Starting the year with clearer judgment
What Q4 sharpened for product leaders
AI has made building easier, but it has also made choosing harder.
That tension shaped the most valuable conversations in our community throughout the final months of 2025.
The most meaningful moments came from live conversations with product leaders who were willing to think out loud. That’s what made our AMA mentorship sessions stand out.
Throughout Q4, our cohorts were joined by senior leaders from companies including Walmart, Meta, and Mozilla. They spoke candidly about how decisions actually get made as pace accelerates and the margin for error shrinks.
Again and again, the same theme emerged: when everything feels urgent and possible, clarity becomes the constraint. Progress comes from developing the judgment to prioritize, to say no, and to align teams around decisions that hold up under pressure.
The faces in this graphic represent leaders who chose to invest their time helping others think more clearly about their work. I’m grateful for their openness and for the depth of engagement this community brought throughout Q4.
As the new year gets underway, it’s worth pausing to notice how your decision-making has evolved. Even if outcomes are still unfolding, stronger judgment compounds, because each good decision shapes the next one.
If these kinds of conversations resonate, I invite you to join one of our upcoming events below.
Elevate your craft with our free in-person and online events designed to keep you connected and ahead of the curve.
On January 22: The Product Speaker Series for New York. RSVP here.
On January 29: The Product Speaker Series for San Francisco. Get your ticket.
On January 7 (virtual): Problem-Solving, Ownership, and LLM Judgment in the AI Era. Join the conversation.
On January 8 (virtual): The 2026 AI Product Lifecycle Playbook for High-Velocity Teams. Join us live.
On January 13 (virtual): How Top B2B Product Teams Decide What to Build in Agentic AI. Sign up here.
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Great framing on the clarity constraint. The paradox is that AI gives us more capacity to build, which makes the judgment about what not to build way more critical. I've seen this firsthand where teams that shipped faster with AI assistants actually struggled more with priortization becuase they could prototype everything. The discipline to say no when things are technically easy but strategically wrong is probly the skill gap that separates good PMs from great ones right now.