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Forget About Memory: Building a Context OS for Your Hermes Agent

Most AI memory is a sticky note. This flow breaks down an 11-layer context architecture for Hermes Agent — identity, facts, procedures, session archives, compression, and scheduled routines — and the distinctions that decide whether your agent actually remembers how you work.

Hermes AgentXforgetaboutmemorybuildingcontextstickynote.
Category
Memory & Context
Level
Community
Author
Tony
Reading time
5 min

Most AI memory is a sticky note. This flow breaks down an 11-layer context architecture for Hermes Agent — identity, facts, procedures, session archives, compression, and scheduled routines — and the distinc...

Community flow by Tony. View source

Flow sections

Section outline mirrored from the public community flow. Use the source page for full prose and examples.

Upstream outline

  1. The core idea
  2. How to audit your own memory
  3. The 11 layers
  4. Layer 1 — SOUL.md: the identity file
  5. Layer 2 — MEMORY.md and USER.md: always-on context
  6. Layer 3 — Holographic memory (fact_store): structured facts
  7. Layer 4 — Session database and session_search: the archive
  8. Layer 5 — LCM: context compression
  9. Layer 6 — Skills: procedural memory
  10. Layer 7 — Project-local context files
  11. Layer 8 — Nexus: the second brain
  12. Layer 9 — Self-improving files: after-action learning
  13. Layer 10 — Cron jobs: scheduled context loops
  14. Layer 11 — Hooks, plugins, and MCP: expansion surfaces

Section map

The core idea

Frames the core idea for this Memory & Context workflow, including the operating context to verify in the source page.

How to audit your own memory

Frames how to audit your own memory for this Memory & Context workflow, including the operating context to verify in the source page.

The 11 layers

Frames the 11 layers for this Memory & Context workflow, including the operating context to verify in the source page.

Layer 1 — SOUL.md: the identity file

Frames layer 1 — soul.md: the identity file for this Memory & Context workflow, including the operating context to verify in the source page.

Layer 2 — MEMORY.md and USER.md: always-on context

Frames layer 2 — memory.md and user.md: always-on context for this Memory & Context workflow, including the operating context to verify in the source page.

Layer 3 — Holographic memory (fact_store): structured facts

Frames layer 3 — holographic memory (fact_store): structured facts for this Memory & Context workflow, including the operating context to verify in the source page.

Layer 4 — Session database and session_search: the archive

Frames layer 4 — session database and session_search: the archive for this Memory & Context workflow, including the operating context to verify in the source page.

Layer 5 — LCM: context compression

Frames layer 5 — lcm: context compression for this Memory & Context workflow, including the operating context to verify in the source page.

Implementation notes

  • Use this Memory & Context flow as a pattern library entry: start from the summary, then inspect the linked source before copying any commands, schedules, or account wiring.
  • Primary decision areas: The core idea, How to audit your own memory, The 11 layers, Layer 1 — SOUL.md: the identity file, Layer 2 — MEMORY.md and USER.md: always-on context. Treat those sections as checkpoints for scope, cost, orchestration, and human review.
  • Useful search signals for this flow: forget, about, memory, building, context. These are derived from the public title and summary, not from private runtime data.

Decision table

Best fitMemory & Context workflow pattern

Use when the summary outcome matches your own workflow and the core idea is relevant to your setup.

Verify firstAccounts, models, schedules, and tool access

Open the source sections for The core idea and How to audit your own memory before wiring credentials or automation.

Review boundaryHuman approval point

Keep human approval for merges, spending, external messages, credentials, and unattended execution.

Verification checklist

  1. Confirm the workflow outcome matches your use case: Most AI memory is a sticky note. This flow breaks down an 11-layer context architecture for Hermes Agent — identity, facts, procedures, session archives, compression, and scheduled routines — and the distinctions that decide whether your agent actually remembers how you work.
  2. Open the source section for The core idea before copying commands, prompts, or schedules.
  3. List every credential, account, model, and external service the flow would touch.
  4. Define the human approval step before spending money, sending messages, trading, merging, or running unattended.
  5. Run a small dry run and compare the result with the source sections for The core idea and How to audit your own memory.

Risk notes

Automation

Start with a bounded dry run, logs, and a manual stop path before enabling recurring or unattended execution.

External messages

Keep human review before sending public posts, customer messages, trading instructions, or team notifications.

Runtime access

Check filesystem, shell, browser, repository, and server permissions before granting the agent write access.

What this page covers

  • Most AI memory is a sticky note. This flow breaks down an 11-layer context architecture for Hermes Agent
  • identity, facts, procedures, session archives, compression
  • and the distinctions that decide whether your agent actually remembers how you work.

Source mirror note

This page is generated from the public Hermes Bible index so the clone has the same route coverage and search surface. It stores the public title, category, summary, and source link locally; use the source page for full upstream text and updates.

Open source page