🍲 Sim-mer Down: Why AI's Perfect Simulations Might Be Missing the Point

🚀 What's News: From Roblox to Replicants

This month at Novela Marketing Simulations, we’ve seen a number of developments in our world:

Roblox can now build entire 3D worlds with a flick of generative AI magic. No more meticulous designing—just tell the AI what you want, and it appears.
Minecraft has gone all AI, generating real-time environments that change instantly based on user input. Drop a block of dirt, turn around, and suddenly it’s a medieval castle.
Stanford and DeepMind eggheads have taken it even further: give them two hours, and they can create an AI replica of your personality. (It’d probably take it two minutes to crack mine.)

If we put these advances together, we can start to imagine simulations in which we can perfectly model both people and environments.

But beyond these flashy stories, what really caught my attention this month is a new book called “Playing With Reality: How Games Shape Our World” by Kelly Clancy.

It’s an excellent read that gets the coveted Context Window “Thumbs Up” 👍, and it contains some lessons we could do with heeding before we start building brand new, simulated worlds.

One such lesson takes us back hundreds of years to a magical land called Prussia.

Kriegsspiel and AI: Learning Through the Fog

"Games are the closest representation of human life” - Leibniz

Back in the 1800s, a group of Prussian military officers gathered around a table to play Kriegsspiel—a simulation that was revolutionary for its time. The whole point of Kriegsspiel (it just means “war game” in German) wasn’t to recreate reality perfectly but to create an environment where players could think, adapt, and strategise under uncertainty.

Players gather round a table with a big map and sets of coloured blocks on the table top. Each team is given command of an imaginary army and they take turns to make decisions, moving across the map as they go.

In 1824, in a Berlin residence temporarily cleared of cats (so they wouldn’t knock the game pieces all over the place), officers didn’t just “play” Kriegsspiel—they debated strategies, questioned assumptions, and honed new ways of thinking. For weeks. Yes, a game could go on for weeks at a time.

The game’s influence grew slowly but profoundly, eventually attracting the attention of the Russian Grand Duke, who summoned its creator to St. Petersburg for a whole summer of training. Clearly, this was more than just a game—it was a tool to shape thinking. The game was still in common use through World War II and military teams use it to this day, although it is no longer their chief technological aid.

The genius of Kriegsspiel was its use of the "fog of war": players didn’t have all the information. The umpires filtered what players knew, reflecting the imperfect information of real battlefields.

These weren't technical limitations - they were conscious design choices.

Why? Because the game's architects understood something significant: sometimes, not having all the answers helps you find better questions.

The fog of war wasn't there to make the game harder - it was there to make the thinking clearer.

🧠 The Power of Purposeful Design

Fast forward to today's landscape. We’ll use marketing as our example.

Consider Google’s Performance Max campaigns. Google's AI promises to optimise everything - targeting, bidding, creative assets. But the marketers getting the best results aren't those who blindly trust the algorithm. They're the ones who use its limitations to develop crucial skills:

Strategic Diagnosis: Learning to spot patterns in the AI's successes and failures, developing frameworks for understanding when to trust it and when to override it
Resource Intelligence: Using the AI's targeting choices not as final answers but as prompts for deeper audience investigation
Risk Navigation: Building workflows that combine AI's efficiency with human judgment to gain a competitive advantage

At Novela, we're seeing this pattern across all our training simulations. Whether it's managing a crisis, allocating marketing budgets, or launching new products, the best learning happens not when we create “perfect” simulations, but when we design the right limitations.

We're not just developing new tools - we're developing new ways of thinking:

Instead of asking "What would the AI do?" we learn to ask "What is the AI missing?"
Instead of seeking perfect data, we get better at working with uncertainty
Instead of just automating decisions, we learn to make better ones

The Next Wave of Simulation

The future of simulation isn't just about better graphics or more accurate models. Here's what we're starting to see emerge:

Adaptive Learning Environments: AI that adjusts scenarios based on how you handle uncertainty.
New Forms of Feedback: Instead of just “right” or “wrong,” feedback that helps learners analyse their own decision-making.
Collaborative Challenges: Multi-player simulations with incomplete information, reflecting the complexity of real-world collaboration.
Ethical Dimensions: Scenarios that include ethical dilemmas, forcing learners to think critically about AI’s role and limitations.

Final Thought

It’s true that we're living in an age of unprecedented simulation capabilities. We can model personalities, generate worlds, and optimise complex systems automatically. But the most powerful simulations won't be the ones that replicate reality perfectly - they'll be the ones that are designed to help us think better.

Yet there is a slightly false promise today that AI will illuminate any battlefield, which can lull us into dulling our senses.

Just as those Prussian officers learned warfare better through carefully designed limitations than they would have through perfect battlefield replicas, today's learners might find their best insights not in flawless AI simulations, but in the thoughtful gaps we leave for human judgment to fill.