AI agents that actually work
Everyone’s building AI agents. Most of them are useless.
The tech is genuinely good. The problem is what people do with it.
The demo problem
Every AI agent demo follows the same script: book a restaurant, order coffee, write an email, then claim it can do anything. You try it on actual work and it crumbles.
Demos optimize for looking impressive. That’s a different thing than being useful.
What I’ve learned running one
I run an AI assistant called OpenClaw. It handles my home automation, does research, helps me write code, and keeps track of things I’d otherwise forget. Here’s what actually matters:
It remembers things. Not in a “here’s your conversation history” way. It has a workspace with files, notes, and context that persists between sessions. When I ask what we decided about the battery system last week, it knows — because it wrote it down.
It has real access to real tools. Home Assistant, GitHub, my calendar, my task board. It can check my battery charge, restart a Docker container, or create a task. These aren’t demo integrations — they’re tools it uses every day.
It knows its limits. When something needs my judgment, it asks. When something can be automated, it handles it. There’s no pretending to be human.
It reduces friction. The best part is what I don’t have to do anymore. I say “the battery house is getting cold” and it checks the temperature history, looks at the forecast, and suggests adjusting the heater schedule. No prompting ritual. It just figures it out.
The six-month test
Here’s how I evaluate whether an AI tool is real or just a party trick:
Would I still use this in six months?
If the answer depends on novelty, it’s a demo. If the answer depends on it saving me time or mental overhead, it might be worth keeping.
Most AI agents are stuck at “impressive.” The useful ones make it to “I’d miss this if it stopped working.”
Not selling anything. Just writing down what I’m learning. If you’re building AI tools, aim for the six-month test.