How I work with AI

Fifty-three distinct applications across commercial, legal, product, operational and personal work - mapped to the stage of work each belongs to, and the role AI plays in it.

The individual uses matter less than the shape. AI is present at every stage of how work actually moves - from the first discovery conversation to the institutional record that outlives the project - and its role changes at each one. Adviser here, maker there, verifier somewhere else. Underneath runs a set of practices that govern all of it, including the decision not to automate.

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Role

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The practices underneath

These apply at every stage rather than sitting at one. They are what makes the rest defensible - and the last of them is the one most easily forgotten.

What proficiency actually looks like

A useful way to read everything above. Most discussion of AI skill stops at the first two rungs, which is why "AI proficient" has stopped meaning very much.

  1. Answer retrievalDefinitions, summaries, direct answers.
  2. Guided explanationSimplification, examples, follow-up questions.
  3. Dialogic learningExplaining concepts back, inviting correction, testing understanding against scenarios and edge cases.
  4. Workflow designA source-grounded, repeatable process: progress tracking, practice generation, assessment, categorisation, targeted remediation.
  5. System stewardshipEvaluating the limits of the workflow itself, establishing verification controls, improving it on performance evidence, and adapting it for other people and for organisational capability building.
AI proficiency is not demonstrated by accepting answers more quickly. It is demonstrated by designing interactions that improve the quality of human understanding, judgement and performance - while preserving traceability, verification and human accountability.

Outside work

Included because the practice is continuous rather than switched on at the office, and because some of it is where the methods were first tested.