I'm a day late and I see so much advice here, but I see little mention of what made the most difference to me: lean into TDD.
Building tests first has always been a strong methodology, but with AI support its both far less work AND you get double dividends, because your test becomes the spec the AI needs to follow but it's an executable, verifiable one. So as you give it more requirements, it's automatically finding and fixing its mistakes along the way.
In terms of having it code how you like: nothing beats putting examples into AGENTS.md / CLAUDE.md etc. Give it some examples of how you like it, and say this is how the code is written. Make remarks about why as well, put the design philosophy in too.
Building tests first has always been a strong methodology, but with AI support its both far less work AND you get double dividends, because your test becomes the spec the AI needs to follow but it's an executable, verifiable one. So as you give it more requirements, it's automatically finding and fixing its mistakes along the way.
In terms of having it code how you like: nothing beats putting examples into AGENTS.md / CLAUDE.md etc. Give it some examples of how you like it, and say this is how the code is written. Make remarks about why as well, put the design philosophy in too.