Usually I describe the problem, explore a bit with LLM iteratively. Then I switch to creating a plan when I have enough insight (and the LLM has it in context/same session as exploration), specifying all the things I'm trying to accomplish.

Then I just iterate with LLM - I let it start writing stuff in YOLO mode and check on what it's doing in the code steering it in the direction I want.

Usually the code LLM generates will work but is kind of garbage - but I can easily steer it towards better implementations.

Sometimes using an LLM is theoretically slower than hand-rolling - if I just sat down and focused I could outperform the iteration and the waiting, especially considering how stupid agents are at running expensive builds/test suites (with a bunch of explicit instructions in skills/claude/agents.md). But the practical improvement of going with LLM is that you have a bunch of thinking traces saved as a part of your iteration proces - it's really easy to get back into flow. This is a huge productivity win for me given how many interruptions I have in my work day.