>the chance to think deeply about the problem, perhaps notice analogies with other processes, or more general or more efficient ways to solve the problem, perhaps even why it was necessary at all. Those are the tasty bits of the work, a little something just for me, not for my employer.

You should be aiming to use AI in a way that the work it does gives you more time to work on these things.

I can see how people could end up in an environment where management expects AI use is expected to simply increase the speed of exactly what you do right now. That's when people expect the automobile to behave like a faster horse. I do not envy people placed in that position. I don't think that is how AI should be used though.

I have been working on test projects using AI. These are projects where there is essentially no penalty for failure, and I can explore the bounds of what they offer. They are no panacea, people will be writing code for a long while yet, but the bounds of their capability are certainly growing. Working on ideas with them I have been able to think more deeply about what the code was doing and what it was should do. Quite often a lot of the deep thinking in programming is gaining a greater understanding of what the problem really is. You can gain a benefit from using AI to ask for a quick solution simply to get a better understanding of why a naive implementation will not work. You don't need to use any of that code at all, but it can easily show you why something is not as simple as it seems at first glance.

I might post a show HN in a bit of a test project I started over the Christmas break. It's a good example of what I mean. I did it in Claude Artifacts instead of using Claude Code just to see how well I can develop something non-trivial in this manner. There have been certainly been periods of frustration trying to get Claude to understand particular points, but some of those areas of confusion came from my presumptions of what the problem was and how it differed to what the problem actually was. That is exactly the insight that you refer to as the tasty bits.

I think there is some adaptation needed to how you feel about the process of working on a solution. When you are stuck on a problem and are trying things that should make it work, the work can absorb you in the process. AI can diminish this, but I think some of that is precisely because it is giving you more time to think about the hard stuff, and that hard stuff is, well, hard.