Monorepos May Not Be the Ideal Setup for AI Coding Agents After All

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A developer who once championed monorepos for AI-native development has revised that view after observing how coding agents actually operate in large, shared repositories. The core appeal was 'context closure' — keeping code, tests, and design decisions in one place so agents could work without human interruption. However, attempts to introduce a shared agent harness revealed a deeper organizational problem: teams had already built their own overlapping agent workflows, making centralization a disruptive migration rather than a simple setup. Centralizing too early risks standardizing poorly designed systems, while waiting too long lets local workflows become too entrenched to replace. With newer long-running models now capable of searching and coordinating across multiple repositories, the monorepo's boundary is no longer the decisive capability advantage it once was.

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