Google Research open-sourced Harness², which lets AI agents test and improve their own prompts, tools, memory and workflows while the model stays the same. For operations teams, that points to agents that get better at a repeat job without a model swap.
Built on OpenCASCADE, it covers sketches, assemblies, drawings, static and modal FEM, topology optimization and milling output for Mach3, LinuxCNC or GRBL, all reachable from Python and over MCP. By the author's own warning, the CAM has cut real parts on only one machine.
For small machine shops and design engineers: worth a test, not a production CAM yet.
Agents tuned on three famous fields will look brilliant until they meet a fourth.
The AI proposes findings from drawings, specs and addenda, each tied to the sheet, page and quoted words, and nothing enters the scope until a person accepts it. The motto is AI interprets, code calculates, humans authorize.
For estimators and preconstruction managers: a concrete way to use AI on bid documents without letting it fill gaps with confident numbers.