About / Radical Transparency

LLM Watch is accountability journalism for AI — not generic aggregation. We cover the gap between demos, capital narratives, and what builders and workers can actually verify.

Mission

Hold the AI industry to numbers, documents, and methods. If a claim cannot survive a source trail, it does not lead the homepage.

Content pillars

• News digests — daily “N biggest stories” briefs under the 60-Second / Briefing hub.

• Model Release Tracker — every major Claude/GPT/Gemini/Grok/Kimi drop gets a comparative benchmark table on the Frontier Model Release Tracker & Elo Board.

• Live data trackers — Bubble Tracker (capex vs revenue), Who’s Suing Whom, labor scorecards.

• The Weekly Take — long-form with an explicit editorial position (hub).

• Investigations — system-prompt leaks, defense/contract clauses, data-center labor (Governance Beat).

• Builder Notes — plain-language utility for people shipping product (hub).

• 60-Second — social-native scripts and vertical briefs that match the day’s digest.

How we write

Smart Brevity lead: one bold key line, a “Why it matters” beat, then tight bullets.

Semafor three-block: The News (what happened) → The View (our take) → Room for Disagreement (strongest counter-arguments).

What “Radical Transparency” means

Every article carries a byline state: Human-verified, or Human-verified / AI-assisted with an estimated human-intervention percentage. The meta fields are editorial, not decoration — they force us to say how much automation we used.

Independence

LLM Watch is an independent brand. Editorial decisions are not subordinate to vendor PR calendars. Corrections are published when we get something wrong — contact [email protected].

Publisher

LLM Watch is published by Livio Andrea Acerbo. For AI advisory, venture building, and corporate development beyond this newsroom, see Acerbo.AI or our AI strategy page.