Asked. Answered.

The angle I would add is what changes when your product involves AI, and the buyer has AI skepticism baked into their procurement cycle. At Tableau and later Salesforce, the enterprise sale was about ROI clarity and champion development. The work was hard but the mental model was stable. When the product is AI, procurement added a third track: "will this actually work in our environment?" And PMM is the only function positioned to answer that question credibly, at scale, before the sales team gets in the room.

Win rate is the right north star. The core problem with win rate as a CI KPI is attribution lag. A competitive battlecard built today influences a deal that closes in six months, and by the time the deal closes, the field has forgotten which asset changed how they handled the objection. The organisations solving this well are tracking competitive touchpoints in the deal, not just the outcome. Not "did we win?" but "was competitive content used and at which stage?"

The thing I would add is what happens when the disagreement is not really about strategy. It is about territory. In my experience running PMM across organisations at Microsoft, Salesforce, and now at the Sr. Director level, most of the strategy disagreements that land on a PMM are actually executive boundary disputes wearing the costume of strategic debate. The surface argument is "which positioning do we use." The real argument is "whose domain does this GTM motion belong to."

The companies that survived feature parity cycles were not the ones with longer roadmaps. They were the ones who made the feature discussion irrelevant by owning a specific outcome claim. In enterprise AI, where copying has gone from a quarterly concern to a weekly one, the practical move is to stop defending features and start owning the deployment story. Your competitors can copy the capability. They cannot copy your customer's production deployment.