I've tried most form of planning - from the basic AGENTS.md guide to keeping ./dev/ plan files, todo list tools, sqlite db with both minimal and extensive tracking, etc.

None of them have been worth it. A year ago the models needed to be reminded. Today they can follow a plan from text alone. This is my experience from working on a project alone - in teams ... i actually think the same lesson holds in the new AI paradigm.

My current scheme is basically this - in order of the task's complexity:

- Tell an agent to do something

- Tell an agent to make a plan then tell it to execute on it.

- Tell an agent to make a plan, write to a file, have a subagent review it, then execute it.

- Do the above, but instead tell the agent they're in a supervise mode and to have subagents implement as many phases and rollover with a handoff.md while they, as the supervisor agent, keeps driving the task to completion.

The latter two i have under a sigil so they're prepared prompts i can inject with a few keystrokes.

If i feel very fancy i'll tell them to update the plan with a checklist and add checkboxes, but it just doesn't pay enough to have 'init-prompt' level planning feature or tools if in the same context you already have files/read/write.