The opportunity
Modern coding agents are powerful but still need a conductor — someone to decide what starts next, avoid overloading the repo, notice blocked tasks, run a review pass, route fixes back, and merge finished work. That orchestration is exactly the mechanical overhead that pulls a developer out of the creative, high-leverage part of the job.
The hypothesis
If the conductor itself is made programmable and autonomous — with an AI agent as the worker behind every step — a prioritized backlog becomes a living assembly line: issues → implementation → PR → self-review → fixes → squash merge. The developer expresses intent and reviews outcomes; the loop handles the handoffs, rebases, and CI fixes in the background.
Current state → future state
| Current state | Coding agents produce work but each handoff — start, review, conflict, CI, merge — needs a human babysitter. |
| Problem / pain | Mechanical orchestration breaks creative flow and caps how much an agent fleet can actually ship. |
| Who is affected | Solo developers and small teams running agentic development. |
| Impact focus | Throughput · flow · forward momentum. |
| What success looks like | Unblocked issues are picked up, implemented, reviewed, fixed, and merged automatically; only finished work accumulates. |
| What would improve | The developer stays on intent and architecture while the loop pulls weight in the background. |
| Constraints & risks | A manual label keeps any issue or PR under direct human control; merges are squash-clean with closing references preserved. |
How impact is measured
- Autonomous merge rate — issues taken from open to merged without human intervention.
- Human touch-points per change — how often a person must step in per shipped unit.
- CI-fix turnaround — time from a failing check to a pushed, passing fix.
Why it’s a Lab case
It is a governed, measurable bet on developer leverage — and the conductor pattern generalizes: any repository with a well-formed backlog can adopt the same self-driving loop, making it a reusable delivery-operations capability rather than a one-off script.
The exact system may be different. The pattern is what matters: a real workflow, a measurable pain, and a bounded first proof point.
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