The objective
SkunkWorks explores a local production assistant with retrieval, job tracking, code fixtures and asset workflows. The business ambition is to build a professional AI-assisted studio, not to call every automation an autonomous employee.
What the later handoff records
A local application and limited Blender fixtures were exercised. Existing model weights powered local answers. Both evaluated language models made factual or citation errors that required review.
A failure worth preserving
The neural mesh pilot ran, produced geometry and was rejected for poor shape fidelity. Neural images and rigging still had dependency or resource blockers. Successful execution was not accepted asset quality.
How to measure the advantage
Track cost per accepted asset, iteration time, quality and player response. A faster rejected mesh is not a studio advantage. Engine testing and user acceptance remain separate gates.
Evidence & perspective
- SkunkWorks local application handoff
Local application and limited fixtures were exercised. A neural mesh pilot was rejected; neural image and rigging capabilities have blockers. No new model training or proven vendor superiority.