Why AI coding sessions need written architecture decisions to prevent silent drift

Software engineer Derek Wang argues that decisions made during AI-assisted coding sessions are effectively lost once a chat context window closes, as the model starts each new session without memory of prior choices. Without a written record, teams face three compounding problems: the AI silently re-argues settled questions, code gradually deviates from intended design, and the same debates are repeated across sessions with potentially contradictory outcomes. Wang points to Architecture Decision Records (ADRs) — short written files documenting what was decided and why — as the solution, noting they have been a trusted engineering practice for decades. In the AI era, he contends, such records become structurally essential rather than merely good practice, because a language model reads files literally and cannot fill gaps with judgment the way a human engineer might. His core principle is that a decision only becomes real and enforceable once it is written in a file that every future session, human or AI, is required to read.