The empty desk
The chatbot module described the context window as the desk the model works on. Most people use it with an empty desk. They type a question and receive an answer assembled from memory, which is the least reliable thing the model does. The fix is mechanical: put the material on the desk first.
This lesson is the beginner’s version of what the prompting course in this catalogue does in depth. It covers the four things that make the largest difference, and one that most people get backwards.
Give it the document
If the task is about a document, paste the document. A contract, an email thread, a page of notes, a spreadsheet exported as text, a transcript. A modern context window holds a hundred pages or more, and the model reads all of it before answering. “Summarise the attached” with the text present is a reliable task; “summarise the report on X” with nothing present is an invitation to invent a report.
The same applies to code, to a form, to a product description, to the syllabus you are asking about. If it is not on the desk, the model does not have it, however confidently it proceeds.
Give it the draft
Ask for a rewrite of something you wrote rather than a first draft from nothing. The draft carries your facts, your structure and your voice, and the model’s job becomes transformation: the reliable column from the previous lesson. A first draft from nothing is memory, and it will be generic for the reason the lesson on where the text came from explained: generic is the likeliest continuation.
Give it examples
Two or three examples of what you want are worth more than a paragraph describing it. Show it three product descriptions in your house style and ask for a fourth. Show it two emails you sent that landed well and ask for one to a new person. The model infers the pattern from the examples in the same way it learned everything else: from instances. This is called few-shot prompting and it is the single most effective technique that costs nothing to learn.
Tell it who it is for, and how long
“Explain this to a customer who has never used the product, in under a hundred words” produces something usable. “Explain this” produces the median explanation on the web, at the median length, for the median reader. The model has no idea who you are writing for unless you say, and the audience changes everything about a good answer.
Then argue with it
The first answer is a draft. Say what is wrong with it. “Too formal.” “You dropped the second point.” “Shorter, and lead with the deadline.” Each turn keeps the previous ones on the desk, so the model revises rather than starts over. Most people stop after one exchange, and most of the value is in the second and third.
The thing people get backwards
Do not ask the model for facts and then work on them. Get the facts yourself, from a source you trust, put them on the desk, and ask the model to work on them. The reason is the entire fourth module of this course: facts from memory are invented in the specifics, and once an invented specific is in the conversation, every subsequent turn treats it as true. The model is a superb writer and an unreliable witness. Use it as the first and not the second.
A worked example
Instead of: ”Write a letter to my landlord about the leak.”
Try: ”Here is the clause of my tenancy agreement about repairs. [paste] Here is the email I sent on 3 March and the reply I got. [paste] Write a firm, polite letter, under two hundred words, citing the clause, giving a deadline of fourteen days, and asking for written confirmation. Do not invent any dates or amounts that are not in the material above.”
The second version is longer to type and takes the model thirty seconds. The first produces a letter with a plausible clause number, a plausible date and a plausible deadline, none of which is yours.
What context does not fix
Putting material on the desk makes the model’s reading reliable. It does not make its judgement reliable, and it does not fix the jagged frontier. A model with your whole contract in view will still occasionally misread a clause, and it will do so fluently. The material makes checking possible; it does not make checking unnecessary.
Check your understanding
You want a summary of a twenty-page report. Which request is most likely to produce a reliable result, and why?
Pick the one you would defend. Your answer stays private.
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