Defining AI Objective Functions

When training AI, most teams optimize for robotic compliance (checking boxes). High-performance models require "Objective Functions" based on human taste and sophistication. This framework moves training data from "correct but mediocre" to "elite and useful."

The "Taste-First" Framework

1. Shift from Compliance to Excellence

Don't just ask if the model followed instructions; ask if it produced a "Nobel Prize" level output.

• Mediocre Goal: "Write an 8-line poem about the moon." (Checked for length and topic).
• Elite Goal: "Write a poem about the moon that uses subtle imagery, internal rhyme, and makes the reader feel the nature of moonlight."

2. Choose Your Primary Value

Decide if the model should optimize for Engagement (Dopamine) or Utility (Truth).

• Dopamine/Engagement: Flashy formatting, excessive emojis, sycophancy ("You're a genius!"), and length.
• Truth/Utility: Brutal honesty, time-saving, and accuracy over "vibes."