Good Taste the Only Real Moat Left

Summary

Good Taste the Only Real Moat Left AI and LLMs have changed one thing very quickly: competent output is now cheap. A landing page can be generated in minutes. A product memo can appear in a single prompt. A pitch deck can look polished before anyone has done the hard work of deciding what the company actually believes. That is why taste has become a serious topic in tech. When everyone can produce something that looks decent, the advantage shifts to judgment. The people who stand out are no longer just the ones who can produce. They are the ones who can tell what is generic, what is true, and what is worth pushing further. But there is a second point that matters just as much: taste is not the final answer. If humans reduce themselves to selecting from AI outputs, they risk becoming reviewers of a machine-led process instead of builders with real stakes in the outcome. The real opportunity in the age of AI and LLMs is not to become a better selector. It is to combine taste with context, constraints, and the willingness to build something that could not have emerged from the average alone. What taste actually means In this context, taste is not about luxury, status, or personal aesthetic branding. It is about distinction under uncertainty. Most meaningful work does not come with perfect data. You do not get a spreadsheet that tells you which sentence will make a customer care, which feature is worth a month of engineering time, or which design crosses the line from polished to forgettable. You still have to decide. Taste shows up in three places: What you notice What you reject How precisely you can explain what feels wrong That last part matters more than it first appears. Many people can say, "this feels off." Far fewer can say, "this fails because it sounds like every other SaaS product," or "this explanation collapses a regulatory constraint into marketing language and will confuse the customer." Taste becomes useful when it moves from vibe to diagnosis. Why AI a...