Original learning sequence
7 field notesMove from AI interest to one owned nonprofit decision.
Read in order or enter at the decision in front of you. Each guide stays vendor-neutral and keeps mission result, information boundary, human authority, evidence, and reversibility in view.
Start with the mission question, not the model
Turn a broad interest in AI into one bounded question that matters to people and programs.
Map data before choosing a tool
Understand what would enter, leave, persist, or influence the workflow before comparing features.
Write the human review boundary
Make it clear where AI may assist, where a person must decide, and where the workflow must stop.
Run a small evidence-first pilot
Test quality, burden, risk, and mission fit before a broad rollout or purchase commitment.
Plan for accessibility and language
Treat access, comprehension, and language quality as design requirements, not final checks.
Govern vendor and model change
Keep a useful workflow reviewable when products, models, terms, and integrations change.
Close, pause, or scale the experiment
End pilots deliberately so temporary tools and workarounds do not become invisible operating systems.