We’re all drowning in takes about building AI into our products. But I think the more immediate, game-changing conversation is about how we use AI to do our own jobs better. Let’s be honest, a huge chunk of our time is spent on necessary but tedious tasks: sifting through user interview transcripts, trying to spot themes in a mountain of feedback, or drafting the fifth version of a PRD.
This is where AI is starting to feel less like a feature on a roadmap and more like a co-pilot. Instead of manually tagging 500 support tickets, you can have AI surface the top 3 emerging issues. Instead of staring at a blank page, you can have it generate a first draft of user stories based on your research notes.
This isn’t about replacing strategic thinking; it’s about automating the tactical toil that gets in the way of it. For example, platforms like https://leera.io are leveraging this to help teams instantly connect qualitative user feedback to specific product priorities, freeing up PMs to focus on the ‘why’ instead of the ‘what.’ When you spend less time synthesizing and more time strategizing, you create more impact.
How are you personally using AI tools in your day-to-day product management workflow, and what has been the most surprisingly useful application you’ve found?