Why fluid thinking skills win over linear progression

My daughter once asked me, “Who’s more important — the author or the editor?”

I didn’t have a great answer then. I still don’t. But I’ve been thinking about that question a lot lately, especially after reading Michelle Kassorla’s piece “Inverted Bloom’s for the Age of AI” on her Substack, The Academic Platypus. Michelle and her colleague Eugenia Novokshanova have been wrestling with how AI has changed the way students engage with thinking: we’re seeing students create first now, and understanding comes later. It’s a thought-provoking piece, and I’d encourage you to read it.

But as I sat with it, I found myself thinking in a slightly different direction.

The conversation about Bloom’s and AI has been building for a couple of years. The argument goes something like this: students used to climb the pyramid. We focused on the linear progression of remember, understand, apply, analyze, evaluate, create. AI has flipped that. Students are creating first. They’ve skipped to the top. It’s caused all sorts of reactions.

But what if the problem isn’t the order? What if the problem is the pyramid itself?

Bloom’s was never meant to be a ladder. It was designed as a categorization system. Benjamin Bloom wasn’t designing a sequence where create sits at the peak waiting to be earned. He was describing types of thinking. Thinking types are meant to flow together, intersect, and loop back on each other depending on what the problem demands.

I designed this graphic as a visual to support my reflections. No pyramid. No pinnacle. No start and end point. Just six interconnected ways of thinking, moving in and out of each other throughout the process of learning, creating, and problem-solving. That’s what unlocked looks like. It’s not Bloom’s upside down. It’s Bloom’s without an order at all.

We’re the ones who turned it into a hierarchy. And we’ve been teaching it that way for seventy years. So, when students jump straight to creating with AI, teachers respond with panic, grieve the loss of skills, and even resist the innovation. That’s because in our mental model, they’ve skipped everything that matters. But what if they haven’t skipped anything? What if they’ve just used a different starting point?

Consider how we cook. We follow a recipe without necessarily understanding all of the ingredients. If we use a meal prep service, we don’t even plan the ingredients — we just cook. We learn by doing, by tasting, by adjusting. Understanding how the ingredients work together might come later, mid-process, or sometimes not at all, and the meal still turns out. We don’t require mastery of concepts before we’re allowed to start creating.

Why should learning be any different?

I speak to schools around the world about how to prepare students for an AI world. One of my talking points is motivation. How motivated would students be if they could create first, then pull apart what they made to understand it? What if some students started a project by creating a product, while others started by brainstorming?

I’m not a brain researcher. But I do wonder if part of our disengagement problem is that we’ve overstructured how learning is supposed to happen. All throughout life, we move in and out of these thinking skills interchangeably — we create, evaluate, apply, remember, analyze, understand — not in sequence, but as the moment calls for it. Is school the only place where we insist on a specific order?

I believe it’s possible the insistence to follow a linear progression of learning is rooted in fear. And now, all around us, we see students creating with AI and we want to restrict it, redirect it, bring them back to the “right” starting point. But if we let go of the sequence, we are giving students the freedom to think in a way that fits how real life happens. Some will start by creating. Some will start by asking questions. Some will jump straight to applying something they barely understand yet, and the understanding will catch up. Some will be the author — others will be the editor.

This isn’t about AI replacing an activity. It’s about reconsidering a structure that was never as fixed as we made it.

That feels like something worth being optimistic about.