AI workflow · decision guide · miniclass
Use a simple table to see whether to use AI, how to use it, and where to stop — then turn the lesson into next steps for your own situation.
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Fresh notes
A longer source list does not make AI research complete. Define the decision, candidate cap, required evidence, stop rule, and parking lot before adjacent questions consume the deliverable.
Availability lookup, event drafting, and sending an invitation are separate actions. Keep an AI scheduler at proposal until a person approves the exact organizer, guests, time zone, and notification scope.
Addresses, deadlines, and consent need maintained systems of record—not just AI memory. Fetch and compare the current value immediately before an action, then bind approval to that exact result.
When AI revisions drift, replace vague adjectives with one observable difference, a frozen baseline, and a clear stopping rule.
A blank spreadsheet cell may mean unanswered, not applicable, or lost in import—not numeric zero. Define missingness and the denominator before asking AI for a summary.
AI daily briefs can rank calendar events, incoming requests, and generated suggestions together. Label source and commitment state before deciding what belongs in today's work.
Let AI find likely duplicate and stale cloud files, but separate inventory, human approval, quarantine, and a restore drill. Permanent deletion is a different decision.
Before an AI note-taker joins a meeting, define what it may capture, who can stop it, who receives the notes, and where every artifact will live.
Before launching an automated search, define the baseline, score, hard constraints, stopping rule, and human who owns the release decision.
Use a constrained AI patch as a price check, then assess generation, review, and six-month ownership separately before choosing ship, revise, or stop.
Use exploitation, reachability, exposure, impact, and asset context to set vulnerability urgency, then assess test, validation, scope, and rollback readiness as a separate human-controlled decision.
Map every identity handoff in an AI agent’s call chain. Exchange tokens for each downstream API, preserve user and agent identities, and reject mismatched audiences or excessive scopes.