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Cognition founder Scott Wu says most software never gets built because the economics don't work: "The math only really works out to create software if it's going to be used at least a million times or something. Maybe it's 10,000 times or whatever." "You need that software to be...

37,919 views • 3 months ago •via X (Twitter)

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Scott Wu (Scott Wu) on what programming will look like in the future: “All programming really comes down to is how do you tell your computer what to do? For every single piece of software that you use, some team of engineers came together and thought through all these details of, "Okay, here's what I want it to do. Here's how I want it to look. Here's what I want this button to do. Here's how I want to architect it." Every single little decision was made by somebody. And the computer is then executing it according to the wishes of its creators. At this point you don't need to know a programming language. You don't need to know Python or Java or something like that in order to build your own software. You can just say, "Hey, here's what I want. I wanna make a cool website that does this and that." Or in my existing product, "Here' what we have today, and I wanna change this thing or add this new feature," and just have the agent go and do that for you. I think we're gonna continue to go further down that axis. I think we'll start to see that abstraction will continue to climb. I think what we'll see a lot more of in the near future is making a piece of software which you're going to use one time and never again. To create software today the math only really works out if it's gonna be used at least a million times or something. Maybe it's 10,000 times or whatever. My point is if you wanna go build a product today, you need a whole team of engineers. Engineers are expensive. You need that software to be used enough times to create enough value for that to be worth it. But there are so many things out there which are very specific things that only need to be used a few times, or even only once. There’s all of these things that could be done with software. It just obviously doesn't make sense to hire a whole team of people to go make you that piece of software, which you're gonna use one time and never again. We're gonna get to a point where you are just giving your instructions to your agent, and the agent is gonna figure out, okay, I'm gonna write this code that's gonna go do this. I'm gonna put a script that automates this part etc. and that's what's gonna allow [single use software]. What [this is all about] is really just how you control your computer and how you get it to do what you wanna go do. You’ll wake up in the morning and you’ll talk to your agent about it. The agent does the literal writing of the code and you're the one that's deciding what to do.”

David Senra

12,855 views • 3 months ago

Is Traditional Software Engineering Dead? “Does this mean that traditional software engineering is dead? Absolutely not. Software engineers—even the ones who are not necessarily tuning or training AI models—these are now among the most leveraged people on earth. Sure, the guys who are training and tuning models are even more leveraged because they’re building the tool set that software engineers are using. But software engineers still have two massive advantages on you. First, they think in code, so they actually know what’s going on underneath. And all abstractions are leaky. So when you have a computer programming for you—when you have Claude Code or equivalent programming for you—it’s going to make mistakes. It’s going to have bugs. It’s going to have suboptimal architecture. So it’s not going to be quite right. And someone who understands what’s going on underneath will be able to plug the leaks as they occur. So if you want to build a well-architected application, if you want to be able to even specify a well-architected application, if you want to be able to make it run at high performance, if you want it to do its best, if you want to catch the bugs early, then you’re going to want to have a software engineering background. The traditional software engineer is going to be able to use these tools much better. And there are still many kinds of problems in software engineering that are out of scope for these AI programs today. The easiest way to think about those is problems that are outside of their data distribution. For example, if they need to do a binary sort or reverse a linked list, they’ve seen countless examples of that, so they’re extremely good at it. But when you start getting out of their domain—where you have to write very high-performance code, when you’re running on architectures that are novel or brand new, when you’re actually creating new things or solving new problems, then you still need to get in there and hand code it. At least until either there are so many of those examples that new models can be trained on them, or until these models can sufficiently reason at even higher levels of abstraction and crack it on their own… And remember: there is no demand for average. The average app—nobody wants it, at least as long as it’s not filling some niche that is filled by a superior app. The app that is better will win essentially a hundred percent of the market. Maybe there’s some small percentage that will bleed off to the second-best app because it does some little niche feature better than the main app, or it’s cheaper, or something of the sort. But generally speaking, people only want the best of anything. So the bad news is there’s no point in being number two or number three—like in the famous Glengarry Glen Ross scene where Alec Baldwin says, “First place gets a Cadillac Eldorado, second place gets a set of steak knives, and third place you’re fired.” That’s absolutely true in these winner-take-all markets. That’s the bad news: You have to be the best at something if you want to win. However, the set of things you can be best at is infinite. You can always find some niche that is perfect for you, and you can be the best at that thing. This goes back to an old tweet of mine where I said, “Become the best in the world at what you do. Keep redefining what you do until this is true.” And I think that still applies in this age of AI.”

Naval

863,914 views • 7 months ago