Developer Uses Parallel AI Agents to Document a Debt-Ridden, Undocumented Codebase

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A software developer shared how they tackled the challenge of documenting a heavily indebted, undocumented codebase that had grown from a poorly built MVP. The core problems included duplicated business logic, obsolete database columns, and implicit dependencies that confused AI coding assistants. Drawing on a Meta research article, the developer implemented a parallel-agents workflow where multiple AI agents analyze the codebase simultaneously across defined business domains such as orders, payments, and billing. Each agent follows a structured 'compass' approach, extracting key files, non-obvious patterns, quick commands, and cross-references rather than generating generic filler documentation. The goal is to make implicit architecture explicit, giving future AI development agents accurate context and constraints before they begin making changes.

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