The featured note
Making AI recommendations reviewable before people act
A public-safe applied study on turning AI recommendations into reviewable human action.
Read the noteA personal notebook on technology, trust, and the way we work.
The featured note
A public-safe applied study on turning AI recommendations into reviewable human action.
Read the note16 articles
A product framing tool for AI recommendations where model output needs to become human-reviewed action.
A public-safe applied study on platform adoption, builder friction, safe defaults, and self-service product paths.
A product framing tool for internal platforms where adoption depends on making the official path easier than the workaround.
A public-safe applied study on making risk signals understandable, proportionate, and embedded into a financial decision workflow.
A public-safe applied study on turning post-visit instructions into clear, safe, and trackable next actions.
A public-safe applied study on exception-based coordination for healthcare follow-up workflows.
A public-safe applied study on turning financial risk signals into reviewable, routable, and closable work.
A framework for connecting user trust, risk signals, safeguards, workflow friction, review paths, and measurable outcomes.
A framework for connecting patient clarity, care-team workflow, safeguards, adoption friction, and measurement.
A model for clarifying model output, user decision, failure risk, explanation needs, review points, and governance requirements.
How an internal platform becomes useful only when builders can adopt it without fighting the workflow.
How digital services reduce everyday friction when product decisions are grounded in real workflows.
How governance, risk, compliance, and trust requirements can become useful workflows instead of late-stage friction.
Internal platforms only work when the people expected to use them can see a better path than their workaround.
A staged model for moving teams from manual workarounds to governed adoption and a scaled platform ecosystem.
A model for connecting technology capability to workflow change, adoption behavior, operational metrics, and business outcomes.
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