Episode two. Three stages of giving an AI agent real independence.
First, a counterintuitive discovery: more instructions made my agent worse. I went from 471 lines of rules down to 61 by replacing abstract adjectives with concrete behaviors. “Principle beats rule” turned out to be the single biggest performance unlock.
Then, teaching it to learn. Error logging, structured lessons, and an identity layer that knows who I am. But MIT research shows personalized profiles increase sycophancy by 33-45%. The AI starts telling you what you want to hear instead of catching your mistakes. True autonomy requires friction, not agreement.
Finally, giving it a physical home. Migrating to a dedicated Mac Mini broke everything: no display meant no UI automation (solved with a virtual 5K screen hack), hundreds of hard-coded paths pointed to folders that didn’t exist, and the agent burned through API credits stuck in silent error loops. The fix: full root authority inside a contained blast radius. If the AI deletes the entire drive, it literally doesn’t matter.
The payoff: a self-improving agent running 24/7 on its own machine, with its own iCloud account, reachable via iMessage like a coworker.
Posts discussed in this episode:
- I Built a Personal AI Agent Called Wiz (https://thoughts.jock.pl/p/how-i-structure-claude-md-after-1000-sessions)
- My AI Agent Learns From Its Own Mistakes. Here’s the Architecture (https://thoughts.jock.pl/p/wiz-ai-agent-self-improvement-architecture)
- I Gave My AI Agent Its Own Computer. Here’s Every Lesson From 72 Hours of Migration (https://thoughts.jock.pl/p/mac-mini-ai-agent-migration-headless-2026)
