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To create a high-quality AI agent of oneself, an expert can't just rely on their public work. They must manually document their nuanced style and judgment into a system of prompts and triggers. This shifts the burden of creating a good AI product from the platform to the creator, asking them to codify their intuition.
The transformative power of AI agents is unlocked by professionals with deep domain knowledge who can craft highly specific, iterative prompts and integrate the agent into a valid workflow. The technology itself does not compensate for a lack of expertise or flawed underlying processes.
Developing a high-quality AI skill, like an "Ad Optimizer," is not as simple as writing a single prompt. It requires a laborious, iterative cycle of instructing, testing, analyzing poor outputs, and refining the instructions—much like training a human employee. This effort will become a key differentiator.
AI tools rarely produce perfect results initially. The user's critical role is to serve as a creative director, not just an operator. This means iteratively refining prompts, demanding better scripts, and correcting logical flaws in the output to avoid generic, low-quality content.
As AI democratizes the technical aspects of content creation, the ability to guide it with unique perspective, craft, and taste becomes the key differentiator. AI is a powerful tool for experts to scale their vision, but it cannot replace the vision itself.
Building an AI application is becoming trivial and fast ("under 10 minutes"). The true differentiator and the most difficult part is embedding deep domain knowledge into the prompts. The AI needs to be taught *what* to look for, which requires human expertise in that specific field.
'Taste' is a collection of specific preferences, not an abstract feeling. Document what makes an output 'good' by creating universal rules (e.g., 'write at a ninth-grade level,' 'avoid cheesy quotes,' 'no em dashes'). Feeding these documented rules to an AI transforms your subjective taste into repeatable instructions for consistent results.
The concept of "taste" is demystified as the crucial human act of defining boundaries for what is good or right. An LLM, having seen everything, lacks opinion. Without a human specifying these constraints, AI will only produce generic, undesirable output—or "AI slop." The creator's opinion is the essential ingredient.
The best AI models are trained on data that reflects deep, subjective qualities—not just simple criteria. This "taste" is a key differentiator, influencing everything from code generation to creative writing, and is shaped by the values of the frontier lab.
Despite AI's ability to generate functional code, replicating the nuanced, subjective quality of a specific designer's "taste" remains extremely difficult. Felix Lee, after spending weeks attempting to codify his own taste into an AI model with little success, notes it's a significant unsolved challenge.
Treat AI skills not just as prompts, but as instruction manuals embodying deep domain expertise. An expert can 'download their brain' into a skill, providing the final 10-20% of nuance that generic AI outputs lack, leading to superior results.