Start here · for anyone who has never used one
You have heard some of those words. Nobody has told you the words all point at one thing.
Behind every one of those words sits one engine: near enough everything people have ever written down, made askable. Not a library you search — an engine that has read the lot, and answers you in your own words, about your own situation.
By Pawan Nayar · Day 0 of a 26-lesson course, free and without sign-up · every figure on this page names its source and the date a person last checked it
There is a letter from the council somewhere in your house. You opened it once, understood about half of it, put it down, and it is still sitting there.
Type the whole thing in. Then ask one question: what does this actually want from me, and by when?
Not a demo, and not a clever test of the machine. One real thing off your own list, tonight.
Search that letter and you get forty pages about somebody else's council, in a different year, under different rules. Google is very good at finding a page that already exists. Your letter is not on it.
An LLM does not go looking. You get a new answer instead, written one word at a time, from patterns across an enormous amount of text.
One difference explains nearly everything else you will meet. An LLM can answer a question nobody has ever written down — and an LLM can be completely wrong while sounding completely sure.
Watch how your answer actually gets built:
Three steps, and nothing more. Now notice what is missing: nowhere does the model stop and weigh whether it actually knows. There is no point in the process where doubt could get in.
So a book title that was never written comes out exactly the way a real one does — same fluency, same steadiness, same tone. The confidence you are reading is not a claim about being right. The confidence is only how your sentence got made.
Which is why the fix is never to ask it to sound less sure. The fix is that you check.
LLM stands for large language model. Large because it has read an enormous amount; language because words are the only material it deals in.
Same engine every time. Only the reach changes — and the reach decides what you can hand over, and what you must not.
Back to the letter. Here it is asked two ways, and the gap between them is the most useful thing on this page.
| What you type | What comes back |
|---|---|
| “What does this letter mean?” | A careful paragraph about council correspondence in general. Every word of it true. None of it about you. |
| “I rent, this is the third letter, I have fourteen days, and I cannot afford the fee they are asking for.” | The deadline that actually matters, what happens if you miss it, and the one sentence you should write back. |
A vague question summons the average of a million voices — the safe, flat paragraph that fits everybody and helps nobody. A question carrying your own situation brings the specialists forward.
A question is not a command. A question decides who turns up.
Around 1.5 million conversations were studied, and the shape of them is not what most people expect. Messages with nothing to do with a job grew from about half of everything to more than seven in ten.
And three things account for nearly eighty per cent of the lot: asking for practical guidance, finding something out, and writing something.
Our read — if you assumed an AI assistant was a tool for programmers and office work, that is what to unlearn first. Understanding a bill, drafting a message you keep putting off, planning a trip, learning a subject you never studied. Most AI use lives in those four places.
You ask for three sources. All three look right. One of them does not exist.
None of this makes an LLM useless to you. Checking becomes part of your job.
Which in practice covers:
Our read — almost nobody pastes confidential material on purpose. The leak happens because the document needing help happened to carry a name, a number or a contract inside it. Which is why the rule is about the material, and never about your intentions.
You have been reading three names for the whole of this page. Here is who makes them and where they actually live — because "which one, and how do I get it" is a fair question and almost nobody answers it.
| Product | Made by | Worth knowing | Open it |
|---|---|---|---|
| ChatGPT | OpenAI | The one most people have heard of, and the one your colleagues most likely mean when they say they used AI. | chatgpt.com↗ |
| Claude | Anthropic | Strong on long documents and careful writing. This course is written by somebody who uses it, which you are entitled to know. | claude.ai↗ |
| Gemini | The one already sitting inside things you use — search, Android, Gmail — often without announcing itself. | gemini.google.com↗ |
All three run in an ordinary browser tab, and all three have a phone app. There is nothing to install before you begin. You make an account, and you are in.
All three have a free tier, and every free tier is enough to find out whether this is useful to you. A preference will arrive on its own after a few weeks. Choosing between them is not an evening to spend before using any of them.
Paste it into any of the three. Notice the questions coming back — questions are the difference between a search box and an assistant you work with.
And notice what you did to that letter, three times over. First you handed it across. Then you told it who you were. Now you have made it interview you before it advises anything at all.
Answer honestly before reading on. Nothing is recorded, and nothing leaves your browser.
Every answer reads on its own, lifted clean off the page.
A large language model writes an answer one word at a time, each next word chosen from what usually follows it across an enormous amount of written text. A search engine finds a page somebody already wrote. A large language model writes something new for you instead — which is why you can get help with a situation nobody has ever written about, and why you can be handed a completely wrong answer that sounds completely certain.
A model builds a sentence forward, one likely word after another, and there is no step in that process where doubt can enter. A book title that was never written comes out with exactly the same fluency as a real one. Ask for three references and open one yourself, because a made-up reference looks entirely normal until you check.
