I threw Claude Code at an existing codebase a few months back and quickly quit— untangling its output was slower than writing from scratch. The fix turned out to be process, not model horsepower.

Iteration timeline

==================

• 50 % task success - added README.md + CLAUDE.md so the model knew the project.

• 75 % - wrote one markdown file per task; Codex plans, Claude codes.

• 95 %+ - built Backlog.md, a CLI that turns a high-level spec into those task files automatically (yes, using Claude/Codex to build the tool).

Three step loop that works for me 1. Generate tasks - Codex / Claude Opus → self-review.

2. Generate plan - same agent, “plan” mode → tweak if needed.

3. Implement - Claude Sonnet / Codex → review & merge.

For simple features I can even run this from my phone: ChatGPT app (Codex) → GitHub app → ChatGPT app → GitHub merge.

Repo: https://github.com/MrLesk/Backlog.md

Would love feedback and happy to answer questions!

Like the idea of a self hosted kanban in git, one item you should do in your repo is add the installation instructions to the readme :)

I see its a TS app so I am sure the bun bundle is the install, but always good to include in your 5 min intro.

Is there an alternative that integrates with a Jira instance?

Many of my tasks already exists in forms of a Jira ticket, would be interesting to prompt it to take over a specific ticket & update its ticket progress as well.

Brilliant! Thank you for sharing.

Had similar success with making some more markdown files to help guide the agent but never would have thought of something this useful.

Will try your workflow and backlog on a build this week.

Ooh, definitely trying this out! I ended up homebrewing a whole context maintainance ritual, but that was a pain to get an AI agent to consistently apply, so it spun out into building a whole project management... thing.

This looks much more thought out, thanks for sharing!

Really nice! Have you thought of interfacing with the todo.txt ecosystem?

That's look fascinating. I will certainly be testing it in the morning! Thanks!

Seems like a great idea. How would that work with multiple branches ? One task might be implemented in a different branch, we might want to have a global overview of all the tasks being coded in the main branch

  All data is saved under backlog folder as human‑readable Markdown with the following format task-<task-id> - <task-title>.md (e.g. task-12 - Fix typo.md).

If every "task" is one .md file, I believe AI have issues editing big files, it can't easily append text to a big file due to context window, we need to force a workaround launching a command line to append text instead of editing a file. So this means the tasks have to remain small, or we have to avoid putting too much information in each task.

This is a good idea. But the screenshots you have show lots of tasks in a project; how are you dispatching tasks (once planned) to an agent, and how are agents navigating the large number of markdown task content you're producing without blowing out their context budget?

Can we change the title to include that this is a tool for AI? I thought it was just gonna be a visualizer.

The tagline from the repo seems fine: "A tool for managing project collaboration between humans and AI Agents in a git ecosystem"

All I'm wondering is how did you secure the .md TLD?

Part of this confusing trend of naming projects like files

I built myself a tool that does something quite similar. It's a single no-dependency Python script that parses "tasks.md" in the root of the repo which contains a Markdown table of tasks, then has basic support for BLOCKED/READY/DONE/CANCELLED, dependencies, titles, tags, etc.

For a project that is just for me, it's exactly what I need – dependency tracking and not much more, stored offline with the code. Almost all of the code for it was written by Gemini.

With aider you can run a second instance along with --watch-files and if you in your tasks do // #AI it will be added to the chat and with // !AI AI will then respond

so you can do

`backlog task create "Feature" --plan "1. Research\n2. Suggest Implementation// #AI AI!"` (yes weird order with the !)

and in the background aider will propose solutions.

I’m not sure how this compares to Claude Code or Codex, but its LLM-flexible. Downside is it doesn’t create a pull request. So it’s more helpful for local code.

I would probably add some Readme.md files to the --watch-files session and I think you need to click once [D]ont ask again so it wont keep asking you to add files

Ah, this is what the future after Jira looks like.

Would love to be able to use this UI, connected to an external source like Linear.

This is a neat implementation, personally I use https://www.task-master.dev

How is this different from taskwarrior? I feel the use cases are overlapping (which is a good thing as taskwarrior rewrite in rust is a mess)

Is there a proper way to use this project without commiting files to git ? I just want to try it out in a project I'm working on, but don't want to put it in the history.

What I did is to add the backlog folder into the .gitignore file, but after every command I get a lengthy error about a git command error.

And even if I were to add these files to my repository, I would want to add them manually.

Whatever is going on in the that GIF must be very impressive, but it goes by so fast it's impossible to tell for sure.

> Markdown-native tasks -- manage every issue as a plain .md file

> Rich query commands -- view, list, filter, or archive tasks with ease

If these things appeal to you and you haven’t already looked at it, the GitHub CLI tool gh is very useful. For instance:

    gh repo clone MrLesk/Backlog.md
    cd Backlog.md
    gh issue view 140
    gh issue view 140 --json body --template "{{.body}}"

— https://cli.github.com

You can do things like fork repos, open pull requests from your current branch, etc.

What exactly is Markdown-native?

Neat! I am going to check this out. I recently built an MCP system similar to this called Nonlinear (so clever) that uses SQLite for storage that lives outside the repo. Honestly though, in repo is the better option.

This seems tailor-made for Org mode! Seeing all those ‘To do’ and ‘Done’ reminds me of it. Did you consider building atop Org mode?

Ooh, the idea of having a CLI for the LLM to mark off tasks without having to pollute context by reading the file over and over again is cool!

Thanks for backlog.md. We love it for our project. The problem we face now is that we have two separate repo for BE (Golang) and FE (next.js). And we wanted to have one backlog for both projects. But backlog resides inside git repo.

Can you propose a neat solution of this problem?