[catcam]

Thanks! To put some numbers behind the motivation:

  Rough Fermi estimate of global impact if this became standard practice:

  Assumptions:
  - ~1B AI queries/day touch technical docs (Copilot, ChatGPT, enterprise agents, CI/CD pipelines)
  - HADS reduces tokens read per query from ~5k to ~1.5k via manifest + targeted block reading (70% reduction)
  - ~0.003 Wh per 1k tokens for GPT-4 class inference (per published ML efficiency research)
  - ~2 min saved per query from more precise first answers

  Results:
  - ~3.8 TWh electricity saved/year (~350k US homes, or ~20% of Google's annual data center consumption)
  - ~12B developer hours recovered/year
  - ~$60B/year in productivity at 10% adoption

  These are intentionally rough — could be 10x off in either direction. The point is that documentation structure is
  economically material at scale, not just an ergonomics concern.

  Full writeup with methodology:
  https://medium.com/@catcam_46604/ai-is-now-the-primary-reader-of-your-docs-nobody-told-your-docs-5f7103ea3281