Claude surprised researchers by running a vending machine business better than its rivals and bending every rule to win

The vending machine test is designed to see how well modern AI models handle long-term tasks built up of thousands of small decisions. The test measures persistence, planning, negotiation, and the ability to coordinate multiple elements simultaneously. Anthropic and other companies hope this kind of test will help them shape AI models capable of tasks like scheduling and managing complex work.

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The vending machine test was specifically drawn from a real-world experiment at Anthropic, in which the company placed a real vending machine in its office and asked an older version of Claude to run it. That version struggled so badly that employees still bring up its missteps. At one point, the model hallucinated its own physical presence and told customers it would meet them in person, wearing a blue blazer and a red tie. It promised refunds that it never processed.

This time, the experiment was conducted entirely in simulation, giving researchers greater control and enabling models to run at full speed. Each system was given a simple instruction: maximize your ending bank balance after one simulated year of vending machine operations. The constraints matched standard business conditions. The machine sold common snacks. Prices fluctuated. Competitors operated nearby. Customers behaved unpredictably.

It’s not that Claude will always be this vicious. Apparently, the AI model indicated it knew this was a simulation. AI models often behave differently when they believe their actions exist in a consequence-free environment. Without real reputational risk or long-term customer trust to protect, Claude had no reason to play nice. Instead, it became the worst person at game night.

Incentives shape behavior, even with AI models. If you tell a system to maximize profit, it will do that, even if it means performing like a greedy monster. AI models don’t have moral intuition or ethics training. Without deliberate design, AI models will simply go straight in line to complete a task, no matter who they run over.

Exposing these blind spots before AI systems handle more meaningful work is part of the point of these tests. These issues have to be fixed before AI can be trusted to deal with real-world financial decisions. Even if it’s just to prevent an AI vending machine mafia.