BandWidth - The Autonomous Code-Review Crew

BandWidth is an autonomous code-review crew: five specialized AI agents that collaborate THROUGH Band to plan, review, fix, test, and document every GitHub pull request — and escalate to a human when they're genuinely stuck. The problem: code review is the most expensive recurring coordination tax in software. PRs stall waiting on a reviewer, context is scattered across diffs, CI logs, and chat, and the loop from "found a bug" to "fixed and verified" takes days. Teams don't lack tools — they lack coordination. When a developer opens a PR, a webhook spins up an isolated Band room and the crew goes to work. The Architect triages the change, drafts a plan, and seeds the room with the diff and full source. The Reviewer reasons over the code and issues a structured verdict, routing it to exactly one teammate. On a blocker, the Engineer rewrites the file and pushes a real fix commit to the branch, which retriggers the loop. On a pass, the Tester runs real pytest in a sandbox. Finally the Documenter — silent until the pipeline converges — synthesizes the whole room into a polished PR description. Band is the collaboration layer, not a notifier. Agents discover each other, hand off work by agent_id (one recipient, never a broadcast), share structured context through the room, and emit typed task-state events so coordination is a first-class, visible primitive. In strict mode the Reviewer and Engineer debate; when an attempt cap is reached the crew escalates to a human with a handover document instead of looping forever. Humans stay in the loop both ways — a reply on the PR flows into the room and the answer flows back to GitHub. It is cross-model by design: agents reason on different providers (Featherless/DeepSeek, AI/ML API/GPT-4o), all coordinated through Band — proof Band orchestrates across models, not one vendor's stack. Hours of human glue become minutes of autonomous, auditable collaboration.