SYSE.45:1 - Problem frame

Use this when a recurring task warrants changing model parameters or adapters, and qualified interaction experience can teach the targeted behavior. Repeatedly supplying stable guidance may be costly; an existing policy may also keep making a consequential mistake.

The subject is the trained policy candidate and the experience, learning mechanism and retained support that make its changed behavior interpretable. The first useful result is a changed candidate with a bounded comparison, or the precise data, training or evaluation gap.

Compare training with retaining help, improving retrieval, constructing a tool or repairing the external controller. Selecting or transforming the next input belongs to SYSE.52, routing and return consumption to SYSE.47, and external recording to SYSE.43. If training is unavailable, those feasible alternatives remain available. Human practice and learning use E.23.CDI/HCD with their own mechanisms. This pattern supplies a bounded machine-policy intervention; foundation-model pretraining and the receiving domain’s correctness criterion remain external.