As AI automates generalist PM tasks like documentation and context sharing, the role is evolving. The new path to value is specialization. PMs should identify their passion—be it data, design, or prototyping—and master the corresponding AI tools to develop deep, defensible expertise.

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.

Even as AI allows a designer to code or a PM to prototype, the fundamental responsibilities of each role persist. Design champions the user, product management owns business outcomes, and engineering ensures system integrity. The tools converge, but the core mindsets do not.

Building your own product forces you to confront technical realities like database migrations and architectural trade-offs. This firsthand experience provides deep empathy for engineering challenges, which in turn builds crucial credibility and improves collaboration with development teams.

PMs often feel pressure to keep engineers busy building new features. The real job is to drive deep understanding, even if it means perfecting three core features rather than adding a fourth. It's better to pause building than to create a bloated, mediocre product that does nothing well.

The PM role has evolved beyond feature roadmaps to a 'systems thinking' approach, akin to a General Manager. PMs now design entire customer experiences and business systems. This shift is accelerated by AI, which lowers the barriers for PMs to acquire skills outside their core background, whether technical or business-focused.

As AI commoditizes code, the traditional PM role is bifurcating. One path is becoming a hands-on builder who uses AI to create the product directly. The other is a business-focused strategist who concentrates on GTM, positioning, monetization, and competitive strategy, which AI cannot yet replicate.

The definition of "cross-functional" is shifting from coordinating between departments to embodying multiple skills. To increase speed, modern PMs must directly perform tasks in design, user research, and even coding, rather than acting as a 'glorified cross-functional secretary.'

AI's rise means traditional product roles are merging. Instead of identifying as a PM or designer, focus on your core skills (e.g., visual aesthetics, systems thinking) and use AI to fill gaps. This 'builder' mindset, focused on creating end-to-end, is key for future relevance.