Artificial Intelligence, in plain English.
Practical AI for operators: what AI and generative AI are, how language models work, prompting and context, verifying output, hallucinations, handling sensitive data, and organizing work across sessions.
For: Learning practical AI
What is artificial intelligence?
Artificial intelligence is software that performs tasks normally associated with human reasoning — recognizing patterns,…
What is generative AI?
Generative AI is AI that produces new content — text, images, code, and more — based on patterns it learned. Chat assist…
How do large language models work?
A large language model (LLM) is trained on huge amounts of text to predict likely continuations of language. From that, …
How do I prompt AI effectively?
Give the AI a clear objective, useful context, and explicit constraints. State what you want, why, for whom, and in what…
How much context should I give AI?
Give enough context that the AI doesn't have to guess what matters — the goal, the audience, relevant background, and co…
What is the difference between custom instructions and project instructions?
Custom (or global) instructions apply to all your AI conversations — your general preferences. Project instructions appl…
How do I verify AI output?
Treat AI output as a draft to check, not a final answer. Confirm facts against reliable sources, test anything operation…
What are AI hallucinations?
A hallucination is when an AI produces information that sounds confident and plausible but is actually inaccurate or inv…
How should sensitive information be handled with AI?
Avoid putting secrets, personal data, or confidential business information into AI tools unless you know how that data i…
How do I organize files and hand off between AI sessions?
Keep a short written summary of goals, decisions, and current state so you can resume or hand off cleanly. Because most …