AI made building software much cheaper. It didn’t make judgment, craft, or understanding your customer any less important. Those still move at human speed. The job is shifting from deciding what’s worth building to deciding what’s worth shipping: build more, test more, throw more away, and hold the line on what is customer-worthy.
The 12 product competencies still describe the skills a team needs to build products customers can’t live without. What changed is how we practice them. Nobody needs to be great at all 12. Individuals should be spiky, and teams should be well-rounded. Knowing your shape helps you decide which strengths to build on, which gaps to cover, and who you need beside you.
What this essay explores
- Understand why cheaper building makes judgment, craft, and customer understanding more consequential.
- Replace assembly-line handoffs with collaborative experimentation while preserving clear accountability for outcomes.
- Build more, test more, throw more away, and decide whether a finished product deserves launch.
- Identify your strongest product competencies and cover gaps through complementary teammates.
- Use AI to accelerate machine work while focusing human effort on customers, habits, and alignment.
- Set ground rules that separate prototypes for learning from production software for shipping.
The shape of the role doesn’t change, but how we practice each competency is fundamentally different.
Key takeaway
AI gets us to the hard part faster. Your judgment, craft, and customer understanding determine whether faster building becomes a product worth shipping.
