Tom Verrilli，Whatnot 的首席产品官（曾任 Twitch 首席产品官、Twitter 产品增长总监），对产品管理持有一种引人深思的观点：“我们很遗憾产品管理这个职位竟然存在。”这并非是对产品经理的全盘否定，而是驱动 Whatnot 产品团队结构和招聘的核心理念。 Verrilli 解释说，在科技行业的早期，创始人（founder）和工程师（engineer）是直接构建产品（product）的。随着公司规模的扩大，一种“人力资源配比”（HR ratio）模式应运而生——通常是每六名工程师、一名设计师和一名工程经理配备一名产品经理。他认为，产品经理的这种过度泛滥“使工程师和设计师变得幼稚。他们完全有能力做出良好的决策，但因为总有产品经理替他们‘照管’一切，所以他们从不需要自己做决策。” 他的前提是，产品管理是一种“技艺，而非资格”，是通过“重复练习”才能练就的“肌肉”。工程师和设计师越是脱离决策过程，他们自身的这种“肌肉”就越是得不到充分锻炼。Whatnot 的做法是只在“确实有特定需求”的地方招聘产品经理，倾向于在可能的情况下，让工程和设计团队来完成“产品经理的工作”。 这一理念导致了极具选择性的招聘流程：两年内，有 31,832 人申请了 Whatnot 的产品经理职位，但最终只招了一人。Verrilli 强调，产品经理招聘中“正在走下坡路”的是那些专注于“推动协同和利益相关者管理”的候选人，这常常是“政治手腕”的代名词。相反，他寻求的产品经理要能同时展现“宏观思维和微观思维”，对验证想法表现出“迫切”，并在构建和迭代方面有具体经验，而不仅仅是“照管”已有的东西。他建议有抱负的产品经理通过不断问“如果情况好（绿色）怎么办？如果情况糟（红色）怎么办？”以及推演最坏情况来培养“系统性思维”。 Verrilli 倡导的一个重大转变是产品经理转向独立贡献者（IC）工作，而非“大型组织管理”。他批评了传统的产品经理晋升路径：成功的PM会成为总监，然后“高升到脱离实际工作”。在 Whatnot，即使是管理者（包括他本人，50%的时间从事 IC 工作）也被期望亲力亲为。这使得经验丰富的“顶尖人才”能够产生直接影响，更快地做出决策，并利用他们在冲突领域（例如，一名产品经理同时负责广告和发现功能，从而自然地实现两者对齐）的更广泛理解。对 Verrilli 而言，产品经理的 IC 工作意味着有效交付所需的一切，从分析用户支持工单和提取数据，到撰写需求文档和主持站会。 AI 在此模式中扮演着至关重要的赋能角色。它能为“独立贡献者提供巨大的杠杆作用”，实现快速数据分析（数据科学家过去需要一周才能完成的工作现在只需几分钟），无需总是麻烦工程师就能理解代码库，并建立连接客户行为与实时代码分析的实时反馈循环。这种效率使得资深产品经理能够处理更广泛的职责范围，并基于真实情况快速做出决策。 Verrilli 承认，这种模式需要特定的公司文化和领导风格。虽然“招聘优秀人才，然后放手让他们去做”是一个流行的口号，但他倡导的是“先验证，再信任”。领导层，尤其是在创始人领导的公司中，必须与“基层”保持紧密联系，才能做出知情的宏观决策。他描述说，他的首席执行官 Grant 会腾出时间，与团队“坐下来一起研究解决问题”，这正是这种亲力亲为方式的典范。他用“拉手风琴”的比喻：不断放大视野以获取战略方向（“吸气”），然后缩小视野以从即时结果中构建和学习（“呼气”/“出乐”）。 最终，Verrilli 相信核心的“产品经理式技能”——识别要构建什么、提炼需求、优先级排序和理解业务战略——是“持久的”，且比以往任何时候都更有价值。他警告人们警惕“产品管理中的‘作秀’现象”，即产品经理擅长沟通和使用框架，但缺乏实际构建经验。他在 Twitter 等职业经历中领悟到，虽然产品与市场契合度可以克服严重的组织混乱，但“大多数时候你听到某事‘真的很复杂’时，它其实不然，只是领导力薄弱罢了。”他还学会了警惕平均值，因为它们往往会掩盖关键的个体用例。 尽管 Whatnot 的这种数量更少、资历更深、更专注于 IC 工作的 PM 模式可能不具普适性，但 Verrilli 坚称，行业向着用 AI 赋能个体，并要求更深入、更亲力亲为的产品工作转变，是一个广泛而必要的趋势。

Tom Verrilli, Chief Product Officer at Whatnot (and former CPO at Twitch, Director of Product Growth at Twitter), holds a provocative stance on product management: "We regret that product management exists." This isn't an outright dismissal of PMs, but a core philosophy driving Whatnot's product team structure and hiring. Verrilli explains that in the early days of tech, founders and engineers directly built products. As companies scaled, the "HR ratio" model emerged – typically one PM for every six engineers, a designer, and an engineering manager. He argues this over-proliferation of PMs "infantilizes the engineers and designers who are perfectly capable of making good decisions, but just never had to because there was always a PM to babysit them." His premise is that product management is a "trade, not a qualification"—a muscle built through "reps." The more engineers and designers are abstracted from decision-making, the more their own "muscle gets underdeveloped." Whatnot's approach is to hire PMs only "where there's really specific need," preferring to enable engineering and design to do "PM work" wherever possible. This philosophy has led to a highly selective hiring process: in two years, 31,832 people applied for PM roles at Whatnot, and only one was hired. Verrilli highlights what's "trending down" in PM hiring: candidates