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As Google, OpenAI and Meta Push A.I. Agents, Enterprises Need Models That Think Less 

As companies bring A.I. into critical business workflows, the priority is shifting from raw intelligence to predictable execution, measurable accuracy and cost-effective performance.

The race to make A.I. more capable is entering a new phase. Google’s announcement yesterday (Oct. 8) of a “universal” Gemini agent that can run in the background of apps and devices marks the latest step in a broader push to make A.I. act on users’ behalf. OpenAI introduced its always-on agents, called dots, in September, just weeks after Meta released Muse, a personal agent capable of shopping, booking travel, sending emails and making payments. The ambition has evolved from giving users a better way to generate text or analyze simple information to build systems that can do the work themselves, across both enterprise workflows and personal life. 

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For the past several years, A.I. has been organized around a fairly simple assumption: smarter models will produce better software. Every new generation promises stronger reasoning, longer context windows and better performance across a growing list of benchmarks. Companies, understandably, have treated those improvements as a roadmap: when a better model arrives, it’s time to upgrade. 

But as A.I. moves from generating answers to executing tasks, enterprise software is beginning to expose a flaw in that logic. In many of the most valuable business workflows, the goal is not to give an A.I. model more freedom to reason. It is to give it less.

We encountered this problem building A.I. for accounting at Campfire. Accounting is an unusually unforgiving domain for probabilistic answers. A model can generate five different versions of a good sales email, and all five might be useful. But if it is categorizing the same Uber transaction 500 times, there is generally only one correct answer the company wants all 500 times. A close approximation is not close enough when the result ultimately feeds a general ledger,........

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