tl;dr: AI vendors (Google, Anthropic, OpenAI, Cursor) have shifted from outcome-based claims like Copilot's "55% faster task completion" to unfalsifiable volume metrics like "% of code written by AI" — essentially lines-of-code with better marketing. Meanwhile, actual outcome research is messy: some studies show gains, others show slowdowns or worse code comprehension, and ~90% of firms report no measurable productivity impact. The author argues adoption metrics are being used to justify layoffs and budget decisions that should rely on battle-tested measures like DORA, reliability, and revenue instead.