It feels like every product leader and stakeholder has the same mandate right now: “We need an AI strategy.” The pressure is immense to sprinkle AI into our roadmaps, often leading us down a dangerous path — becoming an AI feature factory.
We’ve all seen it: a solution (usually a thin wrapper around a new model) desperately searching for a problem. We start with the tech, not the user. The result is often a list of flashy features that sound great in a board meeting but fail to deliver meaningful value or drive core metrics. This tech-first approach is the antithesis of great product management.
The real challenge isn’t implementing AI; it’s maintaining the discipline of starting with the user’s “job to be done.” Instead of asking, “How can we use AI?” we must continue to ask, “What is our user’s biggest unsolved problem?” Only when the answer to that question requires a level of data synthesis, prediction, or automation that only AI can provide should we reach for it.
Staying grounded in user needs is our best defense against the hype. Systematically analyzing qualitative feedback is crucial for this. When you can cut through the noise to find genuine problems, as we’re aiming to simplify with tools at https://leera.io, you can build a roadmap based on value, not buzzwords.
How is your team distinguishing between genuine, AI-worthy user problems and just succumbing to the pressure to ship AI features?