Amen. Context is king, and managing context well is key to proper AI assisted coding. Also, staying accountable for the final output, as you stated in the end.

Not having good (or any in most cases) context management techniques is like saying your car is slowing you down because you have to push it everywhere you go.

I use NotebookLM to manage project context, and do scoping, planning and requirement elaboration which gets copied to Jira tickets (similar to what you explained in the first part) . On the coding side I use Claude Code with the Jira MCP. I use the copy-pasting between project and code domains to correct any mistakes AIs might have introduced. We developed a plugin which captures our engineering best practices and instructs the AI agent to discuss every aspect of the implementation and the task breakdown with the developer before writing any code or tests, as well as to keep a local progress tracker file for every ticket which also serves to capture any insights that emerged during the discussion. This file serves as long term memory between chat sessions, and also gets committed for future reference by humans and AI alike. And I always do a thorough self review towards the end.

I’m convinced beyond doubt coding without modern AI assistants and not gaining experience with them is a mistake. Resist the knee-jerk reaction to downvote comments which give you blueprints to evolve you practice because you have antipathy for AI. I don’t care about the little number at the top of this comment, but I think everyone should start learning and developing new techniques to improve their workflows.