TemporalShy Ruparel5 min readintermediate
The “cool new stuff” trap
Summary
The author attempted to use an AI agent to convert STL files into editable CAD, but discovered that rigorous validation and objective measurement of output quality were far more effective. The project succeeded by focusing on generating and inspecting candidates against clear metrics, rather than relying on the agent's 'cleverness'.
- Rigorous validation and objective metrics are more critical than 'clever' AI planning for complex engineering problems.
- AI is useful for exploration and scaffolding, but not a substitute for defining and measuring output quality.
- Aggressively simple architectures with strong validation often outperform complex agentic loops.
- Define 'good' with objective metrics (e.g., editability scores, deviation checks) before attempting system improvements.
Engineers considering AI for complex, multi-step problems should prioritize defining measurable success criteria and robust validation over relying on agentic planning.
7/10
