ChatPRD

12 careers that will dominate the next 10 years: 1. AI/ML Engineer 2. Data Scientist 3. Cybersecurity Specialist 4. AI Product Manager 5. Robotics Engineer 6. Cloud Solutions Architect 7. AI automation specialist 8. Marketer 9. Technician 10. UX/UI Designer 11. AR/VR Developer 12. Blockchain Developer

Question: Given that all PMs will eventually have access to the same AI tools, how do I differentiate myself as a product manager? I get this question a lot. And I don't love the shallow answer going around that "all that matters is taste." Taste is definitely important, but here's my far more concrete playbook for differentiating as a PM in the age of AI: 1. Stay at the frontier of AI fluency - I think too many people are dismissing this one saying that "everyone is going to have access to the same tools." But I'm a year and a half into this and I can tell you the gap is only widening on folks who can wield AI well in their job vs those that can't. And I don't see that changing anytime soon. So the people best positioned are the ones that know how to use AI effectively to produce great output, which is no easy task. 2. Taste / high standards / judgment - This is the one everyone talks about and I agree it's important. For example, I recently showed off 13 AI PM skills I built in Claude Code. What I didn't show was the 16 others that I tried to build but ultimately threw away because the output didn't meet my bar. I'm seeing lots of other people ship these skills and just accept the low quality output coming out of them. This is a mistake. The first battle is knowing what great product work looks like. The second battle is continuing to hold yourself to that standard. Don't ship slop. 3. Domain expertise - As the functional aspects of the role become more commoditized, I do think domain expertise in a given field becomes even more important. I don't think it's a fluke that a cardiologist beat experienced software developers in Anthropic's recent vibe coding contest. It's because his deep knowledge in the domain allowed him to come up with such a compelling solution to the post-visit patient problem that he deeply understood. Only a domain expert could do that. 4. Product strategy - AI is terrible at product strategy. I've tried every which way and it never comes up with a compelling, differentiated product strategy that has any chance of winning the market. I think that's going to be the case for awhile. So it's a great area to continue to build your muscle. 5. Design - The advancements coming out of Gemini, etc is impressive, but I still can't get AI to match the world-class designers I've worked with in my career. Especially on interaction design, not just visual design. Learning these skills is still valuable.

does AI change the PM's job? no - it's still "deliver the right product at the right time" - whether you're writing a prompt or a PRD the tactics may evolve but the goals remain the same. one of my favorite segments from our interview with ben horowitz

Entrepreneurship is more about stamina than it is about genius

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“I think the traditional PRD process (PRD → mock → code) is dead. But text that describes product requirements is very much alive. This associated document should be a required companion to the prototype before being handed off for review.”

you must internalize this ASAP: - less handoffs, decide fast - faster exploration - encourage to throw away code/tokens - learn by building, de risk with code - pick leads that can own design, eng and product

PRDs are dead.

you must internalize this ASAP: - less handoffs, decide fast - faster exploration - encourage to throw away code/tokens - learn by building, de risk with code - pick leads that can own design, eng and product

you must internalize this ASAP: - less handoffs, decide fast - faster exploration - encourage to throw away code/tokens - learn by building, de risk with code - pick leads that can own design, eng and product