The Code-Adjacent Power of AI

AI coding assistants are most commonly associated with writing code, but many of their most valuable use cases are code-adjacent: understanding legacy workflows, mining open source projects for architectural patterns, onboarding to unfamiliar codebases, decomposing large features into vertical slices, organizing TODO lists, rewriting project documentation, and generating SR&ED tax credit reports. Using Claude Code as the primary tool, the author demonstrates how AI excels at synthesizing information, translating between technical contexts, and reducing cognitive overhead — tasks that surround code rather than produce it. The key insight is that treating AI as an information processor rather than a code generator dramatically expands its practical utility.