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Notes on making work clearer

Short, practical pieces on explainable figures, human review of AI assistance and honest demonstrations. No product claims — just how we think.

Articles

ClarityFive questions to ask of any risk numberWhere it came from, how fresh it is, how it was calculated, what it assumes and who has reviewed it.AI assistanceWhat “human review” should mean in AI-assisted workReview is a design decision, not a disclaimer. Four properties that make it real.Honest demonstrationsWhy we label synthetic dataIllustrations help people understand a workflow. Labels stop them being mistaken for results.
Two colleagues standing in a glass-walled corridor, one pointing at a wall covered in hand-drawn diagrams.
Most of the work behind a clean number happens on a wall like this one.