01
AI prompting guide: how to write prompts that stay useful
A practical system for defining the task, supplying context, controlling the output, and checking the result.
Practical prompt engineering
AI prompting guides for reliable, repeatable work.
Ten original, in-depth guides for creating, testing, organizing, and reviewing AI-assisted work—without relying on magic phrases.
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02
Context engineering: give AI the right working information
How to select, organize, label, and protect the information an AI model needs to complete a task.
03
ChatGPT vs Claude vs Gemini: choose by task, not reputation
A repeatable way to compare AI models using your own inputs, quality criteria, workflow, and risk.
04
Build a reusable prompt library for your team
How to select, document, organize, test, own, and retire prompt templates as shared work assets.
05
How to test and version important AI prompts
Build representative test cases, scoring criteria, failure rules, and a lightweight release process.
06
Use AI for SEO without creating thin, scaled content
A people-first workflow for research, briefs, original evidence, drafting, editing, and maintenance.
07
Use AI for source-grounded research and synthesis
A workflow for defining the question, selecting sources, tracing claims, handling disagreement, and reviewing conclusions.
08
Prompt AI to improve decisions without outsourcing judgment
Use models to frame choices, challenge assumptions, compare options, and design reversible experiments.
09
Responsible prompting: privacy, accuracy, fairness, and human review
Practical safeguards for using AI in everyday work without turning a prompt into a policy substitute.
10
A practical guide to multimodal prompts
How to combine text, images, documents, tables, and other inputs while keeping the task and evidence clear.