You jest, but agents are of course already useful and fairly formal primitives. Distinct from actors, agents can have things like goals/strategies. There's a whole body of research on multi-agent systems that already exists and is even implemented in some model-checkers. It's surprising how little interest that creates in most LLM / AI / ML enthusiasts, who don't seem that motivated to use the prior art to propose / study / implement topologies and interaction protocols for the new wave of "agentic".
In the MAS course, we used GOAL, which was a system built on top of Prolog. Agents had Goals, Perceptions, Beliefs, and Actions. The whole thing was deterministic. (Network lag aside ;)
The actual project was that we programmed teams of bots for a Capture The Flag tournament in Unreal Tournament 3.
So it was the most fun possible way to learn the coolest possible thing.
The next year they threw out the whole curriculum and replaced it with Machine Learning.
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The agentic stuff seems to be gradually reinventing a similar setup from first principles, especially as people want to actually use this stuff in serious ways, and we lean more in the direction of determinism.
The main missing feature in LLM land is reliability. (Well, that and cost and speed. Of course, "just have it be code" gives you all three for free ;)