Field Notes

What operators saw after launch (reporting, not an in-house lab)

DeploymentField Notes

EU AI Act transparency war room runs while high-risk clock moves to 2027

Digital Omnibus (EU) 2026/1744 in force 27 July; Article 50 transparency from 2 August; Annex III high-risk deferred to 2 December 2027.

TLDR

Regulation (EU) 2026/1744, the Digital Omnibus on AI, entered into force 27 July 2026 and deferred most Annex III high-risk obligations to 2 December 2027 while Article 50 transparency duties applied from 2 August 2026. Providers of legacy generative systems gain until 2 December 2026 for Article 50(2) machine-readable marking only. Operators report standing up transparency war rooms separate from delayed conformity-assessment programs. Named enterprise fine counts are UNKNOWN.

Work & moneyField Notes

McKinsey skill-partnership math reframes headcount fights as workflow redesign

MGI report: ~57% of US work hours theoretically automatable today — a capability ceiling, not a job-loss forecast; April 2026 podcast walks the partnership frame.

TLDR

McKinsey Global Institute estimates currently demonstrated technologies could in theory automate activities accounting for about 57 percent of US work hours — roughly 44 percent via agents and 13 percent via robots — while stressing this is technical potential, not a job-loss forecast. More than 70 percent of in-demand skills appear in both automatable and non-automatable work. The McKinsey Podcast episode published 30 April 2026 discusses human–agent hybrid teams. Named customer reorg outcomes are UNKNOWN.

Agents & softwareField Notes

Vertex Gen AI eval pipeline replaces RAG demo scorecards

Google’s Vertex evaluation service and EvalTask score retrieval and generation separately; model-based rubrics replace hallway comparisons.

TLDR

Google Cloud documents a Gen AI evaluation service on Vertex AI: generate answers for a prompt set, score them with named rubrics, and log runs in Vertex AI Experiments. For RAG, operators use EvalTask datasets with prompt and response columns, then batch jobs for large golden sets. Groundedness and answer-quality metrics replace anecdotal pilots. Named customer before/after scores are UNKNOWN.

DeploymentField Notes

Copilot agents split on declarative vs custom engine before Control System gates

Microsoft docs: declarative agents inherit M365 compliance; custom engine agents bring your own orchestrator and hosting bill.

TLDR

Microsoft documents two Copilot agent paths — declarative agents using Copilot's orchestrator and models, and custom engine agents with external hosting — plus a Copilot Control System with security, management, and measurement pillars. Operators report choosing declarative for Graph-scoped Q&A and routing complex workflows to custom engines only after governance review. Named customer agent counts are UNKNOWN.