The art of influence: The single most important skill that AI can’t replace | Jessica Fain (Webflow, ex-Slack)

Influence, in Jessica Fain’s framing, is not a soft political skill layered on top of product work; it is the mechanism by which product work gets funded, prioritized, and ultimately shipped. Drawing on roles at Box, Slack, Brightwheel, and now Webflow, she argues that many product managers stall because they assume good ideas should win on merit alone. Her own turning point came at Slack, where some ideas gained traction and others died despite strong customer evidence. That led her to ask then-new CPO April Underwood to consider her for a chief-of-staff role while Fain was eight and a half months pregnant. That vantage point, later extended under Tamar Yehoshua, taught her that people routinely misunderstand how executives actually operate: their calendars are a blur of budget reviews, hiring, legal issues, people management, and product decisions, so they enter meetings without the context the PM has been building for weeks.

From that observation, Fain develops a practical theory of influence built on empathy. She says PMs are skilled at user discovery but often stop applying curiosity once they enter an executive meeting, where they instead seek approval. Her advice is to treat the executive as another important user: understand how they are measured, what pressures they are under, what the board is asking for, and what communication format best activates their thinking. Some leaders want a silent-read memo, others want a design prototype, a customer story, or a dashboard. In any case, she recommends a tight meeting setup: spend less than a minute reestablishing the topic, where the previous conversation ended, what decision is needed now, and how the meeting will proceed. She also argues that proposals should be anchored directly to company outcomes, not merely team activity, and that PMs should trace how their local metrics ladder up to broader business goals.

A recurring theme is that influence should not be confused with either passivity or manipulation. Fain explicitly rejects being a yes-person; PMs are paid to be the deepest domain expert in the room. But expertise works best when paired with curiosity about why an executive believes something. Her suggested phrase—"That’s so interesting, what led you to believe that?"—is meant to uncover the hidden context behind apparently bad takes, whether that is board pressure, new market information, or knowledge of another team’s work. She also emphasizes that executives often communicate indirectly. The strongest operators pick up on breadcrumbs, respond quickly, and keep momentum alive. She contrasts this with teams that wait too long, miss the point, or fail to clarify urgency. If an executive floats an idea, she recommends asking how strongly they feel about it and whether it supersedes current priorities. In her view, speed of follow-up matters because executives move on fast, and trust is built when people act on feedback rather than merely recording it.

Fain gives several concrete operating patterns. For executive reviews, she advises leading with the recommendation and keeping supporting detail in reserve rather than narrating the whole research process. She warns that presenting only one option often backfires because leaders cannot see what tradeoffs were considered. At Webflow, a review with CPO Rachel Wolan went poorly until Fain’s team returned two days later with multiple options and clearer reasoning. From Slack, she described a "customer love sprint," a two-week effort in which the core product team focused exclusively on polishing the user experience and shipped 65 improvements, directly reinforcing leadership’s belief that craft was central to Slack’s differentiation. She also argues that senior trust is built not just by asking for resources, but by diagnosing constraints clearly, reducing risk through small experiments, and being willing to kill projects that no longer make sense.

The AI portion of the conversation pushes these themes further. Fain thinks AI lowers the cost of execution, prototyping, analysis, and iteration, which means the scarce skill shifts toward deciding what deserves to survive. She calls this a golden age of product management because the work of judgment, alignment, and synthesis becomes more important, not less. She notes that teams are already using AI to simulate executive reactions by training GPTs on prior review transcripts or mining Slack for leadership priorities. But she is skeptical that AI eliminates the need for humans; instead, she thinks it increases the premium on strategy clarity, since empowered teams and agents can move very fast in the wrong direction. Her conclusion is that humans still provide anthropological insight into users, taste about what is good enough to ship, and the trust needed to coordinate organizations. In a world of abundant software and agents acting like teammates, influence remains the skill that turns possibility into committed action.