Side quest · In daily use · Still in development
Agentic Agile, simple and easy.
Kantan is a deliberately small kanban board and shared knowledge base that I run by talking to Claude. The AI does the process work: planning, tracking, remembering decisions. I steer.
簡
Why I built it
I'm good at juggling several projects at once. I actually like a bit of chaos. But I'm now past a dozen projects, and I needed two things: a way to keep track of all of them, and a way to switch between Claude instances without losing what we'd already worked out.
Kantan is a good example of the problem. I started it in the Claude app on my Android phone, at the gym. Its code is now managed by a Claude in PyCharm. And the Claude in WebStorm needs to know all about it too, so it can keep this website up to date without me explaining everything again.
I also never found an Agile tool I loved. Jira is fine, but it has a thousand more features than I need. I wanted the basics: me and my AI chatting and planning, building up features and tasks, with a way to see them, organized by product and project.
What makes it different
Agent first. The board is there so I can see the work. Most of the time I run it by talking to Claude.
One memory, every Claude. Any Claude on any device gets up to speed on a product with a single call.
Knowledge lives in docs, not tickets. Briefs, specs and decision records are versioned, and Claude keeps them current.
Everything can be undone. Every AI action is logged with who did it, and one click reverses it.
The AI wears the hats
The process overhead that makes big tools heavy is handled by Claude. I make the calls.
01
Project manager
Creates products, projects with goals and dates, and tasks. Tracks project health and reports progress.
02
Scrum master
"What should I work on tonight?" "What's blocked?" Moves tasks across the board and runs the weekly review.
03
Senior architect
Keeps each product's brief, specs and decision records up to date, so the reasoning survives the conversation.
04
The coders
Claude coding agents in Xcode, Android Studio, PyCharm and WebStorm load a task's context in one call and report back.
Things I actually say to it
“Planning session for Axel: the next release, two weeks.”
“What's at risk across everything?”
“What did we decide about backups for Ripple?”
“Undo what you just did.”
In use
What it runs on
Kantan isn't built for scale, and it doesn't need to be. It's built for quick iteration and low cost, so I can develop it fast: one small server, one database file, no build step.
Like everything else here, it was built by one person, working with Claude.
App
Python and FastAPI. The whole web UI is a single file of vanilla JavaScript.
Data
SQLite, with full-text search across docs, notes and tasks. Nothing is ever hard-deleted.
AI interface
An MCP server with about 33 tools, so Claude on the web, phone, desktop and in my IDEs can all use it.
Sign-in
Password plus authenticator code in the browser. OAuth with a consent screen for Claude apps.
Hosting
One small AWS Lightsail server, HTTPS only.
Backups
The database streams continuously to encrypted storage, so there's no nightly job to forget.
What's next
Planned
Chat inside Kantan
Talk to Claude in a panel next to the board and watch it change as you talk.
Planned
Proper branding
A finished 簡単 wordmark and icon set to replace the working look.
Planned
Friends-and-family beta
Letting a few people I trust use it, once it's safe to.
Curious how it works?
Kantan is still in development, and for now it's a tool I built for myself. If you're doing something similar with AI agents, I'm happy to talk about it.