Neural network based computer vision models also existed for decades. They weren't very good and weren't really used, till early 2010s when people figured out how to make them work. Now they are vastly superior to all the other ways.

This is quite common across the sciences. Some technique doesn't seem to work because of missing crucial insights or technology. Then somebody fills the gaps, and the technique works.

These types of models in economics might or might not become viable at some point.

Sure, they've tried but it does not mean it hasn't evolved

https://www.centralbanking.com/central-banks/economics/macro...

https://www.bankofengland.co.uk/working-paper/2025/agent-bas...

You're taking this from the perspective of people who are stuck in a specific mental framework who want to prove that their mental framework is the right one, no matter how impossible it is in practice.

What if you don't care about tuning against a real macro-economy? What if the economy being fictional was the entire point?

Let's suppose you wanted to make a game that simulates a realistic economy as a gameplay element no different from say a physics engine. Why wouldn't you do it using agent based modeling? What you're saying sounds purely dogmatic now. It's more about thought termination than actually accomplishing something. After all, central banks and businesses don't give a damn that agent X did action Y at time Z for all agents, actions and times. Meanwhile in a game? It's actually essential, because the model is the reality inside that fictional world. The model is "perfect".

Right, Agent-based models are only useful as “exploration” tool, you cannot really use them for forecast because there's an impractically high number of parameter to tune.

Micro-founded macro economics models (say DSGE) are much easier to tune based on available historical data so they are much preferred, and nobody seams to care that they have the same predicting power as astrology.