The quality of AI-assisted software depends on unit of work management

And the value of AI as pushed to us by these companies is in doing larger units of work.

But... reviewing code is harder than writing code. Expressing how I want something to be done in natural language is incredibly hard.

So over time I'm spending a lot of energy in those things, and only getting it 80% right.

Not to mention I'm constantly in this highly suspicious mode, trying to pierce through the veil of my own prompt and the code generated, because it's the edge cases that make work hard.

The end result is exhaustion. There is no recharge. Plans are front-loaded, and then you switch to auditing mode.

Whereas with code you front-load a good amount of design, but you can make changes as you go, and since you know your own code the effort to make those are much lower.

I somewhat dread code reviews. In order to properly evaluate the solution, you must first know what is the right solution to begin with. You must analyse the problem and arrive at it yourself. This is the brunt of the work, and yet you are not allowed the pleasant part of it: knowing that your work is shipped and feeling pride in it.

Working with LLM-generated code is mostly the same. The more sophisticated the autocomplete, the more mental overhead spent on understanding its output. There is an advantage: you are spared having to argue with a possibly defensive peer about what you believe is best. There is also a disadvantage: you do not feel like you are helping someone grow, and instead you are an unpaid (you are not paid for that in particular) contributor to a product by Microsoft (or similar) intended generally in longer term to push you and/or your peers out of the job. Additionally, there is no single mind that you can build rapport with and learn to understand the approaches and vibes of after a while.