Jake Lawrence · AI Adoption / Change Management / Training Design · AI Systems theme
Six stages of getting a team to use AI well, each tied to work on this site you can open: find the real work, set guardrails, teach until you are not needed, build what people adopt, check the output, and make it stick.
A field guide to AI enablement written from implementation practice rather than vendor slides. Buying an AI tool is the easy part; the work is getting people who never asked for it to use it well, inside rules they can live with, and still using it a year later. The guide runs six stages, and each stage names what the work is and points to the place on this site where that work already exists: the court review console built around a reviewer's own checklist, a plain-language acceptable-use policy and an honest security self-assessment, a certification curriculum and a free language course, a site assistant and an exam-prep pipeline, a two-model audit of the repository's own history and in-browser benchmark checks, and a rollout story where a person signs the hard calls. Three settings reorder the same stages, because enablement inside one company, at an AI vendor, and in a public body or nonprofit start from different places. Qualitative by design: it cites only figures already published elsewhere on the site.
The acceptable-use policy is the guardrails stage of How I'd Roll Out AI, written out in full. The field guide says when the policy comes in, and the template is what you hand people on that day.
How I'd Roll Out AI makes claims about rollout, teaching and verification; the Case Study Library is where each claim is backed by the pull requests that built the work. The AI enablement lens orders the cases for that reader.
This is field data, not commentary: dated, sourced, and versioned. Subscribe and the next release, correction or new thread reaches you when it lands. It is the one list for the whole site, so you will get the rest of the work too. No schedule, easy out.
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I build the AI tools and automations a team adopts, and the full-stack apps and data pipelines under them, and ship them to production. Tell me the problem in a sentence and I'll give you an honest read on fit within a day.
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