Developer finds validation logic beats AI cleverness in STL-to-CAD conversion tool

A developer built an AI-powered agentic tool to convert STL mesh files into genuinely editable CAD models, frustrated that existing workflows still require tedious manual rebuilding. The project used Temporal to make the agentic loop durable, allowing it to retry failed geometry operations and preserve progress across long runs. However, the developer discovered that AI judgment alone was not enough to improve output quality — the real breakthrough came from rigorous validation, where every candidate STEP file was measured against geometric checks before being accepted. Rather than relying on the agent to reason its way to better results, the converter was redesigned to generate candidates, validate them against strict criteria, and discard anything that failed. The lesson drawn was that in geometry-heavy workflows, measurable evidence and structured validation outperform open-ended AI planning.