Lenny's Podcast: Product | Career | Growth
00:26:17 · Simon Willison
[00:26:17] S0: And actually, I want to stand in defense of software engineers for a bit because on the one hand, these things can write code. That used to be our thing. I'm finding that using coding agents well is taking every inch of my 25 years of experience as a software engineer, and it is mentally exhausting. This is something which people are talking a lot more about now. I can fire up four agents in parallel and have them work on four different problems, and by 11:00 AM, I am wiped out for the day, because there is a limit on human cognition in how much, even if you're not reviewing everything you're doing, just how much you can hold in your head at one time. And it's very easy to pop that stack at the moment. There's a sort of personal skill that we have to learn, which is finding our new limits. What is a responsible way for us to not burn out and for us to use the time that we have? And I've talked to a lot of people who are losing sleep because they're like, "My agents could be doing work for me. I'm just going to stay up an extra half hour and set off a bunch of extra things and I'm waking up at 4:00 in the morning." That's obviously unsustainable. I hope that that's a novelty thing. The agents only really got good in the past four to five months. We're all learning what that looks like and what that lets us do. But it's concerning. There's an element of gambling and addiction to how we're using some of these tools. But to stand in defense of software engineers, I get great results out of these things because they are amplifiers of existing skills and experience. And I have 25 years of existing pre-AI experience, which I can now amplify because I can talk to the agent at a very high level. I can use sophisticated engineering language that I've mastered over the years, which they appear to know as well, and we can collaborate incredibly effectively. And it means I can look at a problem and I can say, "This problem is a one-sentence prompt and I know it'll find that bug and fix that bug," as opposed to this other problem, which is who knows how big a problem. There is a flip side to this, which is that I've got 25 years of experience in how long it takes to build something, and that's all completely gone. That doesn't work anymore because I can look at a problem and say, "Okay, well, this is going to take two weeks.
00:28:27 · Simon Willison, Lenny Rachitsky
It's not worth it." And now it's like, yeah, but maybe it's going to take 20 minutes, because the reason it would've taken two weeks was all of the crufty coding things that the AI is now covering for us. And that I've been finding really interesting and challenging. I constantly throw tasks at AI that I don't think it'll be able to do, because every now and then it does it. And when it doesn't do it, you learn. You learn, okay, Opus 4.6 still can't do this particular thing, but when it does do something, especially something that the previous models couldn't do, that's actually cutting edge AI research. You can be the first person in the world to spot that AI can now do X just because you were the person you found it couldn't do it and you've been keeping that sort of backlog of interesting tasks for it. [00:29:13] S1: This is such an interesting line of discussion, this idea that let's say 10X engineers, to use that phrase, are going to be more valuable is what you're describing here because you can work with these tools much more effectively. What do you think of junior engineers? Just what's happening there? What's their future?
00:29:29 · Simon Willison
[00:29:29] S0: So Thoughtworks, the big IT consultancy, did an offsite about a month ago and they got a whole bunch of engineering VPs in from different companies to talk about this stuff. And one of the interesting theories they came up with is they think this stuff is really good for experienced engineers. It amplifies their skills. That's great. It's really good for new engineers because it solves so many of those onboarding problems. If you talk to Cloudflare and Shopify both said they were hiring a thousand interns over the course of 2025 because the intern onboarding costs, it used to be takes a month before your intern can do anything useful. Now they're doing something useful within a week because the AI assistant helps them get up and running faster. The problem is the people in the middle. If you're mid-career, if you haven't made it to super senior engineer yet, but you're not new either, that's the group which ThoughtWorks resolved were probably in the most trouble right now. That's the open question because they don't have that expertise to amplify and use with these tools and it's not as benefit... They've got all of the boosts that the beginners were getting, they've got already, so that's an interesting open question right now for me is it's more the sort of mid-level as opposed to the beginners or the advanced people.
00:30:48 · Lenny Rachitsky
[00:30:48] S1: It's so interesting how AI is coming at the middle of so many things. It's coming at the middle of the product development process. It's coming at the middle of seniority. There's probably other examples. And I'm guessing this is true for all functions, like PMs designers too, just new PMs designers, maybe because being AI native basically is what you're describing and ramping up much more quickly. I guess while we're on this topic, a lot of listeners here are just like those people in the middle. What would your advice be to them to help them avoid becoming a part of the permanent underglass?
00:31:22 · Simon Willison
[00:31:22] S0: That's a big responsibility you're putting on me there. I think the way forward is to lean into this stuff and figure out how do I help this make me better? A lot of people worry about skill atrophy. If the AI is doing it for you, you're not learning anything. I think if you're worried about that, you push back at it. You have to be mindful about how you're applying the technology and think, "Okay, I've been given this thing that can answer any question and often gets it right, doesn't always get it right. How can I use this to amplify my own skills, to learn new things, to take on much more ambitious projects?" Something I've been enjoying, I think the thing I've enjoyed most about this as a software engineer is that my level of ambition has shot right up because now, I never used AppleScript because AppleScript is a whole programming language you have to learn. And I've been using AppleScript for like two and a half years now because ChatGPT knows AppleScript and so now I can automate things on my Mac and that's great. And previously, the fact that it would take me two or three months to learn basic AppleScript was enough for me never to use it. And now I've got all of these technologies that I'm using because that two to three month initial learning curve has been shaved right down. I think that applies to everything else. I'm getting much better at cooking. I've been using Claude, it turns out, excellent chef, which doesn't make sense because it doesn't have taste buds, but it can give you the global average of the world's guacamole recipes, which turns out is good guacamole. So that's been really interesting, like trying to apply this stuff just for sort of self-improvement. I think that's a really useful skill to have because honestly, everything is changing so fast right now. The only universal skill is being able to roll with the changes. That's the thing that we all need. Weirdly, the term that comes up most in these conversations about how you can be great with AI is agency. People, human beings have agency and we use that agency to decide what problems to take on and where to go. I think agents have no agency at all. I would argue that the one thing AI can never have is agency because it doesn't have human motivations.
00:33:35 · Simon Willison, Lenny Rachitsky
Sure, you can tell it, "Make more money," or whatever, but it's never going to be able to decide on what makes sense for it to act on next. So I'd say that's the thing is to invest in your own agency and invest in how do I use this technology to get better at what I do and to do new things. [00:33:53] S1: And also to your point, be ambitious. Think big. [00:33:56] S0: Yeah. [00:33:56] S1: There's an interview with Jensen that just came out yesterday where people asked him about layoffs. There's all these layoffs happening. Is AI actually taking jobs? And he's like the reason a lot of these companies are letting people go is they don't have enough creativity or ambition for what they can do with all of these resources there, because they're not letting people go. They have so much they want to do. And obviously easier said than done and it's not always the case, but I think that's an interesting way of approaching. And now that we have this power, people almost underestimate what they can do with it and don't fully lean into it. So I love this advice of just try to be a little more ambitious, try to stuff that you think is impossible and see it might be actually possible. [00:34:32] S0: My New Year's resolution this year was the opposite. Every previous year, I've always told myself this year, "I'm going to focus more. I'm going to take on less things." This year, my ambition was take on more stuff and be more ambitious. We've got these tools. Bring it all in. Let's try and do everything. I don't know if that was a good New Year's resolution, but that's what I went with.