> ## Documentation Index
> Fetch the complete documentation index at: https://docs.heylinger.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Memory layers

> Compare the personal memory and agent memory, and know which one to check when an agent forgets or remembers wrong.

Linger remembers at two levels, and each answers a different question. The **personal memory** records the facts of your work: people, clients, projects, and what was decided. **Agent memory** records what one agent learned about how to work with you.

A good human assistant keeps both. They keep files on your clients and projects. They also remember which approach worked last time. The comparison stops at one point. Linger updates both levels in the background, mostly at night or when the agent is idle, not the moment you speak.

Tell one agent a fact once, in any chat, and every agent that works for you can find it later. This page compares the two levels, explains when each updates, and shows what to do when a memory is wrong.

![Over nine days, the Acme rollout wiki page starts from Gmail, records the agreed pricing, and later adds the March start.](https://mintcdn.com/lev9-doc/iWlaFXt9R5YUC2Ro/images/feature-wiki-memory.gif?s=5a49753ea92dcf5a0c4ea58c6801e7dc)

One wiki page grows over nine days.

## How do the two levels compare?

The two levels differ in scope, reader, and update schedule. Use this table to tell them apart.

| Attribute | Personal memory | Agent memory |
| - | - | - |
| What it holds | Typed pages for clients, contacts, projects, topics, and Sessions. | Your preferences, proven procedures, decisions, facts about the environment, and lessons from failures. |
| Scope | One per person. | One per agent, across all its Rooms. |
| Who reads it | Every agent that works for you, from any Room. | Only the agent that owns it. |
| How agents read it | By search with `teamhub knowledge search`. | A short summary on the first message of a session, then files on demand. |
| What feeds it | Your conversations, meetings, inbox, and documents. | That agent's Room conversations. |
| When it updates | Each night; a meeting updates it soon after it ends. | Extracted after several runs, merged once the agent has been idle for a while. |
| Where agents see it | Search results, and read-only files for Another Me. | The read-only `agent-memory/` folder in each of its workspaces. |

## How does the personal memory work?

The personal memory gives each real-world entity one page, so every fact has one home. Clients, contacts, projects, and topics each get a page. Each conversation or meeting gets a Session page that links to the entities it touched.

When you connect your inbox, Another Me reads back through the last few months to start the wiki. From then on, your conversations flow back in each night. A model proposes changes section by section, and the app checks each change against the page it replaces.

The wiki guards its own history:

* **Sources.** Each fact cites the message or file version it came from.
* **Lists.** A list section changes one entry at a time, so other entries stay exactly as they were.
* **Change Log.** The app, not the model, writes one dated line for each rewrite, edit, retraction, or merge.

Agents search two indexes: the wiki pages for overviews, and the original messages, transcripts, documents, and emails for exact details. An agent must search the originals before it says something was never recorded. Search uses keywords only, with alternate wordings, so a question in one language can find a page written in another. See [Personal memory](https://docs.heylinger.com/knowledge/personal-memory.md).

## How does agent memory work?

Agent memory crosses Rooms but not agents. What an agent learns in one Room, it can use in the next. No other agent sees it.

The agent does not write its memory during a chat. Three stages run in the background:

1. **Extract.** After several successful runs, new messages and tool calls become a session summary and candidate memories.
2. **Consolidate.** After the agent has been idle for a while, or when the context is compacted, the candidates merge into the memory. Duplicates and disproven facts are removed.
3. **Recall.** The first message of a new session carries the summary index. The agent reads the rest on demand.

Agent memory leaves out progress notes, generic advice, secrets, and guesses. It reads only Room conversations, not delegated Tasks or document work. See [Agent memory](https://docs.heylinger.com/knowledge/memory.md).

## Who does the background work?

Your own computer does the background work for both levels. Each update is a model call, without tools, to the Codex or Claude Code you signed in to. The calls use that account and count against it.

Background work waits its turn on every computer. It starts only once your chats have been quiet for a while, one job at a time, so it never slows a conversation. Agent memory runs before the wiki refresh. This queue matters most on a local model, which slows down for every extra request. See [Model scheduling](https://docs.heylinger.com/models/model-scheduling.md).

## What should you do when a memory is wrong?

What you say now wins. Correct the fact in a chat, in plain words, and the agent uses the correction at once. The stored memory catches up later:

* **Personal memory.** The page is rewritten in the next nightly update, and the Change Log records it. Your correction is searchable sooner, shortly after the conversation goes quiet.
* **Agent memory.** The next extraction picks up the correction. The next consolidation merges it into the memory.

If an agent says something was never recorded, ask it to search the originals. If a wiki fact looks wrong, ask the agent which message or file it cites.

## Keep learning

> [card] [Personal memory](https://docs.heylinger.com/knowledge/personal-memory.md)
>
> See how wiki pages are built, searched, and changed.

> [card] [Agent memory](https://docs.heylinger.com/knowledge/memory.md)
>
> Learn when an agent's memory updates and where to find it.

> [card] [Proactive Another Me](https://docs.heylinger.com/agents/proactive.md)
>
> See how Another Me learns rules from your replies.

> [card] [Where your data lives](https://docs.heylinger.com/concepts/where-your-data-lives.md)
>
> Know which machine keeps each level.


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