It seems like every week there’s a new AI tool promising to revolutionize the PM workflow. From drafting user stories and PRDs in seconds to instantly synthesizing user feedback, these ‘AI copilots’ offer a massive leap in efficiency. I’m all for leveraging new tech to automate grunt work and move faster.
But I’ve been thinking about the hidden cost. The true craft of product management has always been rooted in deep user empathy, intuition, and connecting disparate ideas—the messy, human stuff that happens before the artifact is created. When we outsource the initial synthesis to an algorithm, are we inserting a dangerous layer of abstraction between ourselves and our users?
The risk is that we stop wrestling with the raw data and instead become expert ‘prompt managers,’ directing AI without internalizing the nuanced, qualitative context ourselves. Our core value isn’t just producing a perfectly formatted spec; it’s the deep thinking and strategic choices behind it. We need a framework for augmenting our skills with AI, not replacing them.
How are you integrating AI tools into your process while ensuring you don’t lose that essential, human-centric intuition that defines great product leadership?