How OpenCLAW Memory Actually Works: Fixing Agent 'Forgetting'

How OpenCLAW Memory Actually Works
OpenCLAW agents don't have persistent memory between conversations. Every time you send a message, the agent reads several files (SOUL.md, USER.md, MEMORY.md, and recent session history) and constructs its "memory" from scratch. It's not remembering - it's reading its notes.
Five Reasons Your Agent Forgets Things
Reason 1: Your session is too old
Every message in your current session gets included in each new API call. After 2-3 weeks, this becomes thousands of tokens. The model either hits its context limit (causing early conversations to get silently truncated) or OpenCLAW runs compaction which summarizes everything but loses detail.
Fix: Use /new regularly - daily at minimum, and before any big task. This clears the conversation buffer while keeping all files intact.
Reason 2: Important info is in chat history, not in files
If you told your agent something in a conversation 3 weeks ago, that info lives in session history which gets truncated. Anything your agent should ALWAYS know needs to be in a file, not in chat.
Fix: Put permanent information in USER.md:
# About me
- Name: [your name]
- Partner: [name]
- Location: [city]
- Job: [role]
- Timezone: [timezone]
Preferences
- Communication: direct, no filler
- Morning routine: briefing at 8am
- Never schedule meetings before 10am
- Coffee order: [whatever it is, seriously]
Reason 3: MEMORY.md is a bloated mess
Most people never structure MEMORY.md. After a month it becomes a giant wall of text that the model skims instead of reads. Important facts get buried under irrelevant details.
Fix: Structure your MEMORY.md into clear sections:
# People
- Sarah (wife): works at [company], birthday June 12
- Mike (coworker): handles the frontend, prefers slack over email
Active Projects
- Kitchen renovation: contractor is Dave, budget $15K, starts April
- Q2 presentation: due March 28, needs sales data from Mike
Decisions Made
- Switched from opus to sonnet on March 5 (cost reasons)
- Using brave search API instead of google (free tier sufficient)
Recurring Tasks
- Daily briefing at 8am (calendar + email + weather)
- Weekly grocery list every Sunday at 6pm
Reason 4: You don't have a memory maintenance routine
Memory files grow forever. After 2 months, your MEMORY.md has 300 lines and half are outdated or irrelevant. The model wastes tokens reading about finished projects.
Fix: Set up a nightly memory cron. Add this to your agent's instructions:
every night at 11pm:
1. review today's conversations
2. extract any new facts, decisions, or commitments
3. add them to the correct section in MEMORY.md
4. remove anything that's no longer relevant
5. start a fresh session
Reason 5: You're confusing session memory with long-term memory
Understand the hierarchy:
- SOUL.md: Identity and personality. Loaded every time. Never changes unless you change it.
- USER.md: Facts about you. Loaded every time. Update when your life changes.
- MEMORY.md: Ongoing context. Loaded every time. Grows and gets pruned.
📖 Read the full source: r/openclaw
👀 See Also

Understanding the .claude/ folder structure for Claude Code configuration
The .claude/ folder contains two directories: project-level for team configuration and global ~/.claude/ for personal preferences. CLAUDE.md files provide instructions that Claude follows throughout sessions, with CLAUDE.local.md for personal overrides.

Open-source launch playbook for OSS LLM and local AI projects
An open-source playbook addresses discoverability issues for LLM and local AI projects by providing structured guidance on pre-launch preparation, launch-day execution, and post-launch follow-up. It includes templates and strategies for community distribution, creator outreach, and SEO optimization.

OpenClaw Sub-agents: Don't Treat a Reply as a Completion Receipt
OpenClaw's sessions_spawn is non-blocking — it returns a runId when work is accepted, not complete. A parent can prematurely report success while a child is still running, failed, or lost.

How to run OpenClaw agents for free using cloud APIs or local models
A detailed guide explains how to run OpenClaw agents at zero cost using free cloud tiers from OpenRouter, Gemini, and Groq, or by running local models via Ollama with specific configuration tips to avoid common pitfalls.