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WFGY Problem Map 1.0 — Bookmark it. You'll need it.
16 reproducible failure modes in AI systems — with fixes (MIT).
If this page saves you time, a ⭐ helps others find it.
Cold start → ⭐ 400+ stars in 55 days — solving real problems, not just looking cool.
Hitting ⭐ 500 soon: releasing WFGY CORE on Aug 15 — the world’s tiniest reasoning engine (30-line TXT with Drunk Transformer).
Quick access
- 🏥 Semantic Clinic (AI Triage Hub): Fix symptoms when you don’t know what’s broken →
- 🚀 Getting Started (Practical Implementation): Run a guarded RAG pipeline with WFGY →
- Beginner Guide: Identify & fix your first failure
- Diagnose by symptom: Fast triage table →
Diagnose.md - Visual RAG Guide (multi-dimensional):
RAG Architecture & Recovery – Problem Map 2.0— high-altitude view linking symptom × pipeline stage × failure class, with the exact recovery path. - Field Reports: Real bugs & fixes from users
- TXT OS directory: Browse the OS repo
📌 This map isn’t just a list of bugs. It’s a diagnostic framework — a semantic X-ray for AI failure. Each entry represents a systemic breakdown across input, retrieval, or reasoning. WFGY doesn’t patch symptoms. It restructures the entire reasoning chain.
Quick-Start Downloads (60 sec)
| Tool | Link | 3-Step Setup |
|---|---|---|
| WFGY 1.0 PDF | Engine Paper | 1) Download 2) Upload to your LLM 3) Ask: “answer using WFGY + ” |
| TXT OS (plain-text OS) | TXTOS.txt | 1) Download 2) Paste into any LLM chat 3) Type “hello world” to boot |
🧪 One-click sandboxes — run WFGY instantly
Run lightweight diagnostics with zero install, zero API key. Powered by Colab.
These 4 CLI tools demonstrate WFGY's diagnostic power — each maps directly to one of the 16 failure modes. Other problems (like deployment bugs or reasoning collapse) are already handled inside WFGY,
but are not exposed as CLI yet — either because they require full context, or operate at system level.
More tools coming soon.
⭐ ΔS Diagnostic (MVP) — Measure semantic drift
How to use
- Click the badge ▸ Runtime ▸ Run all
- Replace
promptandanswer- See ΔS score and suggested fix
What it detects:
No.2 – Interpretation Collapse
(Prompt and output look fine, but meaning is mismatched)
⭐ λ_observe Checkpoint — Mid-step re-grounding
How to use
- Run all cells
- Edit
prompt,step1,step2- Compare ΔS before vs after
If ΔS drops → checkpoint worked
If not → try BBCR fallbackWhat it fixes:
No.6 – Logic Collapse & Recovery
(Multi-step reasoning veers off and needs semantic midpoints)
⭐ ε_resonance — Domain-level semantic harmony
How to use
- Run all cells
- Edit
promptandanswer- Optionally update the
anchorslistHigher ε → deeper resonance with domain anchors
What it explains:
No.12 – Philosophical Recursion
(Looping abstraction caused by mismatched domains)
⭐ λ_diverse — Answer-set diversity check
How to use
- Run all cells
- Fill in
promptandanswers(≥ 3 examples)- See λ_diverse score
Low (≤ 0.40) — near duplicates
Medium (0.40–0.70) — partial variety
High (≥ 0.70) — rich semantic variationWhat it detects:
No.3 – Long Reasoning Chains
(Early steps diverge silently across variants)
🍷 More modules coming soon — Drunk Transformer preview
These formulas may sound like something a language model would say after a few drinks…
But they’re actually designed to keep your model sober — no more collapsing logic, no more derailed reasoning.
Think of it as semantic seatbelts for your transformer.
WDT – Where Did You Take me?
→ Asymmetric cross-path suppression. Prevents illegal logic jumps between divergent tracks.WTF – What the F*** happened?
→ Collapse detection and graceful reset. When everything breaks, it gently hits the semantic panic button.
Drunk Transformer math layer (coming soon)
• WRI – Where am I? → Locks token positions to maintain structural coherence
• WAI – Who am I? → Forces head diversity to avoid collapse-by-consensus
• WAY – Who are you? → Boosts entropy across attention heads for better external awareness
• WDT – Where did you take me? → (see above)
• WTF – What the f*** happened? → (see above)
Each one is backed by a real formula.
You’ll be able to try them soon — stay tuned.P.S. These formulas are real.
Like, math-real. Not just wine-fueled wordplay. :P
⚠️ Warning ⚠️ These tools may trigger existential reflection — especially if you've spent months chasing ghost bugs in your RAG stack.
