Developer Shares a Method for Coping with Overload When Working With AI Agents
Developer Sergey Kuhne describes in a blog post a work system meant to prevent burnout when juggling many AI tool tasks at once. It rests on a task queue stored in a git repository and a single place for decisions.
Software developer Sergey Kuhne has described, on his blog, a method for reducing mental fatigue when working with the AI coding tools Claude Code and Codex from the terminal. The post drew attention on the tech news site Hacker News, where it scored at least 150 points.
The problem
The author says work with such tools easily turns chaotic. While the AI answers one task, he starts another, then clarifications, follow-up questions and side tasks appear, each opening its own tab. Eventually he is hopping between around 20 threads and trying to hold every context in his head, until his focus collapses. Others recommend taking breaks, thinking before typing and limiting scope, but he chose a different route. He sees the two main problems as sequencing and context.
The solution
The task queue lives in a git repository. Each ticket is a markdown file placed next to the code it concerns, and the state of the board is a committed snapshot. Nothing important stays in a chat window or in the author's memory, so a session dying loses nothing.
An AI agent works through the board in cycles: it researches new tickets, builds those a human has tagged as safe to build, runs tests and a browser check, and verifies what is already deployed. For sensitive code it builds on a separate branch and asks first. It never deploys to production; the author does that himself.
The agent cannot make decisions. Everything that needs human judgement therefore lands in one place, which he calls the owner inbox. A script reads the whole board and produces a prioritised list. For review he uses a Claude artifact: a single page rebuilt from git on every cycle, which also contains a review page for each ticket. His verdict is written back into git, onto the ticket card.
The key principle
The author takes one item, loads its context, makes a decision or requests an action, and closes it by returning it to the queue. The context closes together with the ticket, so he can focus on the next one. The work is still exhausting, he says, but he no longer feels distracted or lost. The ongoing challenge is tooling that cuts context loading to a minute, and preventing tickets from looping while they wait for a ruling only he can give.
