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@danialhasan
Created June 15, 2025 00:05
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Founder Vertical Memory Protocol

This document defines the vertical memory system for a solo founder operating with AI agents (O3Pro, Claude Code) in your monorepo.


1. Daily Memory Capture

  • New chat per day:

    • Title: YYYY-MM-DD (e.g., 2025-06-11)
    • Import the latest Weekly Control Review table (from canvas or markdown file)
  • End-of-day (EOD):

    • Write an agent_summary block at the bottom:

      ### agent_summary – YYYY-MM-DD
      - o3pro-recsys: [short bullet]
      - claude: [short bullet]
      - (others…)
    • Pin it or mark clearly in the chat/file.


2. Weekly Memory Consolidation

  • Every Monday, 11AM:

    • Open the current chat or markdown file with the canvas/table view.

    • Gather the last 7 days of agent_summary blocks.

    • Paste them into a new section/message.

    • Prompt:

      Run control review for [date range]. Surface all progress, blockers, and next actions in table form.
      
  • Update:

    • Overwrite the previous Weekly Control Review table with the new one.
    • Refresh meta-summary and checklist based on actual progress.

3. Propagation & Evolution

  • When starting a new daily chat, import the latest table/canvas from the previous session or file.
  • Do NOT depend on chat memory—trust the explicit table/canvas only.
  • Workstreams are updated, added, or pruned in the weekly review.

4. Manual as Default, Automation Optional

  • Steps are fully manual until Stage 2 (CLI/database) automation is implemented.
  • Calendar reminders exist for both daily memory block and weekly review.
  • Protocol must take <10 minutes daily, <30 minutes weekly.

5. Scalability Guideline

  • If agent count or memory management becomes a bottleneck, implement Stage 2 automation:

    • CLI for logging summaries
    • Supabase table for weekly rollup
    • React dashboard for persistent board view

6. Protocol Ownership

  • Only the founder (you) maintain and update the memory protocol and table.
  • AI agents cannot write to canvas/table—only you manage state propagation.

TL;DR

This protocol keeps your vertical memory unbroken, your execution compounding, and your stress low—even as agent complexity grows.

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