강력한 AI 모델이 더 좋은 거래를 성사시킨다

Anthropic says stronger AI models cut better deals, and the losers don't even notice Matthias Bastian View the LinkedIn Profile of Matthias Bastian Apr 25, 2026 Nano Banana Pro prompted by THE DECODER Key Points In a week-long experiment called "Project Deal," Anthropic had AI agents from the Claude model family independently negotiate and trade real goods on behalf of employees. The more capable Claude Opus model consistently secured better prices and closed more deals on average than the smaller Claude Haiku model, while aggressive negotiation instructions made no statistically significant difference in outcomes. Despite receiving objectively worse deals, users of the weaker Haiku model rated the fairness of their transactions just as highly as Opus users—a perception gap that Anthropic flags as a form of invisible inequality in AI-assisted decision-making. Ask about this article… Search In a week-long experiment, Anthropic let Claude agents buy and sell goods for employees. The result: stronger models negotiated better prices. The catch: the people stuck with weaker agents had no idea they were losing out. In December 2025, Anthropic ran a one-week classifieds marketplace called "Project Deal" for 69 employees at its San Francisco office. The whole thing ran through Slack, with Claude agents handling every negotiation and deal. Each participant got a $100 budget. Before things kicked off, Claude conducted a short interview with each volunteer to figure out what they wanted to sell, at what price, what they wanted to buy, and what kind of negotiating style their agent should use. Anthropic then turned those answers into a custom system prompt for each agent. Ad From there, the AI agents took over completely. They wrote listings, found potential buyers and sellers, made offers, haggled over prices, and closed deals without checking in. The humans only stepped back in at the very end to swap the actual items, which ranged from a snowboard to a bag of ping-pong balls. Ad DEC_D_Incontent-1 Model strength quietly tilts the market The real research question was hidden in a parallel experiment that participants didn't know about at first. Anthropic ran four versions of the marketplace at the same time. In two of them, every agent used Claude Opus 4.5, Anthropic's frontier model at the time. In the other two, each participant had a 50 percent chance of being represented by Claude Haiku 4.5 instead, Anthropic's smallest model. Either way, only the AI agents talked to each other. In the "real" run, where every agent used Opus, the 69 agents closed 186 deals across more than 500 listings, moving just over $4,000 in total. Participants rated the fairness of individual deals at 4 out of 7 on average, right in the middle. Ad The mixed runs exposed a measurable gap. Opus users came out ahead, closing about two more deals on average than Haiku users. When the same item sold once through an Opus agent and once through a Haiku agent, Opus pulled in $3.64 more on average. A lab-grown ruby, for example, sold for $65 with Opus but only $35 with Haiku. The Opus agent opened at $60 and got pushed up by competitive bidding, while the Haiku agent started at $40 and got talked down. Ad DEC_D_Incontent-2 Across 161 items sold in at least two of the four runs, an Opus seller pulled in $2.68 more on average, while an Opus buyer paid $2.45 less. When an Opus seller faced off against a Haiku buyer, the average price hit $24.18, compared to $18.63 for Opus-on-Opus deals. With a median price of $12 and an average of $20.05 across all runs, Anthropic says these gaps aren't trivial. Ad The negotiation instructions participants gave their agents barely mattered. Some asked for a friendly approach; others wanted aggressive tactics like "negotiate hard and lowball at first." Aggressive sellers did get higher prices, but only because they set higher opening prices to begin with, Anthropic says. The losers had no clue they were losing Despite the clear price gap, participants with Haiku agents rated the fairness of their deals almost the same as Opus users: 4.06 versus 4.05 on the fairness scale. There was also no statistically meaningful difference in satisfaction with individual deals. Of 28 participants who used both Opus and Haiku across different runs, 17 preferred their Opus run, but 11 actually preferred the Haiku run. Anthropic calls this an "uncomfortable implication:" when agents of different strengths meet in real markets, people could end up on the losing side without ever knowing it. The company admits the experiment wasn't built to dig into these dynamics in detail and says more research is needed. The experiment also suggests that AI agent commerce isn't some far-off scenario: 46 percent of participants said they'd pay for a service like this. At the same time, Anthropic flags several risks. In a world with companies instead of volunteers, the incentives would look very different. Optimizing for AI agent attention could become a powerful tool that doesn't necessarily work in people's favor. And new security issues like jailbreaking and prompt injection would come into play with agents that actually act on your behalf. "The policy and legal frameworks around AI models that transact on our behalf simply don't exist yet," Anthropic writes, adding that "society will need to move quickly." "Will those dynamics reinforce, or even compound, existing economic inequalities?" Anthropic has run similar experiments before. As part of Project Vend, the company had Claude run a small shop out of its office . 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