focused on "driving alignment and stakeholder management," often code for "politics." Instead, he seeks PMs who demonstrate both "macro thinking and micro thinking," exude "impatience" to validate ideas, and have concrete experience in building and iterating, not just "babysitting things that existed." He advises aspiring PMs to develop "systems thinking" by constantly asking "what do we do if it's green? What do we do if it's red?" and playing out worst-case scenarios. A significant shift Verrilli champions is PMs moving towards individual contributor (IC) work, away from "big org management." He criticizes the traditional path where successful PMs become directors and are "promoted out of doing things." At Whatnot, even managers (including himself, at 50% IC work) are expected to be hands-on. This allows experienced "A players" to have direct impact, make faster decisions, and leverage their broader understanding across conflicting areas (e.g., one PM owning both ads and discovery to naturally align them). For Verrilli, IC work for a PM means anything required to ship effectively, from analyzing support tickets and pulling data to writing specs and running stand-ups. AI plays a crucial enabling role in this model. It provides "enormous amount of leverage for an IC," allowing quick data analysis (what used to take a week for a data scientist now takes minutes), understanding codebases without always bugging engineers, and real-time feedback loops connecting customer behavior with live code analysis. This efficiency allows senior PMs to handle broader scopes, making decisions quickly based on ground truth. Verrilli acknowledges that this model requires a specific company culture and leadership style. While "hire great people and get out of their way" is a popular mantra, he advocates for "verify then trust." Leadership, especially in a founder-led company, must remain deeply connected to the "ground floor" to make informed macro decisions. He describes his CEO, Grant, clearing his schedule to "sit and figure it out" with teams, exemplifying this hands-on approach. He uses the "play the accordion" analogy: constantly zooming out for strategic direction ("air in") and zooming back in to build and learn from immediate results ("music out"). Ultimately, Verrilli believes core "PM-y skills" – identifying what to build, distilling requirements, prioritizing, and understanding business strategy – are "durable" and more valuable than ever. He warns against "product theater," where PMs are skilled in communication and frameworks but lack practical building experience. His career experiences, including Twitter, taught him that while product-market fit can overcome significant organizational chaos, "most of the time you hear it's really complex, it isn't, leadership's just weak." He also learned to be wary of averages, as they often obscure crucial individual use cases. While Whatnot's model of fewer, more senior, IC-focused PMs may not be universal, Verrilli asserts that the industry's shift towards empowering individuals with AI and demanding deeper, more hands-on product work is a broad and necessary trend.