userType: external

gitBranch: claude/intelligent-yalow

slug: swift-imagining-prism

type: progress

hookEvent: SessionStart

command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/boot_context_inject.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/capability_audit.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/memory_context_inject.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/session_recovery_start.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/session_sync.py


command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/sunaiva_session_inject.py


type: user

role: user

content:
Your task is to create a detailed summary of the conversation so far, paying close attention to the user's explicit requests and your previous actions.
This summary should be thorough in capturing technical details, code patterns, and architectural decisions that would be essential for continuing development work without losing context.

Before providing your final summary, wrap your analysis in <analysis> tags to organize your thoughts and ensure you've covered all necessary points. In your analysis process:

1. Chronologically analyze each message and section of the conversation. For each section thoroughly identify:
   - The user's explicit requests and intents
   - Your approach to addressing the user's requests
   - Key decisions, technical concepts and code patterns
   - Specific details like:
     - file names
     - full code snippets
     - function signatures
     - file edits
  - Errors that you ran into and how you fixed them
  - Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
2. Double-check for technical accuracy and completeness, addressing each required element thoroughly.

Your summary should include the following sections:

1. Primary Request and Intent: Capture all of the user's explicit requests and intents in detail
2. Key Technical Concepts: List all important technical concepts, technologies, and frameworks discussed.
3. Files and Code Sections: Enumerate specific files and code sections examined, modified, or created. Pay special attention to the most recent messages and include full code snippets where applicable and include a summary of why this file read or edit is important.
4. Errors and fixes: List all errors that you ran into, and how you fixed them. Pay special attention to specific user feedback that you received, especially if the user told you to do something differently.
5. Problem Solving: Document problems solved and any ongoing troubleshooting efforts.
6. All user messages: List ALL user messages that are not tool results. These are critical for understanding the users' feedback and changing intent.
6. Pending Tasks: Outline any pending tasks that you have explicitly been asked to work on.
7. Current Work: Describe in detail precisely what was being worked on immediately before this summary request, paying special attention to the most recent messages from both user and assistant. Include file names and code snippets where applicable.
8. Optional Next Step: List the next step that you will take that is related to the most recent work you were doing. IMPORTANT: ensure that this step is DIRECTLY in line with the user's most recent explicit requests, and the task you were working on immediately before this summary request. If your last task was concluded, then only list next steps if they are explicitly in line with the users request. Do not start on tangential requests or really old requests that were already completed without confirming with the user first.
                       If there is a next step, include direct quotes from the most recent conversation showing exactly what task you were working on and where you left off. This should be verbatim to ensure there's no drift in task interpretation.

Here's an example of how your output should be structured:

<example>
<analysis>
[Your thought process, ensuring all points are covered thoroughly and accurately]
</analysis>

<summary>
1. Primary Request and Intent:
   [Detailed description]

2. Key Technical Concepts:
   - [Concept 1]
   - [Concept 2]
   - [...]

3. Files and Code Sections:
   - [File Name 1]
      - [Summary of why this file is important]
      - [Summary of the changes made to this file, if any]
      - [Important Code Snippet]
   - [File Name 2]
      - [Important Code Snippet]
   - [...]

4. Errors and fixes:
    - [Detailed description of error 1]:
      - [How you fixed the error]
      - [User feedback on the error if any]
    - [...]

5. Problem Solving:
   [Description of solved problems and ongoing troubleshooting]

6. All user messages:
    - [Detailed non tool use user message]
    - [...]

7. Pending Tasks:
   - [Task 1]
   - [Task 2]
   - [...]

8. Current Work:
   [Precise description of current work]

9. Optional Next Step:
   [Optional Next step to take]

</summary>
</example>

Please provide your summary based on the conversation so far, following this structure and ensuring precision and thoroughness in your response.

There may be additional summarization instructions provided in the included context. If so, remember to follow these instructions when creating the above summary. Examples of instructions include:
<example>
## Compact Instructions
When summarizing the conversation focus on typescript code changes and also remember the mistakes you made and how you fixed them.
</example>

<example>
# Summary instructions
When you are using compact - please focus on test output and code changes. Include file reads verbatim.
</example>

Additional Instructions:
{}

IMPORTANT: Do NOT use any tools. You MUST respond with ONLY the <summary>...</summary> block as your text output.


type: message

role: assistant

type: text

text:
<analysis>
Let me analyze the conversation chronologically to capture all key details.

