Technical Task Router

The Technical Task Router predicts the optimal combination of AI agents to complete a technical task successfully within a specified budget. Given a structured task description and execution constraints, the model selects the best planner, coder, reviewer, and execution depth based on historical outcomes from real software development workflows executed through wavemill.org and soon other agents. Unlike static model selectors, the router continuously improves as more workflows are completed and evaluated. The model learns which combinations of AI systems perform best across different languages, repositories, task types, and complexity levels, enabling teams to reduce AI costs while improving reliability, autonomy, and development throughput.