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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.
Your plug-and-play semantic firewall — praised by users, no infra changes needed.

Thanks everyone — we’ve just passed ⭐ 550 in 60 Days (we started at Jun 15)
Most people who find this page end up starring it — because WFGY solves real bugs.
WFGY Core will be released on Aug 15 — the world’s tiniest reasoning engine (30-line TXT with Drunk Transformer).
Truly appreciate all the support — you made this happen!
Read user feedback: Hero Log

Semantic memory & reasoning fix in action

Quick access

📌 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

Open in Colab

How to use

  1. Click the badge ▸ Runtime ▸ Run all
  2. Replace prompt and answer
  3. 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

Open in Colab

How to use

  1. Run all cells
  2. Edit prompt, step1, step2
  3. Compare ΔS before vs after

If ΔS drops → checkpoint worked
If not → try BBCR fallback

What it fixes:
No.6 – Logic Collapse & Recovery
(Multi-step reasoning veers off and needs semantic midpoints)

⭐ ε_resonance — Domain-level semantic harmony

Open in Colab

How to use

  1. Run all cells
  2. Edit prompt and answer
  3. Optionally update the anchors list

Higher 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

Open in Colab

How to use

  1. Run all cells
  2. Fill in prompt and answers (≥ 3 examples)
  3. See λ_diverse score

Low (≤ 0.40) — near duplicates
Medium (0.40–0.70) — partial variety
High (≥ 0.70) — rich semantic variation

What it detects:
No.3 – Long Reasoning Chains
(Early steps diverge silently across variants)

⚠️ 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 Problems
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

For #13 (Multi-Agent), see deep dives:
• Role Drift → multi-agent-chaos/role-drift.md
• Cross-Agent Memory Overwrite → multi-agent-chaos/memory-overwrite.md

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, role drift, memory overwrite 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

  1. Open Beginner Guide → follow the symptom checklist.
  2. Use the Visual RAG Guide to locate the failing stage.
  3. 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

🧭 Explore More

Module Description Link
WFGY Core WFGY 2.0 engine is live: full symbolic reasoning architecture and math stack 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 →
🧙‍♂️ Starter Village 🏡 New here? Lost in symbols? Click here and let the wizard guide you through Start →

👑 Early Stargazers: See the Hall of Fame —
Engineers, hackers, and open source builders who supported WFGY from day one.

GitHub stars ⭐ WFGY Engine 2.0 is already unlocked. ⭐ Star the repo to help others discover it and unlock more on the Unlock Board.

WFGY Main   TXT OS   Blah   Blot   Bloc   Blur   Blow