βThe reasoning, the tradeoffs, the βwe tried X and it failed because Yβ, all trapped in chat windows that evaporate when the session ends.β , MemPalace research, 2025Document Type: Research Finding | Status: Open Gap, Partially Mitigated Date Identified: 2026-04-08 | Protocol Version: DSOM v6.1 + Palace v1.0
π The Scale of the Problem
Six months of daily AI use produces millions of tokens of conversation. That includes every decision, every debugging session, and every architecture debate. All of it is trapped in chat windows.[!NOTE] DSOM with the Sovereign Markdown Palace addresses the state persistence problem effectively. This approach originated from and was inspired by the MemPalace research (milla-jovovich/mempalace).
β What DSOM Solves Well
DSOM with the Sovereign Markdown Palace addresses the cost and state persistence problem effectively:State Persistence
task.md, What we are working on right now (Present)walkthrough.md, Full session history with Mental Anchors (Past)implementation_plan.md, Project roadmap (Future)palace_registry.md, Spatial index loaded at every SOD
Fact Retrieval
Eachcloset.md is a distilled, high-density summary. Instead of scanning 300+ lines of session logs, the AI walks to the relevant Room and reads a 40β80 line summary.
Git Persistence
Every state change is committed to Git. The project state cannot be lost, it is version-controlled, multi-machine synced, and provider-agnostic.β οΈ The Identified Gap: Live Reasoning Capture
What the Gap Is
DSOM does not automatically capture the reasoning behind decisions. It captures outcomes, what was decided, what was built, what changed. It does not capture:- β Why a decision was made
- β What alternatives were considered and rejected
- β The conversation thread that produced the reasoning
- β βWe tried X and it failed because Yβ, unless manually committed
Why It Matters
Decisions made today become constraints six months from now. If the reasoning is lost:- A future session may propose the same failed approach again.
- The AI has no way to explain why the current architecture is the way it is.
- New team members (human or AI) cannot understand the tradeoff history.
Example Scenario
π§ Current Mitigation: Hibernation Notes
The existing EOD ritual includes the Hibernation Notes export prompt, which asks the AI to dump its full in-session memory before the session ends:π‘ Recommended Practice: The Decision Log Protocol
The Principle
Capture reasoning in the moment, not at EOD. At every significant architectural decision, constraint, or failure, immediately ask the AI to log it:The Command
Example
When to Trigger a Decision Log
- Any time you say βweβll use X instead of Yβ
- Any time a test fails and you pivot approach
- Any time you override an AI recommendation
- Any time you establish a constraint that will affect future sessions
πΊοΈ Future Consideration: Semantic Search for DSOM
If the DSOM community grows and the reasoning backlog becomes deep, a sovereign semantic search layer could be added without breaking the Plain Markdown Mandate:- Tool:
ripgrep(already used) for keyword search across all closets - Upgrade: A local embedding model (e.g., via Ollama) to add vector search on top of the existing Markdown files
- The Markdown files remain the source of truth, the embeddings are a search index only
π Gap Status Summary
π Related Documents
Research finding documented: 2026-04-08 Identified by: Harisfazillah Jamel (LinuxMalaysia) in session with Google Antigravity Inspired by and originated from: MemPalace research (milla-jovovich/mempalace) Protocol: DSOM v6.1 + Palace v1.0
Deep State of Mind (DSOM) For My AI Protocol | Harisfazillah Jamel (LinuxMalaysia) | 2026-07-04 Standard: UK English | DBP-standard Bahasa Melayu Malaysia (Piawai) | GNU General Public License v3.0