I’ve made a lot of predictions about how AI will change programming. Hacking code will be less important than understanding problems, we’ll have better tools for generating code, higher-level skills will be more valuable, and so on. All of these are tied together, to some extent. If programmers spend less time writing code, they will have more canada whatsapp number data time to spend on the real problems: understanding what the code they’re writing needs to do. Our industry has done a poor job of that over the years. And they’ll be able to spend more time designing the larger systems in which their code runs. We’ve done a better job of that, but we will need to design services that can scale to more and more users while providing better security. Those systems must be observable so that problems can be detected and solved before they become crises. We’ll no doubt get better tools, and some of those tools may even help to solve those issues of software architecture. But we’re not there yet.
What’s on the other side of the coin? Better tools, less time hacking code, and more time to design useful systems all sound great. But what shadows are lurking behind the promises?
The first one is obvious. I’ve never seen a software development group that thought it was underworked. I suspect that most, if not all of them, are indeed overworked, and not engaging in ritual complaining.