Developer cuts AI coding agent API hallucinations 20x by adding a read-only research step

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A developer running a fully autonomous coding system on a Mac mini found that roughly 38% of task failures were caused by implementation agents inventing or misremembering library APIs they never actually checked. To fix the problem structurally, he introduced a dedicated read-only research sub-agent that investigates APIs and existing code before any implementation begins. The research agent produces a short, structured Markdown brief — including exact method names, version details, and confidence scores — which the orchestrator requires before dispatching work to the coding agent. This two-agent split, where research and implementation tools are strictly separated, reduced hallucinated-API bugs from about one in five tasks to roughly one in forty over three months. The added overhead was less than 10% of total token usage, making the tradeoff highly cost-effective.

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