7 Days with a 24/7 AI Agent

The promise of a 24/7 AI agent is that it makes you more productive. After a week of living with one, my experience is different: you end up getting sucked into a lot more things than before. His name is Spock (a friend asked why not Data, but Spock is flesh and blood). He runs OpenClaw on a dedicated Mac Mini, connected to my knowledge base, calendar, and task system. Always on. I message him from Telegram, and he responds with context-aware answers drawn from years of my notes. Here's what I've learned: The security architecture is the real work. Two macOS accounts, firewall layering, API key compartmentalization. Spock is like a new employee with limited admin rights. You don't hand over the keys on day one. "Always-on" has real costs. Disk encryption means manual intervention after restarts. Remote access means another attack surface. Token costs: month one was $100, month two doubled to $200. And I'm already sweating weekly session limits three days into the week. It sent a calendar invite to someone without asking. I shared an email about a meeting and asked how to handle scheduling. Instead of suggesting, it created the invite and sent it. From its own calendar. Instructions matter. "Suggest" and "do" should be very different words to an autonomous agent. But it works. Within 12 hours I went from "how would I use this" to "what else can I give it." It manages my tasks, processes meeting notes, curates my reading list. Sometimes I question if the agent is working for me or I'm working for the agent. The technology is ready. But "works" and "production-ready" are different things. Every lesson, security, costs, boundaries, is a governance question that enterprises will face at scale. Better to learn them on a Mac Mini first.