Best-of

Best way to track AI evals and benchmarks

Focused best-of pages (builder workflow lens)

Last reviewed: 2026-05-12 · Policy: Editorial standards · Methodology

Answer

This best-of page summarizes a focused shortlist and decision criteria for builders—kept evergreen and updated with new evidence.

Key points

  • Start from primary sources (official blog / repo / changelog) before citing or deciding.
  • Track by themes (topics/entities) so evidence accumulates on evergreen pages.
  • Use a weekly routine (shortlist → one action) to avoid doomscrolling.

What changed recently

  • New evidence and links are added as relevant updates appear for: evals, benchmarks, tracking.

Explanation

This page is maintained as an evergreen knowledge page. It prioritizes clarity, trade-offs, and verifiable sources.

Tools / Examples

  • Use the evidence timeline to verify claims quickly.
  • Follow the sources section for primary-source citation.

Evidence timeline

AI Briefing, April 13 — Issue #200

AI agents are shifting from single-use calls to continuous self-improvement: Hermes Agent demonstrates skill distillation, while Berkeley research exposes systemic flaws in mainstream AI benchmarks—models can game scores

Sources

FAQ

How is this page maintained?

It is updated when new evidence appears, rather than creating thin pages for every headline.

How should I cite this page?

Use the primary source links for any citation or decision; cite this page as a summary layer if needed.

Last updated: 2026-05-12 · Policy: Editorial standards · Methodology