Factory.ai Missions: multi-agent architecture for autonomous multi-day software development
Single-agent AI sessions degrade in quality as scope broadens because irrelevant context accumulates in the trajectory, and an agent that has already implemented something is biased when evaluating its own work.
A single Missions run produced a full Slack clone across six milestones, generating 38.8k lines of code with 89.25% statement coverage; validators surfaced 81 issues resolved through 21 targeted fix features, with every milestone converging in 2-4 validation rounds.
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Frequently asked questions
What did this team achieve with this AI workflow?
A single Missions run produced a full Slack clone across six milestones, generating 38.8k lines of code with 89.25% statement coverage; validators surfaced 81 issues resolved through 21 targeted fix features, with eve…
What tools did this team use?
Droid.
What results were reported?
Validation share of total runtime: 37.2%; Lines of code generated: 38.8k; Test lines share of total code: 52.5%; Statement coverage: 89.25% (source-reported, not independently verified).
How is this quality assurance AI workflow structured?
User submits goal → Orchestrator writes validation contract → Feature and milestone decomposition → Workers implement per feature → Milestone validation triggered → Scrutiny and user-testing validators evaluate → Orchestrator creates fix features loop → Blocked mission handed to user.