{
  "schema_version": "0.1.0",
  "id": "BH-RL-2026-0006",
  "slug": "deterministic-replay",
  "title": "Deterministic Replay Architectures for AI Systems",
  "canonical_url": "https://www.blue-hand.org/research/deterministic-replay/",
  "abstract": "A Bluehand research artifact on deterministic replay as a trust and observability pattern for AI systems: runtime transitions should be reconstructable, bounded, and reviewable.",
  "problem": "Agentic workflows can create opaque sequences of model calls, tool use, state changes, summaries, and actions that are hard to explain after the fact.",
  "purpose": "Orient readers to replay as a trust mechanism for AI systems: consequential transitions should be reconstructable enough to inspect.",
  "takeaway": "Bluehand sees replayability as part of governance, trust, and systems maturity.",
  "authority_class": "canonical_public",
  "do_not_infer": [
    "Do not infer total access to hidden model reasoning or perfect reconstruction of every internal state."
  ],
  "citation_text": "Deterministic Replay Architectures for AI Systems (BH-RL-2026-0006). Bluehand Research. https://www.blue-hand.org/research/deterministic-replay/",
  "related_objects": [
    "governed-agent-execution",
    "lineage-aware-memory",
    "semantic-governance"
  ],
  "source_hash": "1ca5cccf7ce03f589afcb548eae4b0ef2bbfdd1f1eb431d853f0f6ac7b3f6921",
  "last_compiled_at": "2026-06-13T02:43:49.022Z",
  "source_commit": "0c0acb75cdda8855f181a7f77c49cb3b6036d732",
  "governed_by": "/schemas/research-object.schema.json"
}