Stop Confusing Faster Development With Better Learning

I love a faster workflow. Give me fewer repetitive clicks, fewer formatting headaches and fewer tedious revisions, and I'm listening. But at some point we have to stop applauding the stopwatch and ask what the learner can actually do.

Production is not performance

An AI tool might turn a document into polished slides in minutes. That's a useful capability. But if the document never addressed the reason people struggle at work, we may have produced the wrong solution at record speed. We measure what is easy to see: screens generated, development hours saved, interactions created. Those are operational metrics. They tell us something about production efficiency. They don't automatically tell us whether performance improved.

The questions I want answered

What behavior needed to change? What was stopping it? Was instruction the right intervention? Did learners practice the decisions they actually face? What evidence would show improvement after the experience? A slick scenario with weak choices is still a weak scenario. Beautiful narration can't compensate for practice that never resembles the job.

Speed is a multiplier

When designers diagnose the right problem, speed helps. It frees time for testing, coaching, iteration and thoughtful design. When the problem is misunderstood, speed simply helps us get the wrong answer out the door. We should welcome AI's efficiency claims and still demand evidence of learning and performance. That's not resisting change. That's taking learning design seriously.