Self-Taught Dev Uses Dual Implementations to Catch AI Coding Agent Bugs
A self-taught engineer transitioning from restaurant work built an evaluation framework to verify the correctness of agentic AI code. The system runs identical match-3 game logic across two independently written implementations — a React build and a Java engine — and flags any disagreement as evidence of a bug. Logic-invariant tests validated across roughly 9,000 random boards complement the differential oracle, catching errors that conventional single-implementation test suites missed. The approach is embedded in an autonomous development harness featuring a self-review loop, an independent critic, and a human-approval gate for irreversible actions. The developer has open-sourced both the dual implementations and a deliberately buggy version to demonstrate the oracle's detection capability.
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