I honestly feel like you're making this sound more complicated than it needs to be. I get what I would describe as very good results from GPT 5.6 on my projects.

There are some methodologies that can improve things for me versus just YOLO'ing but even these are of marginal benefit:

* Have good requirements. Experience with a codebase and stakeholders helps a lot here.

* Correctly subdivide the task into chunks that won't blow context. You can write a big task and have an agent plan subtask delegation for you, but it's good to have some intuition of your own.

* Perform an automated code review. This is a no-brainer but it catches stuff.

* Make sure you understand the "big picture" stuff and stop caring about the little details. The agents will write unit tests, so you shouldn't have to care about reading every LOC, you can ask the agent to describe the architecture and flow instead.