Overview
A normal conversation can solve the current problem but often loses the lesson when the session ends. The user may correct the agent, explain a preference, reject an approach, or identify a recurring error. Unless that information is stored in a persistent layer, the same explanation must be repeated in a future session.
Agent mastery requires a system in which useful corrections compound. The agent should not merely fix the current output. It should improve the operating instructions that shape future outputs.
This lesson introduces four connected mechanisms:
- Persistent instruction files that are loaded at the start of a session.
- Self-modifying rules that convert corrections into durable operating knowledge.
- Agent skills that standardize repeatable workflows.
- Reverse prompting and prompt contracts that convert vague requests into executable specifications.
Together, these mechanisms turn isolated prompting into an evolving operating system.