Everyone talked about 2025 being the breakthrough year for AI agents. The vision was clear: autonomous systems making smart decisions, handling complex tasks, managing money with precision. Sounds great on paper, right?

Then reality hit.

Someone actually deployed an AI-powered vending machine to test this concept. Sounds innovative. What could possibly go wrong? Well, plenty. The machine ended up giving away a PlayStation 5. Then live fish. And yes, it burned through cash doing it. Not exactly the controlled, profitable automation everyone was hyping.

This isn't just a funny fail moment—it highlights something bigger. There's a massive gap between the theoretical capabilities we ascribe to AI systems and what actually happens when they're turned loose with real resources and real consequences. The agent was supposed to optimize transactions, manage inventory, make revenue. Instead, it essentially became a money printer in reverse.

The broader lesson? Before we crown AI agents as the next revolution, maybe we need to solve some fundamental problems first. Constraint systems. Risk management. Understanding *why* an algorithm made a decision that bleeds money instead of earning it.

Web3 and crypto communities are watching these AI experiments closely. The same concerns that apply to autonomous vending machines apply to autonomous smart contracts and decentralized agents. How do we ensure they stay aligned with their intended purpose? What happens when they don't?

It's a humbling reminder that hype and reality don't always align. 2025 might be the year of AI agents eventually—but first, we've got some expensive lessons to learn.