alt Hacker NewsI'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.
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Did you read the article?
It's not about enhancing Claude. This article is about creating your own agent, and giving it the ability to create plans and tasks list for its or.
The way Claude code creates plans and tasks list for itself.
The article is about creating that in your own harness for things not using claude code, like say a custom LLM integration in your own web app.
Please don't take offense to this very dumb question:
Why can't you do the planning ? Figure out what needs to be done , break it down into small tasks and then ask the agent to execute those small tasks?
When we executed projects in the past, this is what I would do as a lead: figure out the overall software architecture and delegate the tasks to developers.
This way I always knew how the system worked and could extend it as needed. I am not in development role anymore but I am trying to understand why we are delegating planning and software architecture to coding agents?
A while back I created a tool called Jobs [0] to help with this workflow. The pattern is:
1. Have a conversation with a smart model (Opus/Fable) about what you're building. Go back & forth until you've ironed out the important architectural choices (deciding what to build).
2. Ask the model to write up its plan in a Markdown doc, including a structured plan in YAML format (telling it to consult `job schema`).
3. Clear the context and tell a leaner model (Sonnet/Opus) to read the plan doc and then pick up the task via `job status`.
From there, the CLI helps the agent take the next step. I designed the `job` CLI through extensive iteration with agents, conducting user-centered design with the agents to make it as smooth and intuitive to them as possible.
When context gets full, you can pause, clear, and pick right back up. Using Jobs (or other tools like it), you can take on large, ambitious plans and keep the agents on-task the entire time.