quality_assurance · saas · workflow
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.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User submits goal
A user describes what they want built, and the orchestrator investigates and asks clarifying questions until requirements are unambiguous.
Tools used
Droid
Outcome
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.
Results
Time saved37.2%
Volume38.8k
Grounding & classification
Source type: technical build writeup
29 fields verified against source quotes.
agentic workflowai agentcode generationmulti agent workflowcode diff prhuman review describedmetric backedproduction runtime claimedtools describedworkflow describedsoftwareaccuracy improvementerror reductiontechnical build writeupquality assuranceagentic task executionai draft human approval