Your team probably already uses it. Maybe you tried Claude once, got a good answer, and moved on. That's fine. But if you want it to really help you get more done, it helps to know what it's actually doing. Not because it's complicated. Because knowing this is what makes the difference between people who poke at it and people who get real work out of it.
Let's clear up the confusion.
The simple version
Claude is a kind of program called an LLM. That stands for Large Language Model. Here's all it really does: it guesses the next word, over and over, based on patterns it learned from reading huge amounts of text.
It is not looking facts up in a database. It is not thinking like a person. Think of it like the autocomplete on your phone — but much, much better at it.
What happens when you type something
When you type a question, Claude doesn't look anything up. It was trained by reading a giant pile of text: books, articles, emails, code, conversations. While reading all of that, it learned patterns — which words tend to come after other words, how ideas fit together, what a clear answer looks like.
When you hit send, it uses those patterns to pick the next word. Then the next one. Then the next. Each word it writes helps it choose the one after it.
This is why Claude is good at things like:
- Summarizing. Paste in a long email chain and ask for the short version. It has seen thousands of summaries, so it knows the shape of a good one.
- Matching a style. Ask for a memo that sounds formal, or friendly, or short and punchy. It learned those styles and can copy them.
- Connecting ideas. It can spot how two things relate and explain the link.
- Working through steps. Ask it to do the math or walk through a problem one step at a time, and it can.
What Claude needs your help with
-
Knowing what's happening right now. Claude doesn't know today's date or this month's numbers unless you tell it. It can search the web if you ask, so for recent news or prices, tell it to look it up.
-
Getting facts exactly right. If you ask it to "name a study that proves X" with nothing to look at, it might make one up that sounds real but isn't. The fix is easy: give it the source, ask it to search, or check anything that really matters.
-
Saying when it's not sure. By default, Claude often sounds confident even when it isn't. But if you ask "how sure are you?" or "what might you have wrong?", it will tell you.
-
Knowing things only you know. It can't know your private files or last week's meeting. You have to give it that.
So here's the pattern: Claude is great at writing, thinking, and connecting ideas. But for exact facts — especially recent ones — you need to give it the information or tell it to look it up.
What this means at your desk
-
Be specific. "Look at our growth" is too vague. "Here are our sales for the last 18 months — what's the trend, and where might we hit trouble?" gives it something real to work with.
-
Use it for first drafts and thinking, not final numbers. It's a fast helper. You're the check. You catch the mistakes.
-
Show it your own work. The more examples of your writing and your style you give it, the better it sounds like you.
-
When facts matter, give it the facts. Numbers, recent news, sources — hand them over or tell it to search. Don't trust its memory alone.
-
Treat it like a smart coworker, not a search engine. Ask it to poke holes in your plan or suggest other options. It's great at that.
-
Trust it most where it's strongest. Writing, drafts, and working through business problems are safe bets. New or very specialized topics are where you double-check.
The one thing to remember
Claude writes the most likely next words. "Likely" and "correct" are not the same thing. A clear, confident explanation of something wrong sounds just like a clear, confident explanation of something right.
That's why it can sound so sure even when it's wrong. Sounding confident is just its style — it's not proof. The answer isn't to distrust it. It's to know when to check.
Most people who get real value from AI figure this out in the first month: treat it like a coworker who knows a lot but can be confidently wrong about details. A great thinking partner — not a know-it-all. Give it sources when facts matter, and let it run free when they don't.
Try it yourself
Open Claude. Type: "Explain what an LLM is to me like I'm a smart manager who never studied computers."
Read the answer. Notice which examples stick. Then ask: "What's one thing I probably still don't understand?" Watch how it handles not being sure. That's your starting point.
What's next
You've got the basic idea. Next question: how do you get real value out of something that's great with patterns but needs checking on facts?
Lesson 2 makes it practical. It's the difference between just asking Claude a question and actually prompting it. The way you set it up matters more than you'd think.