Today my AI woke up the entire house. At 6 a.m. Let me back up and explain what I've been building. For the last few weeks, I've been building my own music system — an AI DJ that runs my whole house Sonos system. Not another algorithm feeding me the mainstream. This one knows my taste and plays from my library. It also does the thing streaming never does well for me: real discovery. It pulls out new-to-me songs and albums I'd never discover on my own, and finds new artists that actually sit in my lane instead of the algorithm’s. Or, if I want radio, I can play Sirius XM or TuneIn. It's genuinely changed how my family listens to music. Which is exactly why this morning stung. 6 a.m., I open it for something quiet. The TV Room speaker blasts on at full volume. Everyone's awake. Prior, I'd asked the AI for one simple thing: remember the music volume, so it never inherits the TV’s. It built the opposite of simple. It only remembered rooms I'd set by hand in the app, and because I hadn't set the volume in the TV Room last time I played, the one guaranteed to be loud was the one it didn't learn. Then it tried to identify the TV by reverse-engineering its audio signature, and admitted it couldn't verify that worked. I stopped it: "You know when THE APP is playing. If it’s the app, remember the volume. If not, don't.” Fixed in one line. The takeaway: everyone's racing to make AI more autonomous. But its failure mode isn't incompetence — it's confident overcomplication. It ships a clever, plausible, wrong answer with total conviction. So the moat in AI products isn't the model. It's the human who catches the overengineering and forces the obvious. Remove that human, and you don't get magic. You get a speaker blasting your kids awake at 6 a.m., very intelligently. BTW, I call the app Skáld, which is Icelandic for poet. 28 AI agents run my CPG brand. I'll help you build yours.

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