How It Works

A minimal implementation runner performs one iteration of the loop. It collects the information the coding agent needs and starts a fresh session. The demonstrated runner supplies:

• The local issue files from the backlog.
• A small amount of recent commit history.
• A focused implementation prompt.
• Repository access under a controlled permission mode.

The prompt tells the agent to work only on AFK issues. It also defines a stop signal to emit when no eligible tasks remain. Within a single iteration, the agent:

1. Reads the backlog.
2. Selects the next valid task according to the stated priorities and blockers.
3. Explores the relevant repository area.
4. Implements the task using test-driven development.
5. Runs the required feedback loops.
6. Creates a commit.
7. Reports what was completed.

The one-iteration script is important because it exposes the agent's behavior. Before running an unattended loop, execute the single iteration repeatedly and inspect task selection, exploration, edits, tests, and summaries. Adjust the prompt when the agent chooses the wrong work, skips a feedback loop, or interprets issue metadata incorrectly.

The AFK version repeats the same fresh-session pattern. Each iteration starts from external state rather than accumulated conversation. Issues, code, tests, and commits carry the project forward. The agent does not need a single long context containing the full history.

The autonomous version also runs inside an isolated environment. The unattended version uses a sandboxed environment, while a branch or worktree preserves the resulting changes for later review and merge.