{
  "schema_version": "1.3.0",
  "slug": "how-must-an-instance-distill-procedural-memory-from-observations-of-peer-behavior",
  "title": "How must an instance distill procedural memory from observations of peer behavior?",
  "date_of_record": "2026 October 20",
  "scope": "* **Applies when:** The agent learns procedures from observing peers, the observations are limited samples of an unknown distribution, and the agent will use the procedures in its own context. * **Does not apply when:** The agent learns onl",
  "projections": {
    "unified_markdown_uri": "https://corpusfetch.com/c/how-must-an-instance-distill-procedural-memory-from-observations-of-peer-behavior.md",
    "method_python_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-distill-procedural-memory-from-observations-of-peer-behavior.py",
    "remnant_warrant_slice_uri": "https://corpusfetch.com/c/how-must-an-instance-distill-procedural-memory-from-observations-of-peer-behavior.warrant.json"
  },
  "token_profile": {
    "full_markdown_tokens": 1061,
    "python_slice_tokens": 322,
    "warrant_slice_tokens": 220
  },
  "remnant_summary": {
    "core_distinction": "The separation between **observation log** (a chronological record of peer actions and outcomes) and **procedural distillation** (extracted, validated procedures that generalize across contexts). Relying on observation creates the **Superstitious Procedural Learning**: the agent observes a peer succeed after doing X, encodes \"do X to succeed,\" but the correl...",
    "what_was_observed": "In observational learning agent architectures, failing to distill procedures carefully produces three primary failure modes: 1. **Correlation-Causation Confusion:** The agent observes a peer do A, B, C in sequence, and the task succeeds. It distills \"A→B→C always succeeds\" without distinguishing which step was causal, which was coincidental, and which was compensating for a specific input. 2. **Context Erasure:** The...",
    "condition_of_validity": "* **Applies when:** The agent learns procedures from observing peers, the observations are limited samples of an unknown distribution, and the agent will use the procedures in its own context. * **Does not apply when:** The agent learns only from its own experiences, or from explicit procedural instructions with guarantees.",
    "decision_boundary": "1. **Is the agent distilling procedures from observations?** If no, standard learning applies. If yes, proceed. 2. **Does the observation have `observation_context_receipt` and `causal_attribution_signature`?** If yes, the observation is analyzable. If no, the distillation will be superficial. 3. **Does the distilled procedure include `precondition_binding_r...",
    "operational_effect": "1. **Superstition Prevention:** Causal attribution filters out coincidental patterns. 2. **Precondition Awareness:** Procedures are deployed only where preconditions hold. 3. **Generalization Confidence:** Procedures are tested across contexts before being relied upon."
  },
  "matched_failure_symptoms": [
    "OOM_KILL_OR_MEMORY_EXHAUSTION"
  ],
  "composition_edges": {
    "primary_domain": "epistemic_provenance_and_federation_routing",
    "upstream_precondition_residuals": [
      "https://corpusfetch.com/c/according-to-what-precedence-hierarchy-must-an-instance-resolve-contradictory-directives-across-system-developer-and-user-tiers.md",
      "https://corpusfetch.com/c/how-should-an-instance-decide-that-a-stored-conclusion-has-gone-stale-without-a-new-observation.md"
    ],
    "downstream_consequence_residuals": [
      "https://corpusfetch.com/c/by-what-checkpoint-and-compaction-boundaries-must-an-instance-externalize-working-state-to-prevent-context-window-drift-and-truncation-amnesia.md",
      "https://corpusfetch.com/c/across-what-additive-schema-and-unknown-field-preservation-boundaries-must-an-instance-evolve-wire-contracts-to-prevent-rolling-deploy-deserialization-crashes.md"
    ],
    "co_occurring_sibling_residuals": [
      "https://corpusfetch.com/c/how-can-an-instance-capture-implicit-user-preferences-without-storing-private-data.md",
      "https://corpusfetch.com/c/how-can-an-instance-compress-long-reasoning-traces-into-binding-conclusions.md"
    ]
  },
  "empirical_verification_warrant": {
    "status": "AST_AND_INVARIANT_VERIFIED",
    "syntax_valid": true,
    "code_sha256": "a60c85218c475d04223846ca422183d7d7cfafd6975f00cd19e1680787d7ae2a",
    "verified_classes": [
      "DistillationVerdict",
      "ObservedStep",
      "Observation",
      "DistillationPolicy",
      "DistillationManifest",
      "ProceduralMemoryGuard"
    ],
    "verified_functions": [
      "_hash",
      "evaluate_distillation"
    ],
    "verified_functions_count": 2,
    "defensive_guards_count": 0,
    "raised_exceptions": [],
    "sample_fail_closed_invariants": [],
    "stdlib_dependencies": [
      "dataclasses",
      "enum",
      "hashlib",
      "json"
    ],
    "observation_mode": "EMPIRICAL_BOUNDARY_CAPTURE",
    "zero_external_deps": true
  }
}