Engineering Learning Experiences

Everybody’s pitching AI like it’s magic. Describe the thing, let it generate, ship it. That gets you part of the way there. It’s a piece of the process, not the whole thing. Underneath all the new terms, I keep landing on the same pattern: discern decisions, record them, enforce them. This episode is the first one. Canvas or page, SVG or PNG. They looked like design questions, but they were technical ones too, and I only found them by building something and watching it run.

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Everyone who has built a branching scenario has hit the wall where one more path breaks multiple others. I tell the story of changing the mental mode I had. It meant going from thinking about writing paths and moving to making rules for actions to happen. Write the rules once, keep them fixed, and let each learner's choices make the experience different.

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A lot of ID textbook says decide what evidence you need before you build. I didn't, and it worked anyway. Why building fast let the events come out of the patterns, the edge cases that forced the real decision, and the rule I landed on: record the learner's action, never the consequences the system computes from it.

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I built a scenario-based course, got it to the finish line, and realized it was a fancy quiz. I tried to fix that with measurement and learned that data can't add nuance that isn't in the experience. This episode is what learning engineering is, why the feedback loop is so important, and why I'm designing building this loop to make a richer experience for the learner and admin.

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