Dylan Patel: belief

Transcript context

…There’s a lot of fear and angst too from current CS students, but that is the area where probably the most AI revenue and productivity gains have come, right? Whether it be Copilots or Cursor or what have you, or just standard ChatGPT. I know very few programmers who don’t have ChatGPT and actually many of them have the $200 tier because that’s what it’s so good for. I think that in that world, we already see it like SWE-bench. And if you’ve looked at the benchmark made by some Stanford students, I wouldn’t say it’s really hard, but I wouldn’t say it’s easy either. I think it takes someone who’s been through at least a few years of CS or a couple years of programming to do SWE-bench, well, and the models went from 4% to 60% in a year, and where are they going to go to next year? It’s going to be higher. It probably won’t be a hundred percent because again, that nines is really hard to do, but we’re going to get to some point where that’s, and then we’re going to need harder software engineering benchmarks and so on and so forth. But the way that people think of it now is it can do code completion. Easy. It can do some function generation. I have to review it. Great. But really the software engineering agents I think can be done faster sooner than any other agent because it is a verifiable domain. You can always unit test or compile, and there’s many different regions of it can inspect the whole code base at once, which no engineer really can. Only the architects can really think about this stuff, the really senior guys, and they can define stuff and then the agent can execute on it. So I think software engineering costs are going to plummet like crazy. And one interesting aspect of that is when software engineering costs are really low, you get very different markets. So in the US, you have all these platform SaaS companies, Salesforce and so on and so forth. In China, no one uses platform SaaS. Everyone just builds their own stack because software engineering is much cheaper in China and partially because people, number of STEM graduates, et cetera. So it’s generally just cheaper to do. And so at the same time, code LLMs have been adopted much less in China because the cost of an engineer there is much lower. But what happens when every company can just invent their own business logic really cheaply and quickly? You stop using platform SaaS, you start building custom tailored solutions, you change them really quickly. Now all of a sudden your business is a little bit more efficient too, potentially because you’re not dealing with the hell that is. Some random platform SaaS company stuff not working perfectly and having to adjust workflows or random business automation cases that aren’t necessarily AI required. not dealing with the hell that is. Some random platform SaaS company stuff not working perfectly and having to adjust workflows or random business automation cases that aren’t necessarily AI required. It’s just logic that needs to be built that no one has built. All of these things can go happen faster. And so I think software and then the other domain is industrial, chemical, mechanical engineers suck at coding just generally. And their tools like semiconductor engineers, their tools are 20 years old. All the tools run on XP including ASML lithography tools run on Windows XP. And a lot of the analysis happens in Excel, right? It’s just like, “Guys, you guys can move 20 years forward with all the data you have and gathered and do a lot better.” You need the engineering skills for software engineering to be delivered to the actual domain expert engineer. So I think that’s the area where I’m super-duper bullish of generally AI creating value. The big picture is that I don’t think it’s going to be a cliff. I think a really good example of how growth changes is when Meta added stories. So Snapchat was on an exponential, they added stories, it flatlined. Software engineers then up until the right, AI is going to come in, it’s probably just going to be flat. It’s not like everyone’s going to lose their job. It’s hard because the supply corrects more slowly. So the amount of students is still growing, and that’ll correct on a multi-year, like a year delay, but the amount of jobs will just turn and then maybe in 20, 40 years, it’ll be well down. But in the few years, there’ll never going to be the snap moment where it’s like software engineers aren’t useful.…

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