A Clean OpenClaw Memory Setup That Keeps Context Useful

Memory is useful only when it stays accurate. Treat it like an operating log, not a junk drawer.

The short answer

• Store durable facts, decisions, preferences, and open loops.
• Keep daily notes short.
• Promote stable facts into curated memory.
• Keep external knowledge in a separate wiki or source library.
• Delete stale or wrong context quickly.

What belongs in memory

Good memory helps the agent avoid asking the same questions.

Store:

• business facts
• customer commitments
• owner preferences
• recurring policies
• open follow-ups
• decisions and reasons

Each note should be specific enough to act on later.

Bad note:

> Customer was unhappy.

Good note:

> June 12: Jamie asked for a revised invoice by Friday. Do not send until Anton approves the discount.

What does not belong in memory

Keep memory clean.

Do not store:

• passwords
• API keys
• payment details
• full customer dumps
• temporary guesses
• old facts you have not verified

Memory should reduce risk, not create it.

A simple structure

Use three layers:

• daily memory for events and open loops
• curated memory for stable facts and policies
• a separate knowledge base for source material, research, and reusable references

Daily notes capture what happened. Curated memory captures what should keep influencing future work. The knowledge base holds material the agent may need to read, but should not permanently believe.

Example daily sections:

• Decisions
• Follow-ups
• Customer commitments
• Things to verify

Keep memory and knowledge separate

Do not turn agent memory into a dumping ground for every article, transcript, email thread, and meeting note. That feels powerful for a week. Then the agent starts carrying too much stale material into simple tasks.

Use a memory ladder instead:

1. Store durable facts in memory: owner preferences, business rules, active commitments, and known constraints.
2. Store reference material in a wiki or vault: docs, SOPs, call notes, research, transcripts, and source links.
3. Store searchable history separately: prior sessions, old decisions, and finished work logs.

Example: if a customer sends a ten-page onboarding document, do not paste the whole thing into memory. Put the document in the workspace or knowledge vault. Save one memory: "Customer onboarding docs live in /clients/atlas/onboarding/; check them before drafting setup instructions."

That gives the agent a pointer without forcing every future task to carry the entire document.

This is where tools like Obsidian, NotebookLM, or a dedicated LLM wiki help. Memory tells the agent what matters. The wiki gives it somewhere to look when it needs source detail.

Add a quality gate before writing memory

Before saving a memory, ask one question: should this affect future decisions?

If the answer is no, store it as a note, not memory.

Good fit for memory:

• "Sameer wants public Claw Empire pages to avoid public pricing."
• "Support replies can be drafted, but sending requires approval."
• "Use Linear for product tasks and Slack for team updates."

Bad fit for memory:

• a full Fireflies transcript
• every sentence from a client email
• a guess the agent has not verified
• research copied from a website

For higher-stakes teams, use an approval step. Let the agent propose memory changes at the end of a session, then approve only the durable ones. This prevents memory from becoming an unreviewed belief system.

Maintenance routine

Once a week, clean memory.

Checklist:

1. Remove stale tasks.
2. Promote durable facts.
3. Mark resolved follow-ups.
4. Fix wrong assumptions.
5. Keep entries short.

This takes minutes and prevents context rot.

Common mistakes

Avoid:

• saving everything
• mixing secrets with notes
• keeping conflicting facts
• writing vague memories
• never pruning old context

An agent with bad memory becomes confidently wrong.

Recap

• Memory is for durable context.
• Daily logs should be short.
• Curated memory should stay clean.
• Stale memory is worse than no memory.

Next step

For resets and context boundaries, read: OpenClaw Session Management.