hmem-using-hmem

To enforce consistent memory and dispatch workflows, apply a policy-driven framework that loads mandatory habits at session start, ensuring reliable memory, dispatch, and lookup operations across all interactions.

The dispatch-first rule for context management requires always dispatching before searching, looking up, or exposing new information to ensure prompt hygiene and prevent context leakage during ongoing interactions.

You can guide AI decisions for recalling and writing context by using a structured decision table, which provides explicit guidelines on when to trigger recall, write, or create actions for handling knowledge and context.

Yes, you can use hmem primitives to manage AI session context by loading required context at session start and utilizing hmem-dispatch, hmem-recall, and hmem-write to govern memory and lookup habits.

The best way to prevent context leakage in AI workflows is to establish a consistent, policy-driven approach that applies mandatory memory, dispatch, and recall habits during both session initialization and ongoing interactions.

Yes, you need to load context at session start for memory management because it activates the mandatory habits required to govern memory, dispatch, and lookup operations throughout the entire session.