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Everywhere you look, people are talking about AI agents like they’re just a prompt away from replacing entire departments. The dream is seductive: Autonomous systems that can handle anything you throw at them, no guardrails, no constraints, just give them your AWS credentials and they’ll solve all your problems. But the reality is that’s just not how the world works, especially not in the enterprise, where reliability isn’t optional.
Even if an agent is 99% accurate, that’s not always good enough. If it’s optimizing food delivery routes, that means one out of every hundred orders ends up at the wrong address. In a business context, that kind of failure rate isn’t acceptable. It’s expensive, risky and hard to explain to a customer or regulator.
In real-world environments like finance, healthcare and operations, the AI systems that actually deliver value don’t look anything like these frontier fantasies. They aren’t improvising in the open world; they’re solving well-defined problems with clear inputs and predictable outcomes.
If we keep chasing open-world problems with half-ready technology, we’ll burn time, money and trust. But if we focus on the problems right in front of us, the ones with clear ROI and clear boundaries, we can make AI work today.
This article is about cutting through the hype and building AI agents that actually ship, run and help.
The problem with the open world hype
The tech industry loves a moonshot (and for the record, I do too). Right now, the moonshot is open-world AI — agents that can handle anything, adapt to new situations, learn on the fly and operate with incomplete or ambiguous information. It’s the dream of general intelligence: Systems that can not only reason, but improvise.
What makes a problem “open world”?
Open-world problems are defined by what we don’t know.
More formally, drawing from research defining these complex environments, a fully open world is characterized by two core properties:
Time and space are unbounded: An agent’s past experiences may not apply to new, unseen scenarios.
Tasks are unbounde …