I'm finding it to be just the opposite - futzing around in the codebase is more effective than ever, it just looks different.

My futzing around is now at a higher level and involves enlisting the help of agents to dig through the code and logs and other sources to help solves problems.

Right now I am working an effort to reduce the amount of "build friction" across our code base. Even scoping this out would have taken a non-trivial amount of time and fixing it would never have been funded. With the help of AI tools, I can now attach this problem and make the lives of hundreds of engineers better.

It's all gone if you don't take time for it, sure.

A good lithmus test I've noticed is "I want to do this thing the system should do", and if claude identifies a major refactor - well that's a sign the code needs a human touch first.

> great way to find dead code, suboptimal structures, etc. With AI that's all gone.

it's not gone, it's literally a prompt away. I run "tech debt" loops all the time, ask it to simplify the code and architecture, remove left over code from previous refactors.

the quality of the resulting code is better than ever

How do engineers internalize the codebase now? Do they just ask Claude and nod their head "because Claude said so"?