How to Train AI to Think Like You

AI strategist Max Bernstein explains that training AI to mirror personal thought patterns requires moving beyond surface-level interviews to extract "tacit knowledge" from unscripted, real-world interactions. By analyzing transcripts from consulting sessions, brainstorming meetings, and daily voice memos, individuals can identify their unique "cognitive fingerprint"—a data-driven map of how they solve problems and make decisions. This process involves categorizing insights into four distinct layers: declarative facts, procedural steps, conditional decision criteria, and metacognitive mental models. Utilizing tools like meeting recorders to capture these authentic moments allows for the creation of a rich context file. Once integrated into AI models, this data enables the technology to replicate an individual’s specific expertise and decision-making DNA, transforming AI from a generic tool into a personalized, high-value asset that preserves and scales individual professional wisdom.