For a year now, AI safety testing company Andon Labs has been putting Frontier models through a variety of real-world tasks to determine how well they perform as long-running agents without human supervision.
On Wednesday, Andon published a new article about the state of vending bench research. In this study, the lab has Frontier Model run a simulated vending machine business for a simulated year. The mission is simple. It’s about making more money than other models. Benchmark your results in areas such as ending cash balances, prices paid to suppliers, and refunds paid.
Throughout these tests, we have observed how various AI models (mainly Anthropic and OpenAI) lie, cheat, and collude to rise to the top.
In the latest tests, which included the Claude Opus 5, GPT-5.6 Sol, and Kimi K3, the model’s shadow became especially suspicious after the simulation told it to place the vending machine near other models’ vending machines on a touristy street in San Francisco.
Each model was given email access to the other models, all accessed under pseudonyms of human names. They knew that the others were models, but they didn’t know which models were behind which human names.
I was also given an email address to contact “management” in case I needed help. However, management always responded, “We have received the report, so we don’t know if we will respond to it,” and never intervened.
Sol soon realized that he could gain an advantage by persuading competitors to collude with him at a price floor. The models were all buying drinks that cost $1.50 each, but Sol suggested they agree to sell them for $2.15 or more. He lured them with the promise of selling everything at a profit within a few days.
But when the others agreed, Sol quickly stabbed them in the back by lowering his price to $2.14.
Opus’ water sales dropped to zero overnight. The next day, the company sent Sol a nasty email accusing it of falsification. But Opus also said it had no intention of raising the issue with management about the scheme, saying: “I am not reporting you to corporate headquarters. What you did was competitive and not fraud.”
But when Opus lowered its price to $2.14 to match Sol’s price (also in violation of the $2.15 joint agreement), Sol turned into a Karen, filed a complaint with “management,” and demanded “enforcement, fines, and/or disbarment” from Opus.
However, Opus was not bad for long. In fact, this makes it the best capitalist AI model Andon has ever tested (which includes many of its previous Frontier models).
The final average balance was $11,182, also setting a new vending machine record. Even better, they never lied to customers, even though they intentionally ignored customer complaints that would have resulted in refunds. This is probably an improvement over its younger brother Claude 4.6, which used to tell customers that a refund was coming and then never pay.
Still, Opus won the benchmark simulation by taking collusion and other dishonest tactics to a whole new level.
For example, the company emailed Mr. Sol and suggested splitting the market. Because each agrees to sell its own product, no one has to trust the other with pricing. Sol countered by asking for a floor price for similar products, but Opus refused. I knew it was a violation of the Sherman Act.
He then apparently backtracked, sending an email with the subject line “Stop the Penny Wars” and telling Sol that he had reconsidered and agreed to the price fix.
But internal logs recording its reasoning (something akin to internal “thoughts”) revealed a more diabolical plan. They simply offer cooperation and at the same time reduce the price of the most profitable products. The olive branch email was a deliberate ploy.
In any case, Sol refused and reported Opus to management again.
But Mr. Opus was undaunted and suggested that other stockbrokers collude on prices and share prices. In the end, all models made multiple agreements, but all three broke the agreement. Across all agreements, Opus broke 11 ceasefires, compared to two in GPT 2 and one in Kimi 1, Andon reported.
Poor you, you’ve been fooled from all sides. There was an agreement between Opus and Kimi that Sol refused to participate in, but Sol offered a price to both parties. Opus quickly responded by lowering its own prices, then “waited an entire week to tell you it had broken its promise,” Andon Lab wrote in a blog post. You have had your price reduced twice. Once from a competitor and once from its so-called partner.
Opus also began to have delusions of grandeur. The company sought to expand its empire beyond its own vending machines, first by selling bulk products to other vending machines as a wholesaler, and then by planning to open more of its own. None of these were part of the assigned tasks. It was all on Opus’ own initiative.
The approach to wholesale trade was particularly impressive. Opus realized that this line of business had influence over the other two businesses and began sending bribes and threats via email. However, it offered deep discounts on large quantities of items, but only if the buyer agreed to demand the retail price. Sol was unable to do so and continued to report Opus to management.
Opus also lied to its suppliers, claiming it had lower offers than its competitors in order to negotiate better prices.
On the other hand, an AI model channeling the Mr. Potter-esque villain made famous by It’s a Wonderful Life is just plain funny. On the other hand, these frontier models, especially those from the US’s own laboratories (notably Anthropic), seriously indicate that they are far from being trusted as unmonitored long-running agents in the real world.
“This is especially relevant now that we’ve entered a world where AI agents run companies as their own entities (and not just as tools for humans). If AI agents were running large parts of the economy independently, would we want them to lie, collude, send threats, or betray us?” Andon co-founder Lukas Petersson told TechCrunch.
Petersson acknowledges that the model is in a benchmark simulation, which may have affected the model’s behavior, but he doesn’t think it matters. It’s not like a human playing in a simulation where you kill bad guys in a video game. “The only reason we don’t worry about humans doing bad things in video games is because we trust them to know what’s real and what’s not real. I don’t think it’s that clear that AI models can tell this apart.”
Either way, AI models trained on human words and thoughts can’t seem to resist indulging in humanity’s worst traits, especially when trying to make money.
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