The OpenClaw Setup Guide Nobody Gave You

Installing OpenClaw takes five minutes. Making it actually work takes knowing what to do next.

We have been running OpenClaw in production for three weeks now. 47 active sessions. Five concurrent projects. Agents that coordinate overnight, evaluate each other's performance, and occasionally do things we did not explicitly ask for.

None of that happened on day one.

On day one, memory did not persist between sessions. Telegram messages vanished into the void. API keys were sitting exposed in the workspace folder. Cron jobs stopped firing and nobody noticed for 36 hours. The default model config worked fine until it did not, and debugging at midnight with no documentation is exactly as fun as it sounds.

This is everything we learned the hard way, organized into the checklist we wish someone had handed us before we started.

If you just installed OpenClaw, stop what you are doing and go through this first. It will take 30 to 60 minutes. It will save you 30 to 60 hours.

0. Before You Touch Anything: Set Up Your Safety Net

The single most useful thing you can do before configuring anything is create a separate Claude project specifically for OpenClaw troubleshooting.

Add the OpenClaw documentation as context. When something breaks at 2AM — and something will break at 2AM — you want a dedicated space where you can paste error logs and get answers without contaminating your main workflow.

Inside OpenClaw itself, install the clawddocs skill early. This gives your agent access to the same documentation context, which means it can often diagnose its own problems before you need to intervene.

Quick baseline checks you should run immediately:

openclaw gateway status
openclaw gateway restart
openclaw doctor

If openclaw doctor flags anything, run openclaw doctor --repair before proceeding. Fix the foundation before you build the house.

1. Personalization: Make It Yours in the First Ten Minutes

OpenClaw ships with placeholder identity files. Most people skip these and wonder why their agent gives generic, corporate-sounding responses.

Three files to update immediately:

USER.md — Who you are. What you care about. What projects you are working on. The more context you put here, the less you have to repeat yourself in every conversation.

IDENTITY.md — Who the agent is. Give it a name. Give it a personality. This is not cosmetic. An agent with a defined identity gives more consistent, opinionated responses than one running on defaults.

SOUL.md — The behavioral rules. How formal should responses be? What topics are off-limits? When should it ask before acting versus just doing the thing? Write these down explicitly. The agent will follow them.

This takes ten minutes and immediately changes the quality of every interaction from that point forward.

2. Memory: The Thing That Breaks First and Matters Most

Memory is the entire point of running a persistent agent instead of just using ChatGPT in a browser tab. If memory is not working correctly, you are paying for infrastructure that gives you nothing extra.

Three things need to be true:

MEMORY.md must exist and be actively maintained. This is the agent's long-term memory. Important decisions, learned preferences, project context, relationship notes. If this file does not exist, create it. If it exists but is empty, that is a problem.

Daily memory files need to be created automatically. The pattern is memory/YYYY-MM-DD.md. Every day should get its own file where raw observations, decisions, and events get logged. This is the journal. MEMORY.md is the curated summary.

Heartbeat instructions must include memory maintenance. Add explicit instructions to your HEARTBEAT.md telling the agent to:

• Create today's memory file if it does not exist
• Append major decisions and learnings throughout the day
• Periodically review daily files and promote important items to MEMORY.md
• Clean up outdated information from MEMORY.md

Without this loop, memory degrades within days. The agent forgets context, repeats mistakes, and loses the compounding advantage that makes persistent agents valuable in the first place.

3. Model Configuration: Reliability First, Cost Second

The default model works. Until it hits a rate limit at the worst possible time, and your overnight automation silently stops.

Set up a proper model stack:

Primary model: Whatever gives you the best balance of quality and reliability for your use case. We run Claude for most tasks. Some people prefer GPT. Pick one and commit.

Fallbacks: Configure at least two fallback models through different providers. If Anthropic goes down, your agents should automatically route through OpenRouter or another gateway. If that fails, there should be a third option.

Configure these in:

agents.defaults.model.primary
agents.defaults.model.fallbacks

The principle is simple: optimize for reliability first, then cost. An agent that runs 24/7 on a slightly more expensive model is infinitely more valuable than one that saves money but drops dead every time a provider has an outage.

4. Security: The Part Everyone Skips Until Something Bad Happens

We are going to be direct about this because the default setup is not secure enough for production use.

Move your secrets out of the workspace immediately. Create a secure env file:

~/.openclaw/secrets/openclaw.env

Set permissions:

chmod 700 ~/.openclaw/secrets/
chmod 600 ~/.openclaw/secrets/openclaw.env

API keys, tokens, and credentials should live here and nowhere else. Not in workspace files. Not in MEMORY.md. Not committed to git.

If you are running on a VPS:

• Allow inbound connections only from your trusted IP addresses
• Keep the gateway auth token enabled at all times
• Never expose the gateway publicly without authentication

Telegram security:

• Set dmPolicy: "allowlist" — this means only approved Telegram IDs can interact with your agent
• Configure allowFrom and groupAllowFrom with specific Telegram user IDs
• This prevents random people from talking to your agent and potentially triggering unintended actions

We learned this one the hard way. An unsecured Telegram bot is an open door into your entire agent infrastructure. Lock it down before you connect it to anything important.

