Project Management

Stop Updating Your Task Board by Hand After Every AI Session

The agent finished the task; now you drag the card, type the status, add a note. Why a hand-kept board drifts from reality, and how to let the repo drive it.

By Tu Nguyen · · 2 min read.md

A developer writes in a notebook next to two monitors, copying task status from one place to another.

The agent finishes the feature. You review it, it’s good. Now the other job starts: open the board, find the card, drag it to “Review”, type a note about what changed, update the checklist, set the next task to “In progress”.

Five projects, several sessions each, every day. Part 4 of Working for the AI — the board you keep for a robot that could keep it itself.

The board becomes a second job

A separate task board asks for one thing: that you tell it what happened. Every time. With agents doing more of the work, “what happened” changes more often, so the board asks for more of your time.

And the day you’re too busy to update it, it starts lying. A week later it describes a project that no longer exists. You stop trusting it, and it becomes one more tab you don’t look at.

The agent already knows the status

At the end of a task, the agent knows exactly what it did, what’s left and what went wrong. The status exists — it’s just in the wrong place, the chat.

So ask for it in the right place. End each task with:

“Update progress.json: set the phase, write the next step, and add a note if anything is stuck.”

Now the status is written by the one who did the work, at the moment it happened, in the repo.

Read the board, don’t write it

If the status lives in a file in each repo, the board doesn’t need to be typed. It can be read from the files. That flips the relationship:

Hand-kept board Board read from the repo
You update it after the work The agent updates the file during the work
Drifts when you’re busy Is exactly as current as the repo
Lives in a separate tool Lives next to the code, in git
One more thing to keep in sync Nothing to keep in sync

This is the same principle as memory living in files: the source of truth sits where the agent can read and write it.

Keep the file small and structured

The status file doesn’t need to be clever. One entry per task:

{ "name": "store listing", "phase": "5/6", "next": "captions for 3 screenshots", "stuck": null }

Phase, next step, and a stuck reason when there is one. Structured enough that a tool can read it, short enough that you can read it too.

Your part: a quick check

You’re still the reviewer. Once a day, glance at the phases and next steps. If one looks wrong, fix the file or ask the agent to. That’s a minute, not a second job.

Where ShotMatic fits

ShotMatic is a board that reads instead of asking you to type. Your agent writes progress.json in each repo; ShotMatic shows every task as one line with its phase, next step and stuck status. The first-run wizard writes a starter file and a prompt so your agent keeps it up to date.

FAQ

Why does my kanban board never match what's actually done?

Because updating it is a separate manual step. On busy days you skip it, and after a few skips the board describes last week.

Can an AI agent update project status automatically?

Yes. Ask it to update a status file in the repo at the end of each task — phase, next step, notes. The agent knows what it just did better than anyone.

Do I still need a project management tool?

For solo work, often not a separate one. A structured file in each repo plus something that reads all of them is enough to see every project at a glance.