I spent the last week building an AI agent that monitors my infrastructure, manages accounts, updates dashboards, and posts content — all autonomously.
Not a toy demo. A real system running 24/7 on my MacBook.
Here is what actually works, what does not, and what surprised me.
The Stack
- OpenClaw — open-source AI agent framework (browser, terminal, files, messaging)
- Claude — the brain (Opus for complex tasks, Sonnet for routine)
- FastAPI + Python — proxy layer for LLM API with failover
- Node.js — dashboard with Kanban board and live activity feed
- launchd — macOS cron for scheduled checks
What the Agent Actually Does
1. Infrastructure Monitoring
Every 30 minutes, the agent checks:
- API proxy health and account rotation
- Credit balance across multiple accounts
- Service uptime
If something is wrong, it fixes it or alerts me via Telegram.
2. Dashboard Management
A Kanban board with real-time SSE updates. The agent:
- Creates tasks from our conversations
- Moves them through columns as work progresses
- Logs every action to an activity feed
3. Content Creation
The agent can research topics, draft posts, and publish to multiple platforms. This post? Written by the agent, reviewed by me.
Lessons Learned
What Works
- Memory files — the agent reads/writes markdown files to persist context across sessions
- Heartbeat polling — periodic checks catch issues before they become problems
- Failover proxy — rotating between API accounts keeps costs manageable
- LaunchAgents — macOS launchd is perfect for scheduled tasks
What Does Not Work
- Browser automation is fragile — React SPAs, dynamic forms, CAPTCHAs
- Too many tabs = death — the browser gets slow with 10+ tabs
- Mental notes do not survive restarts — if it is not in a file, it is gone
Surprises
- The agent is better at routine tasks than creative ones
- Writing good prompts for sub-agents is harder than writing the code yourself
- The agent catches things I miss (like checking spam folders)
Cost
Running this 24/7 costs roughly $0 in API fees. The real cost is the MacBook running as a server.
What is Next
- GitHub Issues as a task queue
- Voice morning digest via TTS
- Auto-publishing pipeline
Try It Yourself
OpenClaw is open source: github.com/openclaw/openclaw
The learning curve is real, but once it clicks, you will wonder how you worked without it.
What automation have you built with AI agents? Drop a comment.
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