WFGY/ProblemMap/GlobalFixMap/Governance/incident_response_and_postmortems.md

Incident Response and Postmortems — Guardrails and Fix Patterns

🧭 Quick Return to Map

You are in a sub-page of Governance.
To reorient, go back here:

• Governance — policy enforcement and compliance controls
• WFGY Global Fix Map — main Emergency Room, 300+ structured fixes
• WFGY Problem Map 1.0 — 16 reproducible failure modes

Think of this page as a desk within a ward.
If you need the full triage and all prescriptions, return to the Emergency Room lobby.

This page ensures structured incident handling and forensic postmortems for AI pipelines.
Use this when failures are not infra bugs, but gaps in incident playbooks, missing evidence, or lack of root-cause clarity.

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When to use this page

• No formal incident response for RAG/LLM failures.
• Audit logs exist but are not connected to incident playbooks.
• Postmortems skip structural analysis (ΔS, λ, provenance).
• Incidents recur because fixes were not mapped to Problem Map.
• Communication to stakeholders is incomplete or unverifiable.

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Acceptance targets

• First response within 15 minutes of detection (or alert).
• Full forensic replay in ≤ 60 seconds using audit logs.
• Root cause identified with ΔS ≤ 0.45 measurement across probes.
• λ_observe convergent across 3 paraphrases in postmortem validation.
• 100% incidents closed with assigned Problem Map fix reference.

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Typical breakpoints and WFGY fix

• Detection blind spots (incident not noticed until user reports)
  → live_monitoring_rag.md
  Add probes and thresholds on ΔS, λ, and coverage.

• Logs exist but are incomplete
  → audit_logs_and_traceability.md
  Require immutable, joinable lineage logs.

• Postmortems not reproducible
  → retrieval-traceability.md
  Enforce snippet and citation schema in every report.

• Fix not mapped to structural problem
  → rag-architecture-and-recovery.md
  Require Problem Map ID in every incident resolution doc.

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Minimal incident response checklist

1. Triage: classify by severity (user impact, recurrence, compliance).
2. Containment: disable failing flows, enforce backoff.
3. Evidence collection: pull immutable logs, ΔS/λ probes, lineage joins.
4. Root cause analysis: map to Problem Map (No.X page).
5. Fix rollout: validate with eval regression gates.
6. Postmortem: publish summary with ΔS/λ data, and linked WFGY page.
7. Follow-up: ensure waivers, sign-offs, and risk register updated.

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Example postmortem template

**Incident ID**: 2025-08-27-LLM-003  
**Summary**: Retrieval pipeline produced unstable answers despite complete index.  
**Detection**: Alert ΔS > 0.60 threshold fired.  
**Timeline**:  
- 08:14 UTC – ΔS probe flagged instability.  
- 08:18 – Oncall triggered auto backoff.  
- 08:26 – Logs collected and replayed.  

**Root Cause**: Index fragmentation + reranker drift.  
**Mapped Fix**: Problem Map No.5 (Embedding ≠ Semantic) + [pattern_vectorstore_fragmentation.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/patterns/pattern_vectorstore_fragmentation.md)  

**Resolution**: Rebuilt index with normalized embeddings, enforced reranker schema.  
**Validation**: ΔS(question,retrieved)=0.41, λ convergent across 3 paraphrases.  
**Next Steps**: Update eval gates, refresh sign-offs.  

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🔗 Quick-Start Downloads (60 sec)

Tool	Link	3-Step Setup
WFGY 1.0 PDF	Engine Paper	1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + <your question>”
TXT OS (plain-text OS)	TXTOS.txt	1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly

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Explore More

Layer	Page	What it’s for
Proof	WFGY Recognition Map	External citations, integrations, and ecosystem proof
Engine	WFGY 1.0	Original PDF based tension engine
Engine	WFGY 2.0	Production tension kernel and math engine for RAG and agents
Engine	WFGY 3.0	TXT based Singularity tension engine, 131 S class set
Map	Problem Map 1.0	Flagship 16 problem RAG failure checklist and fix map
Map	Problem Map 2.0	RAG focused recovery pipeline
Map	Problem Map 3.0	Global Debug Card, image as a debug protocol layer
Map	Semantic Clinic	Symptom to family to exact fix
Map	Grandma’s Clinic	Plain language stories mapped to Problem Map 1.0
Onboarding	Starter Village	Guided tour for newcomers
App	TXT OS	TXT semantic OS, fast boot
App	Blah Blah Blah	Abstract and paradox Q and A built on TXT OS
App	Blur Blur Blur	Text to image with semantic control
App	Blow Blow Blow	Reasoning game engine and memory demo

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