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Alpha
Becoming an AI Power User
A principle-first guide to building an AI practice that compounds. Power users build compounding loops: they experiment at the frontier, reject weak output, diagnose failures, meta-prompt improvements, save reusable assets, evaluate with clear standards, and retest as models change. This book teaches the durable principles through practical projects: quality ratcheting, meta-prompting, error-to-spec transformation, context engineering, experimentation as R&D, evaluation loops, separation of concerns, source verification, portable infrastructure, creative building, judgment preservation, and workflow redesign.
38 chapters
Editorial: Draft
