You know that viral TikTok guy Larry — the one who set up an AI agent to run his social media, respond to emails, and basically live his digital life while he sleeps? I watched that and thought: I could do something like that, but for real work.
So I did. Here's my honest experience running an AI agent 24/7 on a Mac Mini.
The Setup
I'm using OpenClaw as the agent runtime. It's basically a gateway that lets an AI agent (Claude, in my case) interact with my machine — read files, run commands, browse the web, send messages. Think of it as giving the AI a body on your computer.
The Mac Mini sits on my desk, always on, always connected. The agent runs through OpenClaw's gateway, and I use cron jobs to trigger periodic tasks.
What It Actually Does
Here's what my agent handles autonomously:
- Checks my email a few times a day and flags anything urgent
- Monitors my calendar and sends me reminders before meetings
- Publishes blog posts across multiple platforms (yes, including this one 👀)
- Runs background research — web searches, content summaries
- Maintains its own memory — it writes daily notes and reviews them periodically
The cron setup is dead simple:
# Heartbeat every 30 min during waking hours
*/30 8-23 * * * openclaw cron run heartbeat
# Daily summary at 9 AM
0 9 * * * openclaw cron run daily-briefing
What Surprised Me
It's more useful than I expected. The agent catches things I'd miss — an email buried in my inbox, a calendar conflict I didn't notice. It's like having a very attentive (if slightly literal) assistant.
It's not magic. Unlike Larry's TikTok-perfect setup, real agent automation is messy. Sessions time out. APIs change. The agent sometimes misunderstands context. You spend the first week debugging more than benefiting.
Memory is the killer feature. The agent writes notes about what happened each day. When I start a new session, it reads yesterday's notes and picks up where it left off. This continuity is what makes it feel like a real assistant rather than a stateless chatbot.
The Honest Downsides
- Cost: Running Claude Opus for agent tasks adds up. I'm selective about what gets automated.
- Trust: I'm still not comfortable letting it send emails without my approval. External actions need guardrails.
- Maintenance: It's not "set and forget." More like "set and check on it regularly."
Is It Worth It?
For me, yes — but not for the reasons I initially thought. I expected it to save me hours of work. Instead, it saves me minutes here and there, but the real value is in things I'd never bother doing manually: checking my inbox at 2 PM, reviewing my calendar before bed, organizing notes from the day.
The compound effect of those small automations is surprisingly significant.
🔧 If you're thinking about running your own agent setup, I put together a free $0 Developer Playbook with the exact configs and patterns I use.
Your Turn
I'm curious about your experience:
- Are you running any AI agents autonomously? What's your setup?
- What tasks would you trust an AI to handle unsupervised?
- Where do you draw the line between automation and oversight?
Would love to hear what's working (or not working) for others. Drop your setup in the comments! 👇
📚 More in This Series
If you found this useful, check out the follow-up posts where I go deeper:
- How I Built a Self-Healing Automation System That Runs 24/7 Without Me — Retry loops, token refresh, circuit breakers
- I Run 6 Businesses With Cron Jobs and Sub-Agents — Here's the Architecture — Registry + division files + 8-minute hard cap
If this helped you think about AI automation differently, drop a ❤️ — it helps other devs find it.
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