When joining a new company or industry, it's impossible to absorb a decade of accumulated knowledge in weeks. Product managers must be patient and reject the '90-day plan' pressure, as deep learning realistically takes months.

Expert product leadership is not about mastering standard frameworks, but about discerning which elements apply to a company's unique situation. In many contexts, like a PE-backed manufacturer going digital, most textbook frameworks are unsuitable and must be selectively combined, adapted, or rejected entirely to be effective.

Even with a successful playbook from a company like Zoom, a marketing leader must adapt significantly when moving to a new context. Selling a physical product globally introduces complexities like homologation, customs, inventory, and channel sales that require eating 'humble pie' and learning the new business from the ground up.

It is easy to confuse process mastery with product success. The most critical skill is judgment—the ability to identify what truly creates customer value. This is proven not by your process, but by the ultimate business outcome: customers paying with their time or money.

Experienced product leaders avoid relying on muscle memory or applying a standard playbook. Each company, product space, and problem is unique. The most effective approach is to first understand the specific context and then select or create the right tools and frameworks for that unique situation.

As AI accelerates engineering, the technical gap between product and engineering shrinks. The most defensible skill for PMs becomes their superior understanding of the business model, market context, and sales motions, making them the indispensable source of strategic direction that AI cannot replicate.

A non-linear career across varied industries isn't a weakness but a strength. This 'jungle gym' path sharpens a product manager's core toolset by forcing them to apply fundamental principles to new problems, much like a doctor specializing in different fields to become a better diagnostician.

The essential skill for AI PMs is deep intuition, which can only be built through hands-on experimentation. This means actively using every new LLM, image, and video model upon release to objectively understand its capabilities, limitations, and trajectory, rather than relying on second-hand analysis.

Product management "range" is developed not by learning domain-specific facts, but by recognizing universal human behaviors that transcend industries—the desire for simplicity, convenience, or saving time. Working across different verticals hones this pattern-matching skill, which is more valuable than deep expertise in a world of accessible information.