Coffee in the Room is back tomorrow evening — this time we’re talking roadmaps. The ones everyone loves to hate. The ones that are either too high level or too low level, that overlap quarters and look janky, that nobody believes and everybody ignores. Come ready to talk about what’s actually working for you, what you’ve ditched, and how you’re thinking about roadmaps in a world where AI makes them easier to maintain but the pressure to commit hasn’t changed. Wednesday 21st October 6:00pm BST / 10:00am Pacific Hope to see you there. ☕

That’s the closing line from a piece by Ravi Mehta published earlier this month and it got my attention. His argument is sharp. You can eliminate the PM role. You can flatten the team. You can distribute the responsibilities. But the work remains. Someone still has to talk to customers. Own the vision. Connect features to business outcomes. Protect the quality bar. Decide what deserves to ship. If nobody does that work, the product culture shrinks. And after rounds of layoffs and efficiency drives, he worries a lot of companies are watching exactly that happen right now. The part that resonated most for me was this: the PM-to-engineer ratio tells you almost nothing about PM talent. It tells you everything about the organization around the PM. A 1:30 ratio could mean a brilliant product culture where founders, designers, engineers, and researchers all amplify the PM. Or it could mean one exhausted ticket writer building whatever the loudest stakeholder wants. Same number. Opposite cultures. His take is that AI shifts the bottleneck from building to judging. More options. Cheaper to build. Faster to ship. But empathy, strategy, judgment, and taste are what determine whether that speed creates progress or just noise. We don’t need PMs spending more time building. We need them spending more time figuring out where we’re actually going. Worth a read. Link here. Which of these 12 feels most underdone in your organization right now?

I read an interesting study from Metis Strategy this week that basically that if 2025 was the year of AI experimentation, 2026 is the year of proof. Boards and leadership teams want to know what the AI investment actually changed not what shipped, what changed. And a lot of teams built the pilot but never built the reporting or feedback loop. They can describe what they shipped without being able to prove what it worked. I think that the feedback loop is probably the Product Manager's to solve. Which by default means the PM role isn't shrinking because of AI. Instead we are being asked to use our judgement to decide what is worth building, prove it works, and know when to pull the plug. Just like always. :) How are you measuring whether what you built with AI is actually working?

Hi all, The votes are in and our topic for October is Roadmaps: Love 'em or Leave 'em. We'll discuss how roadmaps have evolved over the past few years and where you have landed on them in your current day to day. Please go to the Doodle Link and let me know what times work best for you to meet. I'll do my best to find a time that works for all time zones and availability.