Failure catalog (with fixes)
| # | Problem Domain | What breaks | Doc |
|---|---|---|---|
| 1 | Hallucination & Chunk Drift | Retrieval returns wrong/irrelevant content | hallucination.md |
| 2 | Interpretation Collapse | Chunk is right, logic is wrong | retrieval-collapse.md |
| 3 | Long Reasoning Chains | Drifts across multi-step tasks | context-drift.md |
| 4 | Bluffing / Overconfidence | Confident but unfounded answers | bluffing.md |
| 5 | Semantic ≠ Embedding | Cosine match ≠ true meaning | embedding-vs-semantic.md |
| 6 | Logic Collapse & Recovery | Dead-end paths; needs controlled reset | logic-collapse.md |
| 7 | Memory Breaks Across Sessions | Lost threads, no continuity | memory-coherence.md |
| 8 | Debugging is a Black Box | No visibility into failure path | retrieval-traceability.md |
| 9 | Entropy Collapse | Attention melts, incoherent output | entropy-collapse.md |
| 10 | Creative Freeze | Flat, literal outputs | creative-freeze.md |
| 11 | Symbolic Collapse | Abstract/logical prompts break | symbolic-collapse.md |
| 12 | Philosophical Recursion | Self-reference/paradoxes crash reasoning | philosophical-recursion.md |
| 13 | Multi-Agent Chaos | Agents overwrite/misalign logic | multi-agent-chaos.md |
| 14 | Bootstrap Ordering | Services fire before deps ready | bootstrap-ordering.md |
| 15 | Deployment Deadlock | Circular waits (index⇆retriever, DB⇆migrator) | deployment-deadlock.md |
| 16 | Pre-Deploy Collapse | Version skew / missing secret on first call | predeploy-collapse.md |
Problem families: Prompting · Retrieval · Reasoning · Infra/Deploy — locate the root cause first, then apply the specific patch.
Why these 16 errors were solvable
WFGY does not just react; it gives semantic altitude. Core tools ΔS, λ_observe, and e_resonance help detect, decode, and defuse collapse patterns from outside the maze.
See the pipeline and recovery end-to-end:
→ RAG Architecture & Recovery
Problem Maps Index (Map-A … Map-G)
These short IDs let you route quickly in issues/PRs/support threads.
| Map ID | Map Name | Linked Issues | Focus | Link |
|---|---|---|---|---|
| Map-A | RAG Problem Table | #1, #2, #3, #5, #8 | Retrieval-augmented generation failures | View |
| Map-B | Multi-Agent Chaos Map | #13 | Coordination failures, memory conflicts | View |
| Map-C | Symbolic & Recursive Map | #11, #12 | Symbolic logic traps, abstraction, paradox | View |
| Map-D | Logic Recovery Map | #6 | Dead-end logic, reset loops, controlled recovery | View |
| Map-E | Long-Context Stress Map | #3, #7, #10 | 100k-token memory, noisy PDFs, long-task drift | View |
| Map-F | Safety Boundary Map | #4, #8 | Overconfidence, jailbreak resistance, traceability | View |
| Map-G | Infra Boot Map | #14–#16 | Ordering, boot loops, version skew, deadlocks | View |
Minimal quick-start
- Open Beginner Guide → follow the symptom checklist.
- Use the Visual RAG Guide to locate the failing stage.
- Open the matching page above and apply the patch.
Ask any LLM to apply WFGY (TXT OS makes it smoother):
I’ve uploaded TXT OS / WFGY notes.
My issue: \[e.g., OCR tables from scanned PDFs look fine but answers are wrong].
Which WFGY modules should I apply and in what order?
Status & difficulty
| # | Problem | Difficulty* | Implementation |
|---|---|---|---|
| 1 | Hallucination & Chunk Drift | Medium | ✅ Stable |
| 2 | Interpretation Collapse | High | ✅ Stable |
| 3 | Long Reasoning Chains | High | ✅ Stable |
| 4 | Bluffing / Overconfidence | High | ✅ Stable |
| 5 | Semantic ≠ Embedding | Medium | ✅ Stable |
| 6 | Logic Collapse & Recovery | Very High | ✅ Stable |
| 7 | Memory Breaks Across Sessions | High | ✅ Stable |
| 8 | Debugging Black Box | Medium | ✅ Stable |
| 9 | Entropy Collapse | High | ✅ Stable |
| 10 | Creative Freeze | Medium | ✅ Stable |
| 11 | Symbolic Collapse | Very High | ✅ Stable |
| 12 | Philosophical Recursion | Very High | ✅ Stable |
| 13 | Multi-Agent Chaos | Very High | ✅ Stable |
| 14 | Bootstrap Ordering | Medium | ✅ Stable |
| 15 | Deployment Deadlock | High | ⚠️ Beta |
| 16 | Pre-Deploy Collapse | Medium-High | ✅ Stable |
*Distance from default LLM behavior to a production-ready fix.
Contributing / support
- Open an Issue with a minimal repro (inputs → calls → wrong output).
- PRs for clearer docs, repros, or patches are welcome.
- WFGY Project home: github.com/onestardao/WFGY
- TXT OS: github.com/onestardao/WFGY/tree/main/OS
- If this map helped you, a ⭐ helps more devs find it.
🧭 Explore More
| Module | Description | Link |
|---|---|---|
| WFGY Core | Standalone semantic reasoning engine for any LLM | View → |
| Problem Map 1.0 | Initial 16-mode diagnostic and symbolic fix framework | View → |
| Problem Map 2.0 | RAG-focused failure tree, modular fixes, and pipelines | View → |
| Semantic Clinic Index | Expanded failure catalog: prompt injection, memory bugs, logic drift | View → |
| Semantic Blueprint | Layer-based symbolic reasoning & semantic modulations | View → |
| Benchmark vs GPT-5 | Stress test GPT-5 with full WFGY reasoning suite | View → |
👑 Early Stargazers: See the Hall of Fame —
Engineers, hackers, and open source builders who supported WFGY from day one.
⭐ Help reach 10,000 stars by 2025-09-01 to unlock Engine 2.0 for everyone ⭐ Star WFGY on GitHub
