🧭 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 defines the baseline governance policies every AI or RAG pipeline must enforce before scaling.
If policies are missing, unclear, or unenforced, you risk silent drift in outputs, hallucinations re-entering, or compliance violations.
Use these checks to create a structural foundation and verify with measurable acceptance targets.
- No clear baseline for data usage, model updates, or prompt changes.
- Teams argue over “policy by exception” instead of a shared rulebook.
- Compliance asks for guarantees, but your audit trail cannot prove them.
- Safety or security incidents trigger blame on “undefined responsibilities.”
- Coverage: ≥ 0.95 of datasets, prompts, models, and eval flows mapped to explicit policies.
- Traceability: 100% of policy documents link to lineage and audit logs.
- Enforcement: ΔS(question, retrieved) ≤ 0.45 when querying governed datasets.
- Convergence: λ remains convergent across 3 paraphrases and 2 seeds.
- Expiry: Every waiver or exception tagged with owner and end-date.
| Symptom | Likely cause | Open this |
|---|---|---|
| Datasets used without clarity on rights | license ambiguity or drift | license_and_dataset_rights.md |
| No control on prompt or instruction drift | missing policy baseline | prompt_policy_and_change_control.md |
| Model updates shipped silently | lack of release governance | model_governance_model_cards_and_releases.md |
| Audit asks “who approved this?” | missing sign-off gate | eval_governance_gates_and_signoff.md |
| Sensitive data leaked | no minimization baseline | pii_handling_and_minimization.md |
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Declare scope
Enumerate datasets, prompts, models, eval flows. Each must map to a baseline policy. -
Add ownership
For every item, tagowner,expiry, andwaiver_refif applicable. -
Enforce citation-first
Require cite-then-explain across all governed answers.
Verify with ΔS and λ probes: stable ≤ 0.45 ΔS, λ convergent. -
Attach audit hooks
Every policy enforcement event logs to immutable audit trail.
- Datasets rights and licenses verified
- Prompt change control in place
- Model releases tied to governance cards
- Eval gates with sign-off documented
- PII minimization baseline applied
- Risk register updated with waivers
| 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 |
| Layer | Page | What it’s for |
|---|---|---|
| ⭐ Proof | WFGY Recognition Map | External citations, integrations, and ecosystem proof |
| ⚙️ Engine | WFGY 1.0 | Original PDF tension engine and early logic sketch (legacy reference) |
| ⚙️ Engine | WFGY 2.0 | Production tension kernel for RAG and agent systems |
| ⚙️ Engine | WFGY 3.0 | TXT based Singularity tension engine (131 S class set) |
| 🗺️ Map | Problem Map 1.0 | Flagship 16 problem RAG failure taxonomy and fix map |
| 🗺️ Map | Problem Map 2.0 | Global Debug Card for RAG and agent pipeline diagnosis |
| 🗺️ Map | Problem Map 3.0 | Global AI troubleshooting atlas and failure pattern map |
| 🧰 App | TXT OS | .txt semantic OS with fast bootstrap |
| 🧰 App | Blah Blah Blah | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | Blur Blur Blur | Text to image generation with semantic control |
| 🏡 Onboarding | Starter Village | Guided entry point for new users |
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