Why does schema-driven behavior fail?

The most common reason schema-driven behavior fails: Building sophisticated agents on top of unexamined schemas. You get faster at producing the wrong outputs. The agent fires with perfect reliability, but the underlying model of reality is distorted — so every reliable action takes you further from where you actually want to go. Efficiency without accuracy is just high-speed drift.

The fix: Pick one agent you already run — a repeatable behavior triggered by a specific situation. Write down the schema it operates on: what does this agent assume about the world? Then ask three questions. First, where did this assumption come from? Second, when was the last time I tested it? Third, what would change if this assumption were wrong? If you cannot answer the third question, the schema is running unchecked.

The underlying principle is straightforward: Every agent embeds assumptions about the world — the schema it uses must be accurate.