You Had No Taste Before AI Author: Matthew Sanabria Date: 27 July 2025 Reading time: 6 minutes --- Summary This article critiques the current discourse surrounding the concept of "taste" in the age of AI, arguing that many who urge others to develop taste when using AI have themselves lacked taste long before AI existed. The author challenges the notion that AI introduction has created issues around judgment and aesthetic quality, instead highlighting a longstanding problem of mediocrity and unrefined work. --- What is Taste? Taste is defined as critical judgment, discernment, or appreciation of aesthetic quality. In the AI context, taste entails: Contextual Appropriateness: Knowing when AI-generated content suits the situation or requires human intervention. Quality Recognition: Distinguishing between useful and poor AI output, relying on domain knowledge. Iterative Refinement: Using AI outputs as a starting point that needs further improvement. Ethical Boundaries: Avoiding unethical use of AI, like inauthentic or illegal acts. These skills are not new but fundamental and should have always been applied to creative and professional work. --- Being Tasteless The author observes many people worried about tasteless AI content themselves produce mediocre work such as: Copy-pasting code without comprehension Sending unedited resumes or emails Requesting reviews without self-review Ignoring quality issues Designing websites identical to competitors' Repeating influencer trends uncritically The issue isn't AI, but longstanding human habits of poor taste. AI merely makes this more visible due to the speed and ease of content generation. --- Spectrum of Taste Taste can be seen as a spectrum of: Depth of Taste: Expertise and refined judgment in a specific domain gained through years of experience. Breadth of Taste: Knowledge across multiple domains helping assess contextual appropriateness and overall quality. Breadth of taste is particularly valuable in AI use because AI often requires switching between different tasks and domains rapidly. Successful users of AI typically have broad taste that allows them to judge AI outputs effectively and know when to seek expert insights. --- It Tastes Bitter The author suggests that if readers feel challenged by these ideas, it is a good sign. Developing taste has always been vital and is not some mystical skill exclusive to AI times. Before and after AI, the fundamentals remain: Examine and differentiate good and bad work. Study examples of excellence. Iteratively improve your creations. Judge others' advice on taste by their history of work quality. The conclusion emphasizes that those succeeding with AI are not newly "tasty," but simply have adapted their existing taste to new tools. Developing taste is a timeless necessity, and AI is just another medium to apply it. --- Actionable Tips to Develop Taste Tomorrow: Identify one work you are proud of and one you dislike; analyze the differences. This Week: Find three excellent examples in your field and study the choices behind their quality. This Month: Iterate on your own work multiple times with specific improvements. Always: Evaluate advice on AI taste by the advisor’s pre-AI work to verify their credibility. --- Author Details Matthew Sanabria is an engineering leader known for leveraging his broad and deep experience in minimal context scenarios. He enjoys family time, supporting his wife’s chocolate business, home improvements, and technical reading. --- Additional The article includes a thematic image depicting two dogs waiting attentively behind a hand holding a corn dog—perhaps symbolizing anticipation or selective taste. Navigation links and further posts are available in the site header and footer. --- *This comprehensive reflection encourages readers not to blame AI for