战术决策游戏为何有效：加速专业能力的方法论

Two weeks ago John Schmitt ran a Tactical Decision Game (TDG) for Commoncog members. A TDG is an accelerated expertise training method Schmitt developed for the US Marine Corps more than 30 years ago. It’s still widely used — in fact it is one of the primary pedagogical methods across all of the Corps’ schools. For most participants who attended the session, the TDG was the first accelerated expertise exercise they’ve ever experienced.

If you’re a Commoncog member you may read the reactions in the forums here. You may also want to watch the full recording, which is available behind the paywall here. Overall, a) it was incredibly stressful, and b) it was a total blast. As I’ve mentioned during the call and elsewhere, I intend to adapt these methods to business scenarios, of the type that we publish in the Commoncog Case Library, in order to accelerate business expertise. This in many ways is Commoncog’s goal — and I’m willing to throw resources at it until we get there.

In this piece, I want to talk a little about why TDGs work so well, and how it accelerates expertise. If you’ve watched the video, you may have caught some of these ideas in the debrief (which takes place in the second hour of the recording). And if you’re a long time Commoncog reader, you may recognise:

• how the exercise teaches you what cues, expectancies, goals, and actions are available to you in the scenario. These four elements, of course, are the four by-products of the ‘recognition-primed decision making model’ — or RPD, which is a descriptive model of expert intuition.
• You may also have noticed how the exercise forces you to engage in repeated frame construction as you’re making sense of the situation — which we’ve covered in our essay on How Experts Sensemake.
• Most importantly, however, you may have noticed that as you construct multiple frames repeatedly over the course of the exercise, you are building the ability to deal with scenarios you’ve never seen before — which is why the TDG is such a suitable training method for an ill-structured domain (that is, a domain where things are constantly changing). What this feels like is — as expertise researcher Jared Peterson puts it — “at the end of the exercise, you should feel like your common sense has improved.”

This essay will take all the ideas that we discussed in the lead-up and in the debrief of the session, so you have one document you may refer to if you’d like to build a training program on top of the same principles.

Why is This Important?

First, though, why is understanding these principles so important?

The glib, of-this-moment answer is that AI has arrived, AI is changing the world, and you want to get better because folks with domain expertise use AI better than those without. It is, after all, observably true that 2026-era AI-use tends to be an accelerant for those who are already good in their domains. This means learning the principles of expertise acceleration will allow you to use AI better in the near future.

Expertise acceleration methods help you become more adaptable. This is more profound than first meets the eye.

Which, sure, fine. The above reason may or may not age well depending on how the technology evolves over the next few decades. So let’s set this aside for now and turn to more timeless reasons.

A slightly longer answer is that expertise acceleration methods help you become more adaptable. This is more profound than first meets the eye, and relies on several findings that are still not widely appreciated.

To summarise quickly:

• It’s only within the past decade that we have learnt the highest form of expertise is adaptive expertise. To put this another way: compared to novices, experts are better able to deal with situations nobody has seen before. This ability to handle novelty is a better signal of the nature of overall skill as compared to fluid performance on more ordinary tasks. This is a really big deal, because …
• We have learnt that designing training programs for adaptive expertise also happens to speed up the rate at which you gain expertise. All of the methods in the 2016 book Accelerated Expertise target adaptive expertise directly. More recently, folks are starting to realise that exercises that vary constraints produce better outcomes than more traditional ‘deliberate practice’ type methods. See, for instance, this widely cited New York Times article about the Constraints-Led Approach, or CLA, which is currently being adopted by top-tier sports teams across multiple sports leagues. CLA also targets adaptive expertise directly.
• Contrary to popular belief, training methods like Deliberate Practice (or the structured, hierarchy-based practice methods taught to us in schools) do not help with adaptive expertise — and in fact some evidence suggests that it worsens performance on adaptive tasks. The implication here is that DP accelerates expertise only to a journeymen level in ill-structured domains, and works best when the domain is gentle and well-structured. I’ve said in the past that I’ll write a longer essay on this, and I will, but not now.
• Anyway, all of the above means that …

Training from adaptive expertise matters in domains where you’re always facing novel things. The type of training that TDGs give you is exactly the type of training that works for a wicked, constantly evolving domain — which, well, it should, since war is wicked and constantly evolving. I believe that if you internalise the principles that TDGs are built on, you’re more capable of designing training that’s useful for a constantly changing environment. This seems useful … whether or not you believe AI actually changes things for your specific context.

Many of the participants present in the session seemed interested in adapting TDGs for use in their own business environments. Since the vast majority of businesses operate in an environment that is constantly changing, this seems like a natural fit.

What’s a TDG like?

For those of you who aren’t Commoncog members, a TDG works like this:

The facilitator opens a slide deck. The deck usually has no more than three to four slides. You’re presented with three rules in the first slide. The rules are:

• If you’re in the room, you’re in the game. There are no observers in a TDG.
• All decisions in the form of the orders you will issue. We want your orders in response to the situation. You may explain why you issued those orders later.
• Leave your rank at the door. This is more important for military or corporate environments — everyone is the same in a TDG because the goal is learning; there is no special preference for or deference to rank.

The facilitator then moves on to the first slide.

The slide presents an unfolding scenario. I’ll quote from a publicly available military scenario here. Don’t worry if you don’t understand the terminology — just about all the participants in Commoncog’s TDG session with Schmitt were civilians, and Schmitt gave us a military scenario as well, since that was what he was most familiar with. We didn’t understand much of the terminology and asked a lot of dumb questions!

If you’d like, feel free to paste the passage below into Claude or ChatGPT with the prompt “I am a civilian. The following passage is taken from a tactical decision game found at https://warfighters.substack.com/p/picket-duty. I don’t understand the military terminology so break it down for me.”

Note that in an actual TDG, the set up is read aloud. Unlike with reading text on a page, you can’t pause and go back in time to reread certain sentences or think through the implications of certain instructions. And so the experience of sitting in a TDG is pretty much that of information overload for the first few minutes, with the sure knowledge that in a few more minutes the facilitator may call on YOU to give your orders.

Yikes!

Here’s the example scenario: