The Craft
How to actually work with these tools — prompting, agents, automations, and the honest cases where reaching for AI costs you.
Every other part of this site tells you what is happening. This one is about what to do with the tools yourself — because the most common outcome of learning how AI works is not avoiding it. It is using it badly, confidently, and without noticing.
The three things this section teaches
Context beats phrasing
The industry called it "prompt engineering" and the name did damage, because it implied secret words. A model fills every gap you leave with the average of everything it has seen — so the work is supplying the specifics only you have, not hunting for magic formulas.
Techniques tied to one model's quirks expire at the next release. This does not.
Keep the judgement, hand over the labour
Decide before you start which part of the work is the part you are for — the position, the recommendation, the thing you would defend in a meeting.
If you cannot explain why an output is right, you have not done the work. You have forwarded it.
Verification is the whole job now
These systems produce confident, fluent text whether or not the claim underneath is true, and fluency carries no information about accuracy. That single fact converts "using AI well" from a prompting skill into a checking discipline.
Where to start
If you read one page here, read how to ask AI well — seven habits that survive model releases. Then when not to use AI, which is the page nobody writes, and using AI at work if a job is involved.
This site is written by someone who uses these tools every working day, including on parts of this site, and says so on every relevant page. That is not a disclaimer bolted on at the end — it is why this section can be specific.
The people best placed to say where a tool fails are the ones using it constantly, and almost none of them write it down.