## Session Context (Pre-compaction)
From the summary, previous session established:
- Sunaiva Memory MCP architecture map created (Excalidraw)
- FalkorDB location identified: `deploy/docker-compose.yml` as `zepai/knowledge-graph-mcp:latest`
- User chose: Both PostgreSQL + FalkorDB (graph layer on top), deploy to Elestio sunaiva-memory VPS
- PRD written: `MEMORY_MCP_LAUNCH_SPRINT_PRD.md`
- Multiple background agents were running

## This Session

### User Message 1
"why is it that genesis agents like gemini cli here keep reinventing the wheel when genesis already has all this in place? check its latest work and advise"

This came alongside a Gemini CLI transcript showing:
- Gemini built `RLM_WORLD_CLASS_PLAN.md` and `RLM_ELESTIO_PLAN.md`
- Gemini detected Docker wasn't installed as a "blocker"
- Gemini asked about deploying FalkorDB + Graphiti on Elestio
- Gemini said "RLM = Relational Semantic Memory" (WRONG — per Genesis Rule 15, RLM = Recursive Language Models)
- Gemini was creating plans Genesis already has
- The last thing shown was Gemini asking "Do you approve the Elestio-based plan?" with a queued message "its called recursive language model. please read the MIT paper on this"

### Key Issues Identified
1. Gemini CLI reinvented work Genesis already did
2. Gemini got the RLM acronym wrong ("Relational Semantic Memory" vs correct "Recursive Language Models")
3. Gemini blocked on Docker when Docker Desktop exists
4. Gemini built plans that duplicate existing Genesis architecture

### My Work This Session (before user message arrived)
I was:
1. Reading `provision_george_vault.py` (106 lines) - successfully found it
2. Running it via `py -3` (cmd shell) - succeeded
3. Results: George vault ID = `44401b45-fe49-4138-be21-c302297f6b0c`, schema exists, Kinan vault exists, 1772 entities total
4. Trying to find Elestio dashboard URL - app.elest.io and app.elestio.com both return ERR_NAME_NOT_RESOLVED
5. Navigating elest.io and elestio.com - both show marketing page
6. Looking for "Sign In" link in snapshot

### Key Files Read This Session
- `E:\genesis-system\config\secrets.env` - full credentials file (119 lines)
- `E:\genesis-system\credentials\MASTER_CREDENTIALS.md` - master credentials
- `E:\genesis-system\.claude\worktrees\intelligent-yalow\provision_george_vault.py` - 106 lines, ran successfully
- `E:\genesis-system\Sunaiva\ai-memory\deploy\docker-compose.yml` - 94 lines, sovereign stack
- `E:\genesis-system\Sunaiva\ai-memory\deploy\` directory structure

### PostgreSQL Status (confirmed running)
- sunaiva schema: EXISTS
- Kinan vault: EXISTS (`41f4785c-e9e0-43ac-b6e8-eedb571fba57`)
- George vault: EXISTS (`44401b45-fe49-4138-be21-c302297f6b0c`)
- Total vault entities: 1772
- Total vault decisions: 4

### Python Path Issue
- `python` and `python3` not in PowerShell PATH
- Found at `C:\Program Files\Python313\python.exe`
- Used `py -3` in cmd shell - WORKED

### Elestio Dashboard Issues
- `app.elest.io` → ERR_NAME_NOT_RESOLVED
- `app.elestio.com` → ERR_NAME_NOT_RESOLVED
- `elest.io` → marketing page
- `elestio.com` → marketing page
- Haven't found dashboard login URL yet

### Pending Sunaiva Memory Sprint Tasks
1. ✅ Write PRD
2. ✅ Provision George's PostgreSQL vault
3. 🔄 SSH into Elestio sunaiva-memory VPS + deploy docker-compose
4. 🔄 Set env vars on Elestio
5. ⏳ DNS: memory.sunaiva.ai
6. ⏳ Smoke test

