Overview
An agentic workspace should improve through use. The basic mechanism is a feedback loop: plan the work, execute it, identify what succeeded and failed, compress the learnings, and update the local instructions. Repeated patterns can later be promoted into global instructions after human review.
This creates a practical form of cumulative learning without retraining the model. Future sessions begin with better constraints, fewer dead ends, and clearer knowledge of the environment.