Research notes.
What we're reading in the AI-integration field, what we make of it, and how it changes how we run engagements. Selected, not periodic.
Each note cites the primary source. The full bibliography is at Sources.
Reaction · October 13, 2026
The AI backlash is mostly a rollout backlash
Glassdoor's analysis of US employer reviews finds AI mentions up 240% in a year and now mostly negative. Job loss is one complaint in five. The rest is about how AI was put in front of people, which is the part an employer controls.
Read the noteReaction · October 5, 2026
The most popular AI use cases are rarely the ones that pay back
Gartner's September survey of 1,303 leaders found only 22% have scaled AI, and the use cases leaders pursue most are rarely the ones reporting the best returns. We read it as an argument for choosing from the workflow.
Read the noteReaction · May 19, 2026
Anthropic's 4D AI Fluency model — what it gets right, and where it stops
The 4D model captures the cognitive shift behind effective AI use better than most. The piece it doesn't address is what happens when a fluent individual sits inside an organization that hasn't done the adoption work.
Read the noteSynthesis · May 19, 2026
What Brynjolfsson 2025 means for who you train first
The empirics on who actually gains from AI assistance are sharper than the conventional pilot heuristic admits, and they argue for sequencing training the opposite of how most rollouts approach it.
Read the notePosition · May 19, 2026
Why we don't pilot with the most senior team
The conventional advice is to start AI pilots with the most senior cohort to build executive buy-in. The data says that cohort gains the least from AI assistance. We do the opposite.
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We publish selectively, not periodically. The simplest way to follow the work is the discovery call — it lets us tailor what we send.