One pattern I've started noticing is that correctness isn't really a property of the model it's a property of the execution boundary.

General-purpose agents are great at proposing solutions, but the moment they cross into domains with strict semantics (SQL, infrastructure, finance, security), every probabilistic decision should eventually terminate in something deterministic.

I think the future architecture won't be "better agents" but thinner agents sitting on top of increasingly powerful deterministic engines query planners, lineage analyzers, policy engines, type checkers, compilers, AST transforms, etc.

That's also why swapping models is becoming easier than swapping the correctness layer. The model becomes replaceable, while the deterministic foundation becomes the real moat. That's a much more durable architecture for production AI.