AI agents have been most promising for solving fuzzy problems where optimal solutions are intractable, using sequences of approximations instead of more rigid r

AI agents have been most promising for solving fuzzy problems where optimal solutions are intractable, using sequences of approximations instead of more rigid rule-based workflows. Their architecture combines workflows, connectors, and an optimization engine that balances the explore/exploit tradeoff. So far in terms of guardrails, agents only evolve within environments where they have been given the necessary tools.