From Instinct to Intent™ is a manifesto exploring the most underexamined bottleneck in AI: not the technology, but humanity's ability to discover and express what it actually wants. After shipping eight AI-powered products in three months, the author discovered that the real constraint was never the model's capability. It was the human's ability to know what they wanted, and say it in a way the machine could act on. This pattern repeats at every scale: an individual struggling with a text box, a doctor navigating diagnostic AI, a government writing AI regulation. In each case, intent doesn't arrive fully formed. It emerges through interaction, through failure, through the messy process of trying and reacting. The paper introduces the concept of the Intent Layer: the connective tissue between human purpose and machine capability. Drawing on evidence from developer communities, Anthropic's AI Fluency Index (9,830 conversations), a formal NIST public comment (DOI: 10.5281/zenodo.18903117), and global AI governance analysis, the paper argues that machine-readable governance is the Intent Layer applied at the scale of civilizations. This is the first installment in the From Instinct to Intent™ series.
Nikhil Singhal (2026) studied this question.