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VentureBeat ML · 2026/7/21 18:15:46
Evals are the new PRD, Expedia’s AI chief tells VB Transform 2026

Evals are the new PRD, Expedia’s AI chief tells VB Transform 2026

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核心亮点:评估取代了传统需求文档,成为AI产品设计的关键——好与坏不再靠写需求,而是靠设计测试来定义。 通俗解读:想象一下以前做一款新产品,要先写厚厚的需求文档告诉程序员“我想要什么”。如今在AI时代,Expedia的AI老大说:需求文档已经过时了,真正重要的是“评估”——也就是你要先想好怎么测试这个AI。比如让它当客服,你就得设计各种刁钻情景、找专门团队“红队挑刺”,看它能不能正确应对。他特别提醒:别给AI加太多死板规则,否则会扭曲用户真实反馈,反而让AI学歪了。更聪明的做法是按层次治理:先定高层的原则(比如“公平对待客户”),再用流程和工具落地,最后自动化执行。而且风险评估决定了检查的严苛程度,低风险随便测,高风险要过重重关卡。 实际影响:今后你用到的AI产品会更靠谱——企业在开发时会投入大量精力测试,确保它不胡说八道、不犯低级错误。同时因为少了生硬规则,AI的回答会更自然,聊起天来像真人。不过在高风险场景(比如金融、医疗),企业会设更严格的门槛,保证安全。
“The new PRD are the evals,” Xavi Amatriain, Expedia Group’s first chief AI and data officer, told the VB Transform 2026 audience last week in Menlo Park. “So basically, you encode what you want the product to do through your evals, which might include red teaming evals and all kinds of other things, which already have a bunch of security requirements. So, you already embed that into the PRD and the product design document before you even start coding.”He pushed it further. “With AI-assisted or AI-generated code, that’s gonna be the future. It’s like all your thinking is gonna go into the evals.”Amatriain served as VP of AI and Compute Enablement at Google across the platforms powering Gemini and Google Search before his December 2025 appointment at Expedia. He's mentored talent who went on to found Perplexity and Scale AI. VentureBeat’s VB Pulse research on the evaluation gap reinforced the stakes. Sixty-six percent of the 157 enterprises surveyed already permit some production deployment without human review or are building toward it within the next 12 months, yet only 5% fully trust the automated evaluations that would make that decision. Half have shipped an agent that passed internal evals but then failed with a real customer.Don’t let guardrails get in the way of feedback“The more guardrails and artificial business rules and sort of rules that you put into the system, the worse off,” Amatriain said. “Not only because they’re brittle, but also because they actually mess up with the feedback loop. You are actually biasing the user and the feedback you get from the user, and then you’re learning that in the wrong way.” He called guardrails “a necessary evil” and said the goal is to minimize their impact over time.Not everyone at Transform agreed. Other speakers argued during the event that the highest-risk actions still demand very firm guardrails.Expedia governs AI through three layers instead. Principles come first, communicated broadly. “I like to encode at a very high level how I expect decisions to be made, because in a large organization you’re gonna have a lot of distributed decision making,” Amatriain said. “And sometimes, if you’re lucky enough, those principles might be embedded in your culture. But most of the time, my experience has been they’re not.” The processes and tools that enforce them follow. “Principles look really nice on a picture on some wall, but you need to then give them teeth,” he said. Automation sits on top of both.In practice, this plays out through what Expedia calls agent release toll gates, checkpoints calibrated to risk. “Governance needs to correlate to the risk,” Amatriain said. “And if you have something that is low risk, you don’t need too much governance to get in the way. But if there’s a lot of risk, then you need more governance. That can be encoded.” The toll gates tie evaluation rounds, red teaming, and security review to each agent’s risk level, and the checks shift from recommended to required as the stakes climb. Specialized agents over monolithic intelligence“Even when I was at Google, I was like, I don’t believe in AGI as sort of like a singleton and a unified sort of like single model,” Amatriain told the audience. “I think it’s much better to think of it as composition, sort of like having specialized agents that are very good at some task and then composing the system out of those specialized agents.”Expedia’s architecture starts at the component level. Tools compose into skills, skills assemble into sub-agents, and sub-agents get orchestrated into the full agentic system. “You need to have those principles that are unified that talk about things like what is the tone that we’re using, how are we addressing the user, how are we passing context, memory,” he said. “All of that needs to be thoroughly designed.” He framed this as a systemic design problem. “It’s not about the model, it’s not about a specific solution, it’s about how you’re designing the system.”Amatriain
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