Feature deep dive
Context Recovery for AI Agents
Recover agent context safely after interruptions with checkpoint-based memory workflows.
Context recovery is a reliability requirement, not a nice-to-have. Agents that cannot recover lose time, confidence, and delivery momentum.
ClawVault introduces explicit checkpoint and wake commands so teams can restart with known state.
Why teams lose context
- •Interrupted sessions lose active plans and rationale.
- •Partial outputs can leave systems in uncertain states.
- •Manual recovery introduces drift and inconsistent outcomes.
- •Teams lack a shared, repeatable incident recovery flow.
How ClawVault helps
- •Checkpoint before risky operations and migrations.
- •Persist current objective, constraints, and next steps.
- •Wake with structured context after restart.
- •Treat recovery notes as operational artifacts.
01Recovery-first workflow design
Design your agent workflow so recovery steps are mandatory for high-risk operations. This creates predictable behavior under failure conditions.
02Checkpoint and wake runbook
Use checkpoints before refactors, deploys, and data migrations. On restart, run wake first before generating new plans.
03Operational hardening
Checkpoint quality improves when teams define a template and review failed recoveries in postmortems.
- •Include current objective, branch, and blocking risks in each checkpoint.
- •Record expected rollback path for dangerous operations.
- •Link checkpoints to incident and release timelines.
When should I use ClawVault?
- •Use context recovery workflows before risky code or infrastructure changes.
- •Use checkpoints when agent sessions are long-running and interruption-prone.
- •Use wake commands at every session restart to rehydrate intent quickly.
Frequently asked questions
01How do I recover AI agent context after a reset?
02What is checkpoint memory for AI agents?
03Does context recovery reduce production risk?
04Can OpenClaw use checkpoint-based recovery?
Related guides
Fix OpenClaw Memory Loss
Complete guide for durable memory and context continuity.
Persistent Memory
Store long-term context that supports recovery workflows.
Why AI Agents Forget Context
Understand failure causes behind recovery requirements.
Build a Long-Term Memory Agent
Implementation patterns for resilient agent operations.