Spec-Driven Development for Autonomous Agents: Inside the AI Review Plugin's Two-Stage Architecture
When software engineers collaborate with autonomous AI coding agents, the default workflow is almost always chat-and-code: describe a feature in natural language, watch the model propose a code diff, test it, and iterate. For small, single-function scripts, this works reasonably well. But for production-grade distributed systems, microservices, and multi-module architectures, this approach invariably breaks down. Left unconstrained, AI models suffer from Specification Conflation: they blur the line between WHAT & WHY (the architectural contracts, invariant boundaries, and failure modes) and HOW (the file edits, variable names, and task sequencing). The result is predictable: ...