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5-minute deployment of OpenClaw AI assistant (with troubleshooting notes)

I timed myself the last time I deployed OpenClaw from scratch. Four minutes and thirty-seven seconds — from clicking "Buy Now" to having a working AI assistant respond to my first Telegram message. And that included fumbling for my API key in a password manager.

The deployment itself is genuinely fast. What trips people up is the stuff that goes wrong after — daemon not starting, model not responding, pairing codes expiring. So this guide covers both: the quick deployment AND the troubleshooting notes I wish someone had given me on day one.

The 5-Minute Deployment

Minute 0-1: Provision Your Server

Go to the Tencent Cloud Lighthouse Special Offer page:

  1. Visit the landing page to see the OpenClaw-optimized instances.
  2. Choose the "OpenClaw (Clawdbot)" application template under the AI Agent category.
  3. Deploy by clicking "Buy Now" to launch your instance.

Pick 2 cores / 4GB RAM minimum. Choose an overseas region (Singapore, Silicon Valley) if you're connecting to international platforms like WhatsApp or Telegram. Mainland China region if you're using domestic models or platforms.

Minute 1-2: Configure Your Model

Once the instance is ready, go to the Tencent Cloud Console → your Lighthouse instance → Application Management.

Paste your LLM API key (DeepSeek, OpenAI, Claude, Gemini — whatever you prefer) into the Models section. Click Add and Apply. Wait for "in use" status.

# Alternatively, if you prefer command-line setup:
# SSH into your instance first, then:
clawdbot onboard
# The wizard will walk you through model configuration interactively

Do not hardcode API keys in any script files. Always use the console panel or environment variables.

Minute 2-4: Channel Setup & Pairing

In the Lighthouse web terminal (OrcaTerm), run:

clawdbot onboard

Navigate the wizard:

  • Disclaimer → Yes
  • Mode → QuickStart
  • Config → Use existing values
  • Model → Skip (already done)
  • Channel → Pick yours (Telegram, Discord, WhatsApp, etc.)
  • Skills → No
  • Hooks → session-memory only
  • Restart → Yes

Then go to your messaging app, send a message to your bot, grab the pairing code, and run:

openclaw pairing approve telegram <your-code-here>

Minute 4-5: Daemon Setup

loginctl enable-linger $(whoami) && export XDG_RUNTIME_DIR=/run/user/$(id -u)
clawdbot daemon install
clawdbot daemon start
clawdbot daemon status

Status healthy? You're done. Close everything. Your AI assistant is live.


The Troubleshooting Notes

Now for the part that actually saves you hours. Here are the most common issues I've hit (and seen others hit) during and after deployment.

Issue 1: "Model not responding" After Configuration

Symptom: You send a message to the bot, it acknowledges but never replies with actual content.

Cause: Usually a region mismatch. If your Lighthouse instance is in mainland China but you're using an overseas model API (like OpenAI or Anthropic), the network connection may be blocked or throttled.

Fix: Either switch to a domestic model provider (DeepSeek, Tencent Hunyuan) or redeploy your instance in an overseas region. The Custom Model Tutorial has the full list of supported providers and their base URLs.

Issue 2: Daemon Won't Start

Symptom: clawdbot daemon start returns an error or the status shows "inactive."

Fix: Make sure you ran the linger command first:

loginctl enable-linger $(whoami)
export XDG_RUNTIME_DIR=/run/user/$(id -u)

Then reinstall and restart:

clawdbot daemon install
clawdbot daemon start

If it still fails, check the logs:

clawdbot daemon logs

Issue 3: Pairing Code Expired

Symptom: You enter the pairing code but get a rejection.

Fix: Pairing codes have a short TTL. Send a new message in your messaging app to generate a fresh code, then approve it immediately.

Issue 4: High Token Consumption

Symptom: Your API bill is higher than expected after a few days.

Cause: OpenClaw carries full conversation context with each request. Long conversations with many turns accumulate tokens fast.

Fix:

  • Switch to a cheaper model for routine tasks (DeepSeek-V3 is excellent for this)
  • Keep your system prompt short and focused
  • Avoid enabling deep-thinking / reasoning models for simple Q&A
  • Disable skills you're not actively using

Issue 5: Bot Stops After Closing Terminal

Symptom: Everything works while your terminal is open, but the bot goes silent after you disconnect.

Fix: You forgot the daemon setup. Go back and run the daemon commands from the deployment section above. On templates from 2026.1.29 and later, the daemon should be pre-configured, but it's worth verifying with clawdbot daemon status.

Issue 6: WebUI Not Accessible

Symptom: You try to access the OpenClaw web interface via your server's public IP and get nothing.

Cause: WebUI is intentionally not exposed to the public internet by default — it's a security risk.

Fix: Use the Lighthouse console's Application Management panel instead. If you absolutely need WebUI access, set up an SSH tunnel or follow the secure access method in the deployment guide.

Keep Going

Five minutes to deploy, five common issues to know about. That's the real-world OpenClaw experience — fast to start, and manageable to maintain once you know the gotchas.

Ready to try it yourself? Head to the Tencent Cloud Lighthouse Special Offer:

  1. Visit the page for the latest OpenClaw instance deals.
  2. Choose the OpenClaw (Clawdbot) template under AI Agent.
  3. Deploy with "Buy Now" and time yourself — I bet you'll beat my 4:37.

Happy deploying.