OpenClaw in Production: 7 Lessons from Real Deployments

OpenClaw in Production: 7 Lessons from Real Deployments

We've seen dozens of teams deploy OpenClaw to production. Some succeeded smoothly. Others learned expensive lessons.

Here's what actually matters when your agent goes live.

Lesson 1: The Demo Is Not the Product

What We Learned

OpenClaw demos beautifully. It responds. It takes action. It feels magical.

Then you put it in production and discover:

• It sometimes takes 30 seconds to respond
• It occasionally misinterprets instructions
• It can get stuck in loops
• Users send inputs you never expected

The Fix

Set realistic expectations. Production agents are useful, not magical. They need:

• Timeouts for long operations
• Fallback paths when things fail
• Guardrails for unexpected inputs
• Human escalation for edge cases

Don't promise "it just works." Promise "it helps, and we've got safety nets."

Lesson 2: Users Will Try to Break It

What We Learned

Within 24 hours of deployment, someone will try:

• Prompt injection attacks
• Confusing/contradictory instructions
• Requests way outside your intended scope
• Attempts to access things they shouldn't

This isn't malice—it's curiosity. But the result is the same.

The Fix

Assume adversarial input. Design for:

• Input validation and sanitization
• Rate limiting per user
• Scope restrictions (what the agent can/can't do)
• Audit logging to see what's being attempted

Human-in-the-loop for sensitive actions. Don't let the agent do anything destructive without approval.

Lesson 3: Logging Is Not Optional

What We Learned

The first time something goes wrong, the first question is: "What did the agent do?"

Without logs, you're blind. You can't debug. You can't explain to users. You can't improve.

The Fix

Log everything:

• Every prompt received
• Every action taken
• Every output generated
• Every API call made
• Every error encountered

Make logs searchable. You need to find the exact moment things went wrong.

Retain logs appropriately. 7 days minimum for debugging. 30-90 days for compliance.

Lesson 4: The Kill Switch Gets Used

What We Learned

Every team that ran an agent for more than a month needed to stop it unexpectedly:

• Agent started looping on a bad input
• User reported something concerning
• Security team needed to investigate
• Agent was racking up unexpected API costs

The Fix

Build a kill switch you can actually use:

• One command or one click to stop
• Works immediately (not "after current task completes")
• Doesn't require SSH access or deep technical knowledge
• Can be triggered by anyone authorized

Practice using it. Don't discover problems with your kill switch during an emergency.

Lesson 5: API Costs Surprise You

What We Learned

LLM API costs are variable. An agent that costs $5/day normally can cost $500/day if:

• A user sends extremely long prompts
• The agent gets stuck retrying failed operations
• Traffic spikes unexpectedly
• Someone discovers and abuses your agent

The Fix

Implement cost controls:

• Set daily/monthly budget limits with alerts
• Implement per-request token limits
• Monitor usage patterns for anomalies
• Have automatic pause when limits are hit

Budget 3x your expected costs. Better to be surprised by unused budget than by a bill.

Lesson 6: Security Is Harder Than You Think

What We Learned

Security isn't one feature—it's a continuous practice. Common issues we've seen:

• Credentials leaked in logs or error messages
• Admin panels accidentally exposed
• API keys harvested from exposed config
• Prompt injection leading to data leakage
• OAuth tokens with too-broad permissions

The Fix

Don't DIY security for production. Use managed services or dedicated security expertise.

If you must self-host:

• Never log credentials
• Always require authentication
• Encrypt everything at rest
• Audit access regularly
• Assume you'll be attacked

Get a security review before launch. Fresh eyes catch what you miss.

Lesson 7: Start Small, Then Expand

What We Learned

Teams that tried to launch with everything—all channels, all integrations, all users—struggled.

Teams that started with one use case, one channel, a few users, then expanded—succeeded.

The Fix

Phase your rollout:

Phase 1: Internal testing

• Your team only
• One simple use case
• Heavy monitoring

Phase 2: Limited pilot

• 5-10 trusted users
• Gather feedback actively
• Fix issues quickly

Phase 3: Controlled expansion

• More users, gradually
• Add use cases one at a time
• Continue monitoring

Phase 4: General availability

• Open to all intended users
• Documentation and support ready
• Confidence in your system

Bonus: What Actually Matters

After seeing many deployments, here's what separates success from failure:

The One-Page Summary

Before You Deploy

• Set realistic expectations (it's helpful, not magic)
• Plan for adversarial input
• Set up comprehensive logging
• Build and test your kill switch
• Set API cost limits and alerts
• Get a security review
• Plan a phased rollout

During Operation

• Monitor logs daily
• Watch for cost anomalies
• Respond to user feedback quickly
• Keep kill switch accessible
• Update based on what you learn

When Problems Occur

• Use the kill switch if needed
• Check logs for what happened
• Communicate with affected users
• Fix the root cause
• Document for future reference

Why Teams Use Clawctl

These lessons informed how we built Clawctl:

We built what we wished we had when deploying our own agents.

Deploy with lessons learned → | See all security features →