Design methodologies promise clarity, but they assume deterministic paths: if step A is done, do step B. Reality is messier. Choosing a research method, deciding prototype fidelity, or timing a stakeholder review; these decisions depend on budget cycles, political capital, evidence standards, and a dozen other variables that frameworks ignore.

This talk introduces Decision DNA: templates that encode the sophisticated variables driving specific decision types. Instead of following rigid frameworks, you map the boundaries, and let AI navigate within them based on your actual context.

You’ll learn how to build decision models that let AI adapt to your context intelligently.

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