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📋 WFGY Problem Map – Bookmark This. You’ll Need It.
Every failure has a name. Every name has a countermeasure.
WFGY (Wan Fa Gui Yi) = Semantic Firewall for AI Reasoning.
It fixes logic collapse, memory loss, hallucination, and abstract breakdowns — in live generation and retrieval pipelines.
All terms mentioned (e.g., BBMC, BBPF, BBCR, ΔS) are modules of the open-source WFGY engine (MIT license).
📎 PDF contains full formulas; TXT OS applies them as an operating system for AI workflows. Download links at the bottom.
Benchmark vs GPT‑5 (Coming Soon)
We will publicly compare GPT‑4 + WFGY against GPT‑5 across logic, philosophy, and long-context reasoning.
This is the same engine you’re using — and yes, it will fight GPT‑5 head-on.
📎 Track the benchmark → (launching once GPT‑5 is released)
Welcome! This map lists every AI failure we’ve fixed —or are fixing — with the WFGY reasoning engine.
TXT OS + WFGY exists to turn critical AI bugs into reproducible, modular fixes.
Spot a gap? Open an Issue or PR — community feedback drives the next entries.
👀 Want to test WFGY yourself?
See TXT OS for real-time demos, or start here with RAG failures →
Vision
Make “my AI went off the rails” as rare as a 500 error in production software.
Every solved failure below pushes us closer.
🔗 Navigation – Solved (or Tracked) AI Failure Modes
| # | Problem Domain | Description | Doc |
|---|---|---|---|
| 1 | Hallucination & Chunk Drift | Retrieval brings wrong / irrelevant content | hallucination.md |
| 2 | Interpretation Collapse | Chunk is correct but logic fails | retrieval-collapse.md |
| 3 | Long Reasoning Chains | Model drifts across multi‑step tasks | context-drift.md |
| 4 | Bluffing / Overconfidence | Model pretends to know what it doesn’t | bluffing.md |
| 5 | Semantic ≠ Embedding | Cosine match ≠ true meaning | embedding-vs-semantic.md |
| 6 | Logic Collapse & Recovery | Dead‑end paths, auto‑reset logic | 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 | Outputs become flat, literal | creative-freeze.md |
| 11 | Symbolic Collapse | Abstract / logical prompts break model | symbolic-collapse.md |
| 12 | Philosophical Recursion | Self‑reference or paradoxes crash reasoning | philosophical-recursion.md |
| 13 | Multi‑Agent Chaos | Agents overwrite / misalign logic | multi-agent-chaos.md |
🔗 Status & Difficulty Matrix
| # | 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 |
*Difficulty = gap between default LLM ability and a production‑ready fix; “Very High” means almost no off‑the‑shelf tool tackles it.
🔗 How to Use These Docs
Each problem page covers:
- Symptoms – what the failure looks like
- Root Causes – why standard pipelines break
- Module Breakdown – which WFGY parts fix it
- Status & Examples – code or demo you can run now
Missing issue? Open an Issue or PR—real failure traces especially welcome.
🔗 Specialized Maps
- 🧠 RAG Problem Table (#1, #2, #3, #5, #8) – retrieval‑augmented generation failures
- 🤖 Multi‑Agent Chaos Map (#13) – coordination, memory, role drift
- 🔎 Symbolic & Recursive Map (#11, #12) – paradox, abstraction, logical traps
- 🧩 Logic Recovery Map (#6) – dead-end logic and auto-reset reasoning
- 📜 Long‑Context Stress Map (#3, #7, #10) – 100k‑token stability, noisy PDFs
- 🧪 Safety Boundary Map (#4, #8) – knowledge gaps, bluffing, jailbreak resistance
🔗 Not Sure What’s Going Wrong?
You’re not alone — many AI devs face mysterious failures like:
- “Why is it hallucinating when the chunk is correct?”
- “Why can’t it reason despite having all the data?”
- “Why does context break halfway through?”
🎯 Diagnose by symptom — find your problem, see exact WFGY fix:
| Symptom | Problem ID | Fix |
|---|---|---|
| 🤯 Wrong chunks, wrong answer | #1 Hallucination & Chunk Drift | Fix it → |
| 🧵 Model forgets context in long docs | #7 Memory Breaks in 100k Tokens | Fix it → |
| 🌀 Good data, still bad logic | #2 Interpretation Collapse | Fix it → |
| 🔍 Full diagnosis table (13+ issues) | See full table → |
🔗 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 |
If you want to fully understand how WFGY works, check out:
- 📘 WFGY GitHub homepage – full documentation, formulas, and modules
- 🖥️ TXT OS repo – how the semantic OS is built using WFGY
But if you're just here to solve real AI problems fast, you can simply download the files above and follow the Problem Map instructions directly.
👑 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