Tag
Verifying AI output
Checking what AI tools produce before you rely on it: failure patterns, review tiers, and tests. 6 guides use this tag, newest first.
AI Meeting Summaries at Work: Record, Prompt, Check, Retain
A workflow for team AI note-takers: when not to record, what to tell people, a summary prompt that quotes the transcript, a 5-minute check, and retention rules.
Using AI to Write Internal Documentation Without Making It Worse
Use the four Diátaxis types to decide what each internal doc is for, give AI only jobs it can source, then review and assign an owner so pages stay true.
How to Check AI Output Before You Trust It: A Risk-Tiered Method
Sort AI output into low, medium or high stakes, then run the matching checks for facts, numbers, code, summaries and translations, with a log template.
How to Learn With AI Without Fooling Yourself
AI explanations feel like learning even when they aren't. See what 2025–2026 trials found, plus seven copyable study prompts and a weekly loop to follow.
How to Write Reusable Prompt Templates, With Five to Copy
Build prompt templates that behave the same way twice: six parts, safe variables, fixture tests, versioning, and five complete templates you can paste.
How to Build a Prompt Library Your Team Will Actually Use
Turn a shared prompt doc into a library your team opens: variable templates, a sample entry with test fields, a research playbook, and a re-check routine.