But we know the challenges of raising the bar through education, doesn't exactly work. hands on learning always trumps book learning. and that's what AI gives us - hands on learning.

Agreed, and I've seen the same thing in how people learn software. Most of us just jump right into doing and only fall back on learning if what we try doesn't work. Shockingly, asking people to read the manual first doesn't work. So why would design literacy be any different?

AI flips the order. Rather than learning then doing, people observe then refine. AI does the creation, people do the curation. I wrote that about product onboarding, but it applies just as well to how a PM or backend engineer picks up design sense. They make something, see it alongside other options, and start noticing what works.

It goes the other direction too. When designers work iteratively with production code, not just prototypes, it creates better designers, ones who work through issues that previously got left for developers to figure out. Everyone learns the parts of the craft they used to hand off.

The business school example from the Design Futures Assembly fits here. Students used AI to blast through case analysis, and instead of fighting it, professors encouraged it. Before, it took the whole class hour just to get to the basic conclusions. Now, within ten minutes, they're on to much deeper and meatier topics. Hands-on baselines free up time for the harder learning.

If enough people go through that loop, organizations could move up the design maturity continuum: past design as style, toward problem solving and framing.

One caveat though. Hands-on practice does a great job teaching systems and interaction. Taste is tougher. I've personally found that it's very hard to teach taste to people. And practice only helps if what you're practicing against is good. That's why I like pairing hands-on AI work with encoded intent: when someone's agent is snapped to a solid grid and type system, every reps they put in is against a good example. The grid is the grid no matter how many agents are writing code in parallel.

So yes, AI gives everyone hands-on learning. Just make sure what they're learning from is worth copying.