Even with AI accelerating development, a PM's core role is managing what *isn't* being built. The ability to calculate Total Cost of Ownership (TCO) and strategically say "no" is more critical than ever, as even quickly-built features have long-term costs that displace other opportunities.
Instead of using written narratives to clarify thinking, product managers should leverage AI prototyping tools to go directly from idea to a testable prototype. Documentation can then be generated from the validated prototype in a fraction of the time, dramatically speeding up the feedback loop.
The most critical role on a team is the "product visionary"—the person with a clear, customer-backed vision. This person can be an engineer, a designer, or a PM. Great leadership involves identifying and empowering this individual, no matter their function, rather than assuming it's the PM's job.
The PM role is a high-leverage position intended to be a force multiplier for engineering and design. If a PM isn't making the team at least twice as good or twice as fast, their presence may be hindering progress, and the team would be better off operating without them.
To lead authentically and effectively, especially during periods of change, leaders must be able to "lead by example." This means building prototypes and having practitioner-level opinions on design and product. Theoretical leadership is no longer sufficient to retain a team's respect in a fast-moving tech landscape.
While AI tools make building technology faster, adoption is ultimately constrained by human and organizational factors. Systems for payroll, regulations, and workflows are built around people, who change much slower than tech. This human layer acts as a natural brake on technological disruption.
A leader's effectiveness depends on their ability to calibrate what a "meaningful outcome" is for their company's specific stage and scale. For a large enterprise, pursuing a $100 million idea is a distraction. Leaders must ruthlessly filter for opportunities that align with the company's financial gravity.
Generative AI can be used as a conversational expert to quickly gain deep domain knowledge in new industries. By engaging in long dialogues about market trends, regulations, and business models (e.g., value-based medicine), a leader can compress months of research into a single afternoon.