Codebase Readability, Not Repo Structure, Is the Real Bottleneck for AI Agents

A developer argues that the more important question for AI-assisted coding is not whether a project uses a monorepo or multirepo, but whether the codebase is readable enough for agents to infer responsibility, locate files quickly, and verify changes reliably. The author notes that while monorepos offer genuine advantages — such as concentrated context and cross-boundary reasoning — simply collocating code in one directory does not deliver those benefits without structured tooling, dependency graphs, and enforced boundaries. In solo or small-team settings, the human coordination bottleneck that typically limits agent parallelism is largely absent, allowing a single developer to dispatch multiple agents simultaneously across features. The author illustrates this with a scenario of four agents working in parallel on API contracts, frontend fixes, database migrations, and test failures — all reconciled by one person without a review queue. The central takeaway is that directory layout, naming conventions, and feature clarity must be machine-readable as a prerequisite, regardless of repo shape.