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Lenny's Podcast - Why every company now needs to think and operate like a lab team | Josh Woodward (VP Google Labs)

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在本期莱尼播客中,主持人莱尼·拉奇茨基邀请到了谷歌实验室、Gemini应用和AI Studio负责人乔什·伍德沃德。他在谷歌工作了十六年以上,一直致力于试验和扩展新的AI产品。莱尼的核心观点是,如今每家公司都必须像实验室团队一样思考和运营。由于AI技术和能力变化极快,组织需要一个在最前沿运作的专职团队——尝试新模型、开展实验,并在竞争对手或初创公司之前发现机遇。 ### 寻找好点子与产品市场契合度 伍德沃德赞同这一前提,并强调好点子很少来自传统的头脑风暴会议或设计冲刺。相反,它们是由人们在周末进行黑客式开发或从事副业时自然产生的。伍德沃德分享了一个实用的策略习惯:维护一个“几乎可能实现”的事情清单,并密切关注技术变革或阶段性变化使其成为现实的准确时刻。 在评估早期原型时,伍德沃德依靠简单的全人类指标,而不是数据看板:观察人们的眼睛,看它们是否发光并向前倾身。值得追求的点子能如此有效地解决痛苦的用户问题,以至于人们愿意为此付费。相反,当热情耗尽且团队知道它行不通时,项目就应该被叫停。伍德沃德强调了培养一种文化的重要性,在这种文化中,团队要有足够的安全感,在领导层发现之前就指出失败的点子。 ### 实验室与Gemini的架构 伍德沃德同时监管谷歌实验室(从零到一的实验)和Gemini应用(服务全球超过十亿用户)。尽管规模存在巨大差异,但两者都有着从零到一体的脉搏和一个指导信条:用户第一,谷歌第二,产品第三。伍德沃德指出,谷歌实验室将项目分为不同阶段——从零到一实验室、一到十实验室以及十到一百实验室——每个阶段都针对完全不同的指标和挑战进行了优化。 ### 被低估/高估的趋势与宝贵技能 * **被低估:** 关于产品原则和价值观的讨论。伍德沃德认为,产品编码了构建它们的人的原则,行业需要就他们真正想要创造的未来进行更多对话。 * **被高估:** 模型基准测试和ELO评分。世界上大多数人并不关心基准测试;重要的是产品是否能提供真正的价值。 在热门技能方面,伍德沃德看重“遗忘率”——一个人学习某项东西的速度有多快,以及能否根据新数据放弃它。他还看重“爆发性耐力”(在保持长期可持续性的同时全力以赴的能力),以及建立信任并与AI智能体和人类无缝协作的能力。尽管职位角色正在变得模糊,但伍德沃德警告说,不要过度吹捧每个人现在都只是一个泛化的“构建者”这一概念,并指出专业专长和深厚的领域专业知识依然至关重要。 ### 建立内部实验室团队 对于希望建立自己实验室团队的公司,伍德沃德提出了三个关键建议: 1. **独立性:** 创造一个空间,让奇怪的事物得以生长,而不是依附于现有的业务单元之下。 2. **清晰对齐:** 确保实验室的目标是让用户和核心公司获得成功,而不仅仅是为了成就自身的荣耀。 3. **善意的麻烦:** 不仅将实验室用于技术探索,还要用它来挑战和试点新的内部流程,例如职级阶梯和工作方式。 对话在轻松的快问快答环节中结束,其中包括谷歌实验室独特的内部传统:向成功优化并收获TPU的队友颁发微型Etsy耙子。

In this episode of Lenny’s Podcast, host Lenny Rachitsky is joined by Josh Woodward, Head of Google Labs, the Gemini app, and AI Studio, who has spent over 16 years at Google experimenting with and scaling new AI products. Lenny’s core thesis is that every company must now think and operate like a labs team. Because AI technology and capabilities are changing so rapidly, organizations need a dedicated team operating at the frontier—trying new models, running experiments, and uncovering opportunities before competitors or startups do. ### Finding Great Ideas and Product-Market Fit Woodward agrees with this premise, emphasizing that good ideas rarely come from conventional brainstorm meetings or design sprints. Instead, they emerge organically from people hacking away on weekends or taking side projects. Woodward shares a useful tactical habit: maintaining a list of things that are "almost possible" and watching for the exact moment a technological shift or phase change makes them a reality. When evaluating early prototypes, Woodward relies on a simple human metric rather than data dashboards: looking at people’s eyes to see if they light up and lean in. Ideas worth pursuing solve a painful user problem so effectively that people are willing to pay for it. Conversely, projects should be killed when passion runs out and the team knows it isn't working. Woodward stresses the importance of fostering a culture where the team feels safe enough to call out failing ideas before leadership does. ### The Labs and Gemini Structure Woodward oversees both Google Labs (zero-to-one experiments) and the Gemini app (serving over a billion users globally). Despite the massive difference in scale, both share a zero-to-one heartbeat and a guiding mantra: users first, Google second, and products third. Woodward notes that Google Labs categorizes its projects into stages—zero-to-one labs, one-to-10 labs, and 10-to-100 labs—each optimized for very different metrics and challenges. ### Over/Under-Hyped Trends and Valuable Skills * **Under-hyped:** The discussion around product principles and values. Woodward believes products encode the principles of the people who build them, and the industry needs more conversations about the kind of future they actually want to create. * **Over-hyped:** Model benchmarks and ELO ratings. Most people in the world do not care about benchmarks; what matters is whether a product delivers real value. In terms of trending skills, Woodward looks for "unlearning rate"—how fast someone can learn something and then walk away from it based on new data. He also values "explosive endurance" (the ability to go hard while maintaining long-term sustainability) and the capacity to build trust and collaborate seamlessly with both AI agents and humans. While job roles are blurring, Woodward warns against the overhyped notion that everyone is now just a generic "builder," noting that professional specialties and deep domain expertise remain vital. ### Setting Up an Internal Labs Team For companies looking to set up their own labs team, Woodward offers three key tips: 1. **Independence:** Create a space where weird things can grow without being nestled under an existing business unit. 2. **Clear alignment:** Ensure the lab's goal is to make users and the core company successful rather than just serving its own glory. 3. **Good trouble:** Use the lab not just for technology exploration, but to challenge and pilot new internal processes, such as job ladders and ways of working. The conversation concludes with lighthearted lightning-round questions, including Google Labs’ unique internal tradition of awarding miniature Etsy rakes to teammates who successfully optimize and harvest TPUs.