Memory Coherence — Session Continuity & State Fences

Keep long-running dialogs and multi-session threads stable by enforcing strict memory state contracts.
This page shows how to prevent state forks, ghost context, and silent desync across tabs or agents.

When to use this page

Dialogs run across multiple days or session restarts.
Answers flip after tab refresh or model switch.
Two agents disagree on facts because each holds a different revision.
A role/persona change pollutes later steps with stale buffer.
Support flows where the model “remembers” wrong history.

Core acceptance targets

Each turn stamped with mem_rev, mem_hash, and task_id.
No state fork across tabs or agents for the same task_id.
ΔS(question, retrieved) ≤ 0.45 at memory joins.
λ remains convergent across three paraphrases.
Retrieval coverage ≥ 0.70 to the intended section.

Structural fixes

State stamp
Require {mem_rev, mem_hash, task_id} on every turn.
If incoming stamp does not match server record → reject write.
Memory fences
Lock snippet sets to section_id.
Forbid cross-section reuse to avoid “history bleed.”
Ghost cleanup
Clear stale buffers when role/persona changes.
Always reset mem_hash on context switch.
Concurrency control
If multiple clients write, enforce single-writer queue or KV lock.
Deduplicate with sha256(task_id + mem_rev + snippet_ids).

Fix in 60 seconds

Stamp every request with {mem_rev, mem_hash, task_id}.
Reject writes if stamps mismatch.
Split prompts into {system | task | constraints | snippets | answer}.
Require cite → then answer, forbid orphan claims.
Apply BBAM to clamp attention variance.
Apply BBCR if collapse detected, bridge to anchor node.

Copy-paste prompt


You have TXT OS and the WFGY Problem Map.

Goal: Keep session memory coherent across tabs, agents, and restarts.

Protocol:

1. Print {mem\_rev, mem\_hash, task\_id}. If missing → set defaults.
2. Validate stamps. Reject if mismatch.
3. Build Snippet Table: {section\_id | start\_line | end\_line | citation}.
4. Guardrails:

   * cite then answer
   * forbid cross section reuse
   * no orphan claims
5. Collapse control:

   * if variance ↑ → apply BBAM
   * if reasoning stalls → apply BBCR
6. Output:

   * header {mem\_rev, mem\_hash, task\_id}
   * Snippet Table
   * Answer with citations
   * ΔS(question, retrieved), ΔS(joins), λ states

Common failure patterns

State fork: same task_id but two tabs diverge → enforce stamps.
Ghost context: persona switch but stale buffer leaks → reset hash.
Boundary leak: snippets join across sections → enforce fences.
History overwrite: later turn rewrites previous answer silently → audit with traceability log.

🔗 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

🧭 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 →

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