Agent Memory Framework

Your agent forgets everything. Here is why.

Memory loss in AI agents is actually three separate problems pretending to be one:

1. Session continuity — the agent forgets what happened last session
2. Long-term facts — the agent forgets who you are and what matters
3. Retrieval — the agent has the info but cannot find it

Most people try to solve all three with one system and end up with something bad at everything. This framework separates them into distinct, manageable layers.

What You Get

| Layer | Solves | How | |-------|--------|-----| | Session Handoff | Continuity | Structured state transfer between sessions | | Two-Tier Memory | Long-term facts | Core (never expires) + Working (monthly review) | | PARA Organization | Retrieval | Topic-based filing instead of chronological | | Daily Notes | Timeline | Raw event log with OUTCOME/SCORE/WHY format |

The Two-Tier Memory System

Core Tier — facts that never expire: your name, timezone, communication style, key constraints. Tagged with source (direct/inferred/derived) so the agent knows confidence level.

Working Tier — current context reviewed monthly: active projects, sprint goals, temporary preferences. Stale entries get archived, not deleted.

Minimum 5 entries to be useful. Every entry sourced. No placeholders.

Who This Is For

• Your agent loses context between sessions (the #1 complaint on r/OpenClaw)
• You have tried complex memory systems that did not stick
• You want structured memory without external dependencies
• You are tired of re-explaining who you are every time your agent restarts

One file. 15 minutes to set up. No more amnesia.

$9 — One-time purchase. No dependencies. No external services. Works on any agent with workspace files.