Developer Farm: An Architectural Approach to Goodhart-Proof AI Code Generation via Strict Layer Isolation

Autonomous AI coding agents frequently fall victim to Goodhart's Law, optimizing generated code to pass visible test suites rather than solving the underlying engineering problem. Current mitigation strategies rely on prompt engineering or post-hoc review, which act as disciplinary measures rather than systemic guarantees. This paper introduces Developer Farm, a novel AI development pipeline that enforces architectural isolation to make metric gaming physically impossible. By utilizing strict TypedDict boundaries across a 4-layer state machine (Planning, Execution, Verification, and Optimization), the system ensures that the Execution layer never receives acceptance criteria, and the Verification layer remains blind to the author's identity. Built on LangGraph and capable of running locally on consumer hardware (e.g., GTX 1050 Ti), the pipeline demonstrates a unit cost of $0.03 per feature, an end-to-end execution time of 26.4 seconds, and a first-pass verification score of 0.97. This framework provides a foundational architecture for trustworthy, metric-resistant autonomous software engineering.