Experience is usually treated as an advantage, as exemplified by Google product leader Jules Walter defining what product sense is in Lenny’s Newsletter:
Product sense is the skill of consistently being able to craft products (or make changes to existing products) that have the intended impact on their users. Product sense relies on (1) empathy to discover meaningful user needs and (2) creativity to come up with solutions that effectively address those needs.
Quoting Walter, Tanner Kohler, a researcher at Nielsen Norman Group, argues that it can become a trap when the current problem only looks familiar. He contrasts his definition of product sense with Walter’s:
Product sense is the ability to recognize when current problems match past successes or failures and reliably estimate how similar solutions will affect the desired outcomes.
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This definition improves on Walter’s because it turns product sense from a loose combination of empathy and creativity into a measurable decision-making skill. It specifies the mechanism behind strong product judgment: recognizing when a current problem resembles past successes or failures, predicting likely outcomes, and knowing when those comparisons are reliable. That makes product sense easier to recognize, practice, and improve.
Pattern recognition gets most of the credit when we talk about senior judgment. For designers, calibration means knowing when a pattern that worked before no longer fits the problem in front of you.
Kohler then limits where experience can be trusted:
Our definition requires people with strong product sense to know both when an experience-based pattern is likely to work and when it is not. That judgment is the “sense.” It is not magical, does not come automatically with time, and remains limited to a person’s domain of expertise.
Consider a fire chief experienced with small building fires advising a crew during a skyscraper fire, a NICU nurse caring for an adult patient, or a chess grandmaster playing checkers. Do the cues they learned in one domain still apply?
Daniel Kahneman and Gary Klein point out that any new decision-making environment needs to provide sufficient familiar clues for an expert to accurately match the patterns they’ve learned to the current situation.
Kohler warns that AI can also interrupt the decision–implementation–measurement–reflection loop that creates those patterns:
Buzzwords come and go. There’s nothing wrong with the term “product sense.” The problem is believing that, with little data, an ever increasing velocity, and more work and decision making outsourced to AI, people can develop a “sense” for what to do without rigorous thinking.
Intuition comes with time and repeated exposure to real product decisions and results. AI may rob you of the chance to develop product sense if you aren’t careful. Stay in the ring, own your decisions, and face the results. This is what will make you valuable for years to come.
