As AI automates the tactical middle of product management—specs, schedules, and engineering liaison—the role will bifurcate. PMs must add value at the fuzzy front-end (discovery, strategy, economics) and the go-to-market back-end (sales enablement, marketing), creating a barbell-shaped time distribution.

As AI automates time-consuming tasks like data analysis, requirement writing, and prototyping, the product manager's focus will shift. More time will be spent on upstream activities like customer discovery and market strategy, transforming the role from operational execution to strategic thinking.

As AI tools automate coding and prototyping, the product manager's core function is no longer detailed specification writing. Instead, their value multiplies in judging, facilitating, and making the right strategic decisions quickly. The emphasis moves from the 'how' of building to the 'what' and 'why,' making decision-making the critical skill.

As AI agents automate tasks like writing PRDs and gathering data, the product manager's core value shifts. They spend less time on operational execution and more time applying strategic judgment—validating AI outputs, providing correct context, and making crucial decisions.

The PM role has often devolved into tactical development execution. By automating these tasks, AI forces the role to return to its original strategic function, akin to a P&G brand manager. The focus shifts back to owning the entire system: business model, market dynamics, and go-to-market strategy.

As AI automates routine tasks like writing specs and managing backlogs, the core responsibility of a PM will shift entirely to exercising judgment. This involves evaluating a high volume of potential product changes for their strategic fit, brand impact, and long-term sustainability.

The role of a Product Manager is shifting in the AI era. With coding agents handling execution, the need for diverse tools like Figma is diminishing. The PM's core value is now elevated to strategic business judgment, focusing on simplifying product surface area and prioritizing high-impact initiatives.

With AI handling first drafts of documents like PRDs, the PM's value shifts from authoring to editing. The primary job becomes that of an 'editor-in-chief'—questioning outputs, defending the 'why' behind decisions, and ensuring every artifact is grounded in real customer insight and strategic thinking.

As AI accelerates discovery and building, the role of a PM is less about managing current execution. Their value becomes staying one or two steps ahead of the team to define the next problems to tackle. This requires a shift from tactical oversight to strategic direction-setting.