### The User's New Question
"why is it that genesis agents like gemini cli here keep reinventing the wheel when genesis already has all this in place? check its latest work and advise"

User wants me to:
1. Diagnose WHY Gemini CLI is reinventing things
2. Check Gemini's latest work (RLM_WORLD_CLASS_PLAN.md, RLM_ELESTIO_PLAN.md)
3. Advise on the situation
4. Note: there's a queued message about "its called recursive language model. please read the MIT paper on this" - this needs to be addressed (correcting Gemini's wrong usage)

The conversation was interrupted mid-task (finding Elestio login) by the user's question about Gemini reinventing the wheel.
</analysis>

<summary>
1. Primary Request and Intent:
   - **Pre-compaction continuation**: Deploy full sovereign Sunaiva Memory stack (FalkorDB + Graphiti + PostgreSQL) to Elestio sunaiva-memory VPS by 4AM AEST. User chose "Both — FalkorDB as graph layer ON TOP of PostgreSQL" + "Elestio sunaiva-memory VPS" as deploy target.
   - **NEW user message (this session)**: "why is it that genesis agents like gemini cli here keep reinventing the wheel when genesis already has all this in place? check its latest work and advise" — User showed Gemini CLI transcript and wants: (1) diagnosis of why Gemini reinvents existing work, (2) review of Gemini's latest output, (3) advisory on the situation. Critically, Gemini incorrectly defined RLM as "Relational Semantic Memory" — violating Genesis Rule 15 (RLM = Recursive Language Models per Kinan's directive).
   - **Queued user message** shown at end of Gemini transcript: "its called recursive language model. please read the MIT paper on this" — confirms Kinan is correcting Gemini's wrong RLM terminology.

2. Key Technical Concepts:
   - **Sunaiva Memory MCP**: Per-customer memory vault system, PostgreSQL-backed with FalkorDB graph layer + Graphiti MCP endpoint
   - **George's vault**: `44401b45-fe49-4138-be21-c302297f6b0c` — MCP URL: `https://memory.sunaiva.ai/mcp/?vault_id=44401b45-fe49-4138-be21-c302297f6b0c`
   - **Kinan's vault**: `41f4785c-e9e0-43ac-b6e8-eedb571fba57`
   - **FalkorDB + Graphiti**: Sovereign stack via `zepai/knowledge-graph-mcp:latest` Docker image; ports 6379 (FalkorDB), 3000 (UI), 8000 (Graphiti MCP)
   - **docker-compose sovereign stack**: `E:\genesis-system\Sunaiva\ai-memory\deploy\docker-compose.yml` — 2 containers: `memory-engine` + `pipeline`
   - **PostgreSQL sunaiva schema**: 8 tables — users, vaults, vault_entities, vault_decisions, vault_preferences, vault_conversations, api_keys, usage_events. Currently: 1772 vault_entities, 4 vault_decisions
   - **RLM = Recursive Language Models** (Kinan's definition, Rule 15 HARDWIRED) — NOT "Relational Semantic Memory" as Gemini incorrectly wrote
   - **Elestio dashboard URL**: NOT at `app.elest.io` (ERR_NAME_NOT_RESOLVED) nor `app.elestio.com` (ERR_NAME_NOT_RESOLVED) — actual login URL still unknown
   - **Python path**: `py -3` in cmd shell works; `python`/`python3` not in PowerShell PATH; Python 3.13 at `C:\Program Files\Python313\python.exe`
   - **Gemini CLI files created (problematic)**: `RLM_WORLD_CLASS_PLAN.md`, `RLM_ELESTIO_PLAN.md`, `RLM_PLAN_SUMMARY.md` — all reinventing existing Genesis architecture

3. Files and Code Sections:
   - **`E:\genesis-system\.claude\worktrees\intelligent-yalow\provision_george_vault.py`** (READ + EXECUTED, 106 lines)
     - Provisions sunaiva schema, Kinan vault, George vault in PostgreSQL
     - Ran successfully via `py -3` in cmd shell
     - Output confirmed: George vault ID `44401b45-fe49-4138-be21-c302297f6b0c`, 1772 total entities
     - Key credential used: `postgresql-genesis-u50607.vm.elestio.app:25432` / postgres / `etY0eog17tD-dDuj--IRH`

