Yeah, flow state is not the same, and I miss it.

I've stumbled into a couple of different ways to work with AI, each with their advantages and disadvantages:

* Ask it to solve the issue and trust the results. You're outsourcing your thinking, and lose understanding of the code. The result might work, or it might not. Chances are it will work, but your code slowly grows messier.

* Ask it to solve the issue and review the results. This should help you understand the resulting code, and give you a better chance of setting the AI straight when it messes up. But you're still outsourcing your thinking, and not thinking of the solution yourself still means you lose touch with the code. But more importantly, reviewing is the boring part of software development.

* You write the code, and let the AI review it. In a way, I think this should be the sweet spot. It doesn't make you faster, but your quality should go up. AI is very good at reviewing, and often finds issues that humans skip over. This is the quality over quantity solution. More than code, I think this is particularly important for writing high-stakes non-code documents, like financial reports for customers. Quality is really important there.

* You tell the AI how to solve the issue. The AI still writes the code, but it receives tighter guidance from you. This is what I usually end up doing. I like to think this results is better code. It certainly gives me the impression I understand better what the code does. And I do tackle much larger amounts of code, but I check what the AI does, and often push back on its suggestions and assumptions. I think this is a nice middle ground between speed and quality.

* Full agent mode. Let the AI do everything. Let multiple agents work simultaneously doing everything. You lose control and your mental model. You're going to have to trust whatever the AI is doing. Something it will be correct, sometimes not. Let's hope you never have to personally touch that code anymore. But it sure is fast.