session-lifecycle

To prevent context drift in AI coding sessions, implement a structured lifecycle that actively monitors deviations from the declared intent and warns against unintended task shifts. This maintains strict focus throughout extended workflows.

Preserving AI agent state across sessions requires automated archiving and summary generation via session compaction. This ensures historical awareness and intelligence preservation by saving progress before the context window resets.

Manage AI workflow context by organizing tasks into Trajectory, Tactic, and Action levels. This hierarchical organization provides robust traceability and structures the session state from high-level goals down to specific implementation steps.

Structured session management supports plan-driven development, quick fixes, and exploratory tasks. You declare intent to set the goal, map context for implementation steps, and compact the session to save insights regardless of task scale.

AI coding assistants lose track of project goals due to unmanaged context drift over extended sessions. Without declaring intent and mapping context, the agent lacks the structured state preservation needed to maintain historical awareness.