AI's biggest gap in scientific discovery isn't search or execution—it's the ability to recognize structural inadequacy in existing frameworks and find solutions through conceptual insight rather than brute-force optimization.
This paper argues that AI in scientific discovery requires three layers: searching existing knowledge, forming new models through structural insight, and executing solutions. The key innovation is Layer 2—recognizing when current frameworks are inadequate and finding solutions by understanding what's missing conceptually, not through trial-and-error.