Hello!
Lately I've been circling the idea that turning tasks into reproducible agent outcomes is becoming a genuinely valuable skill. That's the thing worth getting good at: not just prompting an agent once, but defining work precisely enough that you get the same reliable result again and again. Why does this matter now? Because we've gone from a single agent finishing a coding task feeling like magic to orchestrating thousands of them across devices. I literally posted about "a thousand agents, in your pocket" this week... large scale agent coordination running across multiple machines, isolated workspaces, custom agents, steered by text, voice, or image. But coordination at that scale only works if the underlying work is reproducible. That's where things like agent roles come in: a coordinator breaks work into pieces, implementers write the code, verifiers check it against acceptance criteria. And intelligent handoffs let agents pass work forward carrying only what matters. None of that holds together if each run is a fresh roll of the dice. So the skill isn't babysitting one agent. It's writing specs clear enough that a task becomes an outcome you can trust, delegate, and repeat. Get that right, and a thousand agents in your pocket actually means something.
What’s your main takeaway in one word about designing AI products?
If I have to pick one word: humanize.
Our job hasn't changed even as the technology has gone wild. It's taking that empathetic perspective and rethinking what would actually make this work for a person: what do they need to know, what are they thinking, what are they feeling, and bending the technology to that instead of making people bend to it.
It's easy to get lost in technology for technology's sake, stacking feature upon feature until the tools become the focus instead of the thing people actually want to get done. So when I built Ask Luke, the whole point was AI for user experience's sake, not AI for AI's sake.
Humanize the technology. That's the work.