compass? [00:13:33] S0: Yeah. [00:13:34] S1: It's like having a little daemon on your shoulder ... [00:13:36] S0: [inaudible 00:13:36].
00:13:36 · Dan Shipper
[00:13:36] S1: That's a little part of your soul. I really think that's what it looked like was happening. And so I was very into personal agents and I have completely flipped and I really think that the model, for now, is going to be a super agent, like one agent for the entire company and you're starting to see this in some companies. So Shopify very famously has one, Ramp has one now and I think there's some really interesting reasons for that. I actually still think that the personal agent thing is coming, but what we found is there's all this hype with OpenClaw. Everyone's like, "I'm going to set it up. It's so cool," or whatever. And then everyone realizes it's like way too much work. This thing breaks all the time. I got to fumble around with it. I got to be able to SSH into my server and like blah, blah, blah. And most people, to do work at least, just don't want to spend that time, or can't. And the fundamental, underlying thing that drives that is whether it's OpenClaw or any other harness, in order for an AI agent to be useful right now, it really needs a human who cares about it. It really needs a human personal connection with someone who's watching what it does and makes sure that it's doing the right thing and that it's useful for people. And the minute you sever that connection, so the minute someone's like, "Ah, I don't want to maintain this dumb OpenClaw," is the minute the agent is not really that useful anymore. And that's why I think it has started to shift to a more one agent per company model because for now, the ideal is you basically set up a forward deployed engineer or someone with that profile who's responsible for making sure that that agent is working for the whole company and then maybe you have some little team agents. And I think as the models get better at being more independent, that will shift down and it'll be more likely that we'll have more personal agents because we won't have to fuck around with all the internals. But the model that I see working for us and for a lot of other companies, including the model companies, the model companies themselves are starting to see this, is when it comes to the like async agents, it's really a, you have one agent at the top that's like doing, sometimes it's everything.
00:16:02 · Dan Shipper, Lenny Rachitsky
A lot of times it's a particular job that you've decided that everyone in the company needs an agent for, like data requests. And then I think it starts at the top and then it starts to trickle down, where you may get more specialized agents and teams and all that kind of stuff. And the mechanism is agents need people who care about them. [00:16:24] S0: That is so interesting, that point about you need to garden your agent because there's context you have to keep adding to it. It breaks, as you said, and once it's just too much work, you're like, "Okay, forget this thing. I'm going to go back to Codex or Claude or something like that." [00:16:38] S1: Exactly. [00:16:39] S0: Okay, cool. So this is a cool opportunity. So the idea, so what you're predicting here is companies will have this super agent that everyone can talk to. As you said, Shopify's got River, I think it's called. What's the Ramp one called? [00:16:49] S1: I can't remember. [00:16:50] S0: Okay. It's probably got to fun name. Okay. So that's the prediction. Okay. [00:16:56] S1: That's the first prediction ... [00:16:57] S0: That's the first prediction. [00:16:59] S1: Is we will start with agents at the top that are more general and are used by more people in the company and then it will start to grow down, as people get more used to these use cases, they get more specialized and agents become less ... Fiddly. They just work better. [00:17:22] S0: And is this mostly going to be in Slack, do you predict?