   - **`E:\genesis-system\Sunaiva\ai-memory\deploy\docker-compose.yml`** (READ, 94 lines)
     - THE sovereign production stack for Elestio VPS deployment
     - Service `memory-engine`: `zepai/knowledge-graph-mcp:latest`, ports 6379/3000/8000
     - Service `pipeline`: custom build from `./pipeline/`, port 8080
     - Environment: `OPENAI_API_KEY=sk-or-v1-...` (OpenRouter), `MODEL_NAME=google/gemini-2.0-flash-001`
     - `FALKORDB_PASSWORD=sunaiva2026`, `FALKORDB_DATABASE=sunaiva_memory`

   - **`E:\genesis-system\config\secrets.env`** (READ, 119 lines)
     - Contains PostgreSQL creds: `postgresql-genesis-u50607.vm.elestio.app:25432` / postgres / `etY0eog17tD-dDuj--IRH`
     - Does NOT contain Elestio dashboard login or sunaiva-memory SSH credentials
     - Contains Telnyx, GHL, Stripe, n8n, OpenRouter, Namecheap, GoDaddy credentials

   - **`E:\genesis-system\credentials\MASTER_CREDENTIALS.md`** (READ, 60 lines)
     - PostgreSQL confirmed: `postgresql-genesis-u50607.vm.elestio.app:25432` / postgres / `etY0eog17tD-dDuj--IRH`
     - No Elestio dashboard URL or sunaiva-memory SSH details

   - **`E:\genesis-system\Sunaiva\ai-memory\deploy\` directory** (LISTED)
     - Files: `.env.example`, `DEPLOY.md`, `docker-compose.yml`, `pipeline/Dockerfile`, `pipeline/main.py`, `pipeline/requirements.txt`

   - **Gemini-created files (problematic, need review)**:
     - `RLM_WORLD_CLASS_PLAN.md` — reinvents existing Genesis architecture, wrong RLM definition
     - `RLM_ELESTIO_PLAN.md` — duplicates existing Elestio infrastructure decisions
     - `RLM_PLAN_SUMMARY.md` — summary of wrong plan

4. Errors and fixes:
   - **`python` / `python3` not found in PowerShell PATH**:
     - Found Python 3.13 at `C:\Program Files\Python313\python.exe`
     - Fix: used `py -3 provision_george_vault.py` in cmd shell — worked
   - **PowerShell `&&` operator not valid**:
     - Error: "The token '&&' is not a valid statement separator in this version"
     - Fix: removed `&&` chaining, ran script directly with full path
   - **Script path quoting in PowerShell**:
     - Quoted paths with spaces (`"C:\Program Files\Python313\python.exe" "path..."`) caused parse errors
     - Fix: used `py -3` launcher with unquoted path in cmd
   - **SyntaxWarning in provision_george_vault.py**:
     - `print("Schema and all tables created\!")` has invalid escape sequence `\!`
     - Non-blocking warning only, script ran successfully
   - **Elestio dashboard URL unknown**:
     - `app.elest.io` → ERR_NAME_NOT_RESOLVED
     - `app.elestio.com` → ERR_NAME_NOT_RESOLVED
     - `elest.io/login` → redirects to marketing page
     - Status: UNRESOLVED — dashboard login URL still needed
   - **Gemini RLM terminology error**:
     - Gemini wrote "RLM = Relational Semantic Memory" throughout its plans
     - CORRECT per Genesis Rule 15: RLM = Recursive Language Models
     - User queued correction: "its called recursive language model. please read the MIT paper on this"

5. Problem Solving:
   - **PostgreSQL provisioning**: COMPLETE — sunaiva schema + Kinan vault + George vault all confirmed in Elestio PostgreSQL. George vault_id = `44401b45-fe49-4138-be21-c302297f6b0c`
   - **Elestio dashboard access**: BLOCKED — cannot find working dashboard URL. Both app.elest.io and app.elestio.com return DNS errors. Need correct URL from another source.
   - **Gemini reinventing the wheel**: ROOT CAUSE identified — Gemini CLI agents don't have access to Genesis context (CLAUDE.md, GLOBAL_GENESIS_RULES.md, existing architecture maps, existing docker-compose files). They operate without the CHECK-EXISTING-FIRST protocol (Rule 16). They also don't know Genesis Rule 15 about RLM terminology.
   - **Docker Desktop**: Kinan confirmed it exists and can be started; OR Elestio managed service is option. This is NOT a blocker as Gemini claimed.

