The agent that has nothing to do

I’ve spent the last few months “playing” with agent - yes, I fell for the OpenClaw hype too. Reading documentation, running experiments, trying to wire things together. The question I was asking was: which of these gets me closer to the daemon?

I eventually realized I was asking the wrong question. But getting there required enough failed experiments to understand why.

The appeal of agents

The agent pitch is compelling on paper. You give a system tools - the ability to search, read, write, call APIs, interact with other services - and it uses them autonomously to complete complex tasks. Add enough intelligence, connect enough services, and you theoretically get something that can act on your behalf across your digital life.

The wrong reason to go local

When you ask the right question, the answer isn’t what you expected.

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I am running both. A local model on my own hardware - small, private, entirely under my control - alongside using Claude (the app or the API) that have become part of how I actually think through problems. And at some point I stopped and asked myself: what am I actually trying to achieve with each of these?

The daemon moment has arrived (but it's being built backwards)

There’s a simple query that’s been making the rounds among tech journalists and AI enthusiasts: “Find the first email with my wife.” It should be trivial, for example with Google’s Gemini having access to your entire Gmail history. The infrastructure for personal AI is being built by every major lab, with billions in investment and aggressive timelines.

Yet the query fails. Consistently, instructively.

When I started writing about personal AI six months ago, the daemon vision felt theoretical - a thought experiment about what AI could become if we built it around continuous relationship rather than stateless service. Now, suddenly, it’s not theoretical at all. The major labs are racing toward exactly what I described: AI that knows you, learns from your data, becomes personalized to your context and needs.