There’s no escaping the conversation about AI’s impact on our roles. Tools can now summarize user interviews, draft entire PRDs, analyze market data, and even suggest A/B test variations in minutes. This is the ‘AI co-pilot’ dream: freeing us from tactical execution to focus on the big-picture strategy, vision, and deep user connection.
But here’s the tension I’ve been wrestling with: where is the line between augmentation and abdication? The craft of product management has always been in the details—the nuance picked up while personally synthesizing raw user feedback, the intuition built from wrestling with messy data, the insights discovered while painstakingly drafting a spec.
When we offload these core tasks to an AI, are we risking the loss of that deep, earned context? We gain speed, but do we sacrifice the very intuition that makes a great PM irreplaceable? By outsourcing the ‘doing,’ we might become excellent prompt engineers but lose the hands-on expertise that truly informs world-class product strategy. We’re told to be the ‘why’ behind the product, but that ‘why’ is often discovered in the ‘how.’
How are you and your team navigating this balance between leveraging AI for efficiency and ensuring you don’t lose the essential, hands-on product intuition?