Replay-native doctrine

Five principles for replay-safe AI systems.

These principles frame replay as an operating discipline: preserve lineage, make drift inspectable, and keep recovery paths reconstructable as trust posture evolves.

Illustrative doctrine only. This page is not legal advice, regulatory advice, a certification mark, or a standards-body publication.
1

AI systems should be replayable

A replay-native system preserves enough ordered context around prompts, tools, approvals, retries, and handoffs that operators can inspect behavior after the session has passed. Replay does not require exposing every payload; it requires a coherent trail of what the runtime believed, attempted, and changed.

2

Runtime lineage should persist

Lineage connects each action to its predecessor, successor, owner, and review posture. When lineage persists across runtime boundaries, teams can understand how a decision moved through tools and agents instead of rebuilding the chain from disconnected logs.

3

Drift should be inspectable

Drift becomes operationally useful when it can be located, named, and compared against an expected path. Replay-native systems should make changes in authority, policy fit, continuity, and confidence visible before the review becomes forensic reconstruction.

4

Recovery should be reconstructable

Recovery is not only whether a workflow eventually completed. It is whether the checkpoint, attempted fix, authority boundary, and downstream state can be reconstructed by a reviewer who was not present during the incident.

5

Trust should evolve procedurally

Trust posture should change through visible procedures: evidence captured, deltas explained, reviews completed, continuity preserved, and recoveries documented. It should not depend on a single static score or an unverifiable claim that the system is safe.

Developer certification posture

Future ecosystem language, not a live certification program.

Recon may use badge language to describe the posture expected of replay-native developer ecosystems. These labels are illustrative and aspirational today; they do not represent a live audit, paid certification, partner endorsement, or compliance program.

replay-ready

The runtime is designed to preserve inspectable replay context around consequential steps.

GhostLog-enabled

The integration can emit receipt-style evidence for lineage, deltas, checkpoints, and review notes.

TrustGraph-compatible

The system can describe relationships among agents, tools, policies, and posture transitions.

continuity-preserving

The workflow carries enough metadata through handoffs and recovery paths for later reconstruction.