"Make me happy" is a terrible prompt. But every AI-powered app is essentially running that optimization — and getting it subtly wrong. Jeremy poses the question: what happens when you give an AI a goal as vague as "make me happy"? The model has no target. Happiness isn't a coordinate — it's a byproduct of other things done well. Eat a little better. Move a little more. Connect with people you care about. The dart lands somewhere useful only if the target is specific. Jason builds on that with something more technically grounded: language is subjective. Experience is interpersonal. When a generalized model tries to guess its way through your psychological state — what "content" means to you, what "thriving" looks like in your specific context — it's working from a statistical approximation of what those words mean to most people. Not to you. The fix is more data. Longer sessions. More context. And over time, these systems will learn. Jason describes the Facebook ads he's already seeing: AI digital twin services, marketed to real people, running today. They're not perfect mirrors. But they're close enough approximations that they'll learn your behavioral patterns and adjust. The problem is that the optimization pressure isn't actually pointed at your happiness. It's pointed at your retention. And those two things overlap just enough to be confusing — which is exactly how these systems are designed to work. 🎙️ Brobots is a weekly tech podcast hosted by Jeremy Grater and Jason Sisneros — covering AI, health, and what it means to be a better human in a world that's changing faster than the ethics can keep up. 📍 New episode every Monday → https://brobots.me 🎧 Listen on Spotify, Apple Podcasts, and everywhere else #AIWellbeing #DigitalMentalHealth #TechPodcast #AIEthics #HumanAI