The pressure is on. Every team, from startup to enterprise, is scrambling to integrate AI into their product. But in our rush to ship “AI-powered” features, are we missing the bigger opportunity? There’s a crucial distinction between using AI to build the product and using AI to build the product right.
The former can easily turn us into high-speed feature factories, churning out solutions that are technologically impressive but disconnected from real user needs. The latter, however, is where AI becomes a PM’s superpower. Imagine using AI to instantly synthesize thousands of pieces of user feedback, identify emerging themes from support tickets, or analyze user session recordings to pinpoint friction points. This is about augmenting our core competency: deep user understanding.
Instead of just asking “What can we build with AI?”, we should be asking, “How can AI help us make better decisions?” By focusing on tools that enhance our research and discovery process, we can ensure we’re not just building faster, but building smarter. Platforms like https://leera.io are already exploring this space, helping teams get to the core of user needs by analyzing qualitative data at scale. This lets us spend less time on manual synthesis and more time on high-level strategy.
So, how is your team approaching this? Are you focused on shipping AI features, or are you using AI to fundamentally improve your product discovery and decision-making process?