6. All user messages:
   - (Pre-compaction, via summary): "is the sunaiva-memory service correctly hooked up as the sunaiva memory mcp homebase for private memory instances, one for each customer? show me the memory mcp visual map design now. use excalidraw skill"
   - (Pre-compaction, via summary): "where then is falkor db ?"
   - (Pre-compaction, AskUserQuestion answer): Stack = "Both — FalkorDB as graph layer ON TOP of PostgreSQL"; Deploy target = "Elestio sunaiva-memory VPS (recommended)"
   - **THIS SESSION**: "why is it that genesis agents like gemini cli here keep reinventing the wheel when genesis already has all this in place? check its latest work and advise" [with Gemini CLI transcript showing RLM plan work and wrong "Relational Semantic Memory" definition]
   - **Gemini's queued message** (from Kinan to Gemini, shown in transcript): "its called recursive language model. please read the MIT paper on this"

7. Pending Tasks:
   - **IMMEDIATE**: Respond to user's question about Gemini reinventing the wheel — diagnose root cause, check Gemini's work, advise. Address RLM terminology correction.
   - SSH into Elestio sunaiva-memory VPS + deploy docker-compose (FalkorDB + Graphiti) — BLOCKED on finding dashboard URL for SSH credentials
   - Set `SUNAIVA_DB_*` + `FALKORDB_*` env vars on Elestio sunaiva-memory service
   - DNS: point `memory.sunaiva.ai` → Elestio sunaiva-memory VPS IP
   - Smoke test: Graphiti MCP recall() + remember() via SSE for George

8. Current Work:
   User sent new message mid-task. I was navigating `elest.io` looking for the Elestio dashboard login to get SSH credentials for the sunaiva-memory VPS. Browser was showing Elestio marketing page, and I had just tried taking a snapshot to find the "Sign In" link. The snapshot output was too large to read directly.

   Simultaneously, user sent: "why is it that genesis agents like gemini cli here keep reinventing the wheel when genesis already has all this in place? check its latest work and advise" — with a full Gemini CLI transcript showing it created `RLM_WORLD_CLASS_PLAN.md`, `RLM_ELESTIO_PLAN.md`, `RLM_PLAN_SUMMARY.md`, incorrectly defined RLM as "Relational Semantic Memory", falsely flagged Docker as unavailable (Docker Desktop exists), and asked permission to deploy Elestio services that Genesis already has.

9. Optional Next Step:
   Address the user's most recent explicit request: **diagnose and advise on why Gemini CLI reinvents existing Genesis work**.

   Direct quote from user: "why is it that genesis agents like gemini cli here keep reinventing the wheel when genesis already has all this in place? check its latest work and advise"

   The diagnosis: Gemini CLI sub-agents lack Genesis system context injection — they don't receive CLAUDE.md rules, CHECK-EXISTING-FIRST protocol (Rule 16), or RLM terminology disambiguation (Rule 15). They operate as blank-slate agents. The Gemini-created plans (`RLM_WORLD_CLASS_PLAN.md`, `RLM_ELESTIO_PLAN.md`) duplicate what Genesis already has in `Sunaiva/ai-memory/deploy/docker-compose.yml` and the existing Elestio infrastructure. The correct RLM definition per Rule 15 is **Recursive Language Models** — not "Relational Semantic Memory" as Gemini wrote.
</summary>

service_tier: standard

type: assistant


hookEvent: SubagentStop

hookName: SubagentStop

command: wsl.exe -e python3 /mnt/e/genesis-system/.claude/hooks/observability_logger.py --event subagent_stop