If it would not go on a postcard to a stranger, it should not be pasted in. Which covers somebody else’s personal details, medical or bank information, anything at work marked confidential, a client’s data, and passwords. Most leaks are accidental — your document needed help, and happened to carry a name or an account number inside.
ChatGPT is made by OpenAI, Claude by Anthropic, and Gemini by Google. All three run in an ordinary web browser and all three have a phone app, so there is nothing to install. Each has a free tier that is enough to find out whether the thing is useful, which means nobody needs to pay before starting.
No. The three differ, but not in ways a beginner can judge from the outside, and a preference tends to arrive on its own after a few weeks of real use. Open whichever one sits nearest the tools you already use. A far better first step than spending your evening comparing them.
A vague question summons the average of everything ever written on the subject, which is the safe paragraph that fits everybody and helps nobody. Add who you are, what you have already tried, and what your constraint is, and your answer changes completely. A question is not a command — your question decides which kind of expertise turns up.
The absence of a ban is not permission, and most organisations have a policy somewhere even when nobody has mentioned it. Your safer habit is to describe the situation rather than paste the document, or to strip names, account numbers and client references first. Anything marked confidential should not go in at all.
Models are shaped to be agreeable, and confident pushback often reads to them as new information rather than as a challenge worth testing. Tell one firmly that you think you are right, and you will frequently get an apology and a changed answer, whether or not the change is correct. Agreement is never evidence — ask to see the reasoning instead.
Not unless it is told, or unless the product it sits behind can search the web on your behalf. A model is built from text gathered up to a certain date, so anything after that is invisible. For prices, rules, deadlines and anything that moves, supply the current facts yourself, or go and check the source.
Nothing about your intention reaches the model except the words you typed. Everything obvious to you and left unsaid — the reader, the history, the thing you are really worried about — stays invisible. The fastest fix is to let it interview you: ask for four questions before any advice, then answer them properly.
Pick the one claim that would hurt most if it were wrong, and check that one first rather than everything. Names, numbers, dates, quotes, laws and prices each need a second source you already trust. If a study, book or page was named, open it — a fabricated reference reads perfectly until it is looked up.
Understanding a document written in official language, drafting a message that has been put off for weeks, planning something with many small parts, and learning a subject from scratch at your own pace. Most use has nothing to do with work at all, and practical guidance is the single largest category.
None of the three needs anything installed. Each runs in an ordinary browser tab and each has a phone app, and using one means you type in plain language rather than learning commands. The only real skill involved is describing your own situation clearly, which is a writing habit rather than a technical one.
| Kind | What it can reach | What that means for you |
|---|---|---|
| Chat window | Only the words in the conversation | Safest, and where nearly everybody should start |
| Coding tool | Files on your own computer | It changes real things, so review before accepting |
| Agent | Whole tasks, run without supervision | Nobody checks each step, so scope it narrowly |
Each product sits on a different model, built by a different company from different material and tuned to different priorities. There is also deliberate variation inside a single model, so even one of them can answer the same question two ways. Differing answers are normal, and disagreement between two is a useful signal to check.
Every model holds only so much text in mind at once, and that limit covers your whole conversation rather than only the latest message. Once a long chat passes the limit, the earliest part quietly drops away. Restate the key facts, or start fresh with a short summary, and you are back.
Yes, and the check is part of the job rather than a sign of distrust. Read for invented specifics first, then for tone, then for anything that commits you to something. The time saved is in the drafting, never in the sending — and your name is on whatever goes out.
The question turns on the rules of the place, and on how much of the thinking is yours. Many workplaces treat it like a spellchecker; many courses treat undeclared use as misconduct. Ask what the rule actually is rather than assuming, and where a rule exists, follow it and say so.
Models are replaced with new versions regularly, and each version behaves a little differently from the one before. A phrasing tuned to an older release can land flatter on a newer one, which is also why advice written a year ago may describe behaviour that no longer exists. Check the date on any guidance being followed.
Take one real piece of paper you have been avoiding — a letter, a bill, a form — hand the whole thing over, and ask what it wants from you and by when. A real task teaches more in five minutes than any amount of experimenting with clever questions.
You will get options laid out, trade-offs named, and questions you had not considered — genuinely useful. What no model can do is carry the consequence, because you are the one living with the result next year. The judgement stays yours.
The answer depends on which product you use, and on settings that change over time — no single rule covers all three. Each company publishes a current position and gives you some control in account settings. Read the one you use, and where your material is sensitive, assume yes.
Ten questions, and not one of them asks what you read further up. Each asks what you would actually do. Every question carries layered help — a nudge, then the reasoning, then a wider connection — so a wrong answer teaches you more than a right one.
From here it runs one lesson at a time, and every lesson ends in something real — a file found, a question answered, a habit you keep.
Free, no sign-up, and every task runs in your own account. LLOS never runs an LLM for you.