What does it mean that schema selection heuristics?

You need rules for choosing which schema to apply in a given situation.

Example: A startup founder faces a product decision. She could analyze it through a customer-jobs-to-be-done schema, a competitive-moat schema, a unit-economics schema, or a team-capacity schema. Each is valid. Each produces a different recommendation. She doesn't have time to run all four. So she asks: What is the cost of being wrong? The answer — low, because the decision is reversible — triggers a speed-over-thoroughness heuristic. She picks the customer-jobs schema because it has the shortest feedback loop for reversible product bets. She didn't pick the 'best' schema. She picked the best schema for this problem's structure.

Try this: Pick a real decision you're currently facing. List every schema (mental model, framework, lens) you could apply to it — aim for at least four. For each, write one sentence: what would this schema optimize for? Then answer three selection questions: (1) What is the cost of being wrong? (2) How fast do I need an answer? (3) Which schema have I applied most successfully to similar problems before? Use your answers to pick one schema. Write a brief note explaining why you chose it. You now have an externalized record of a schema-selection decision — the raw material for improving your selection heuristics over time.