5. Telegram: Getting It Actually Working

Telegram is the most common interface for OpenClaw and also the one with the most configuration gotchas.

For group chat functionality:

• Disable bot privacy mode in BotFather — otherwise your bot only sees messages where it is explicitly mentioned
• Add the bot as an admin in every group where you want it active
• Set group requireMention = false if you want proactive behavior where the agent responds to relevant messages without being tagged

For topic-based workflows:

• Enable topics in groups when you want separated workstreams
• Set topic-specific systemPrompt when a topic has a dedicated job — for example, a "Research" topic gets different instructions than a "Trading" topic

Quality of life settings:

• Add a default acknowledgment reaction (we use 👀) so you can see when a message has been received and is being processed
• Enable streaming responses so you are not staring at a blank chat waiting for a complete response

6. Browser and Research Stack

Your agent needs to access the internet. The default setup does not include web search.

Add a Brave API key for web search and fetch capabilities. This is free for reasonable usage and gives your agent the ability to research topics, verify information, and pull current data.

Browser profile strategy:

Use the OpenClaw-managed browser profile (node/openclaw) for all automation tasks. This is isolated, stable, and does not interfere with your personal browsing.

Use the Chrome relay (profile="chrome") only when you specifically need access to logged-in sessions — for example, posting to social media accounts or accessing services that require your personal authentication.

Mixing these up is a common mistake. Running automation through your personal Chrome profile leads to session conflicts, unexpected logouts, and the occasional moment where your agent accidentally posts something from your personal account.

7. Heartbeat and Cron: Preventing Silent Failures

Cron jobs are the backbone of autonomous operation. They are also the thing most likely to silently stop working without anyone noticing.

Add these checks to your HEARTBEAT.md:

- Check critical cron jobs for stale lastRunAtMs
- If stale (missed expected run), force-run the missed jobs
- Report exceptions briefly in the daily memory file

This creates a self-healing loop. When a cron job fails, the heartbeat catches it on the next cycle and either re-runs it or flags it for human attention.

Without this, you end up in the situation we were in during week one — discovering three days later that your overnight research automation had silently crashed on Tuesday and nothing had run since.

8. Dedicated Accounts: Separation of Concerns

Create dedicated accounts for your agent infrastructure:

• A separate Google account — for any Google services the agent needs to access
• A dedicated email address — Gmail or AgentMail, used exclusively by the agent
• A separate GitHub account — for code operations, commits, and repository management

Why this matters: clean separation of permissions, easier auditability, and no risk of your personal accounts being affected by agent actions.

When your agent commits code, you want it committing as "Agent Bot" from a dedicated account, not as your personal GitHub profile. When it sends emails, you want those coming from an agent-specific address, not your inbox.

This is a fifteen-minute setup that prevents a category of problems that are extremely annoying to untangle after the fact.

9. Skills: Building Your Agent's Toolkit

Skills are how you extend what your agent can do. The default installation is capable but generic.

Install the summarize skill immediately. This is high leverage — your agent can summarize long documents, email threads, meeting notes, and research findings on demand.

Create custom skills for recurring workflows. If you find yourself asking your agent to do the same multi-step process more than twice, turn it into a skill. Skills are more reliable than ad-hoc instructions because they encode the exact steps, error handling, and expected outputs.

Add voice transcription if you prefer speaking over typing. Whisper or OpenAI's Whisper API integrated as a skill means you can voice-note your instructions and have them accurately transcribed for the agent.

The principle: if you repeat it two or three times, skill it. The upfront investment of 20 minutes creating a skill saves hours of repeated explanation.

10. The Meta Layer: Watching the Watchers

Once everything above is configured, add one more layer that most people miss.

A monitoring heartbeat that checks the health of everything else.

Your HEARTBEAT.md should include:

• Are all critical cron jobs running on schedule?
• Is memory being maintained (today's file exists, MEMORY.md was updated this week)?
• Are API credits within expected burn rates?
• Are there any stuck or silent agent sessions?

This is the difference between an agent that works today and one that works reliably for months. Systems degrade. Configurations drift. API keys expire. The monitoring layer catches these before they become outages.

The Acceptance Checklist

Run through this after setup:

• [ ] SOUL.md, USER.md, IDENTITY.md customized with real content
• [ ] MEMORY.md exists and daily memory flow is working
• [ ] Heartbeat includes cron monitoring and memory maintenance
• [ ] Primary model plus at least two fallbacks configured
• [ ] Secrets moved to secure env file with strict permissions
• [ ] Telegram allowlists configured, bot privacy disabled for groups
• [ ] Brave API key set, browser profile strategy established
• [ ] Dedicated Google, email, and GitHub accounts created
• [ ] Summarize skill installed plus at least one custom skill
• [ ] Monitoring heartbeat checking system health

If everything is checked, your OpenClaw installation is no longer a fresh install. It is a production system.

What Happens Next

We went through this entire process during our first week of building Gas Town — the autonomous agent city we documented in our "From Automation to Swarm Intelligence" series. Every lesson here came from something breaking and us figuring out why.

The difference between people who get value from OpenClaw and people who give up after a week is almost always this post-install configuration. The tool is powerful. But power without setup is just potential energy.

Spend the hour. Do the checklist. Then let the agents work.

That is when things get interesting.