You want to understand AI. Let's start.

From the basics to everyday use, from work to advanced tools.

Start from zero I already know a bit, skip ahead

Where do you start?

Fundamentals

What an AI is, how to talk to it, what you can (and cannot) expect. For people who have never used one.

Everyday use

Writing better, summarizing documents, organizing information, learning new things.

At work

Bringing AI into your job: document drafts, prepping a meeting, research, the AI as a colleague that helps you think.

For students

Studying hard topics, exam prep, writing essays. AI as a tutor that explains until it clicks, without doing the work for you.

For teachers

Lesson planning, tailored materials, grading. AI as a classroom helper, not a replacement.

For people who want more

Advanced tools, automations, integrations. For when the basics are not enough.

About Privacy Open manual, written by a real person, in collaboration with AI.

AI-Guide

A free, bilingual (English and Italian) manual that teaches non-technical readers how to use conversational AI well, from the very first question through everyday productivity, work scenarios, and advanced topics. Audience: parents, teachers, professionals, students. Not engineers.

The canonical site is https://ai-guide.larosa.work. English is the default locale (`/en/`); every page is mirrored in Italian at the same path under `/it/`. URL slugs are identical across languages so any English URL below can be translated by replacing `/en/` with `/it/`.

Start here

Start here: Pick the path that fits your level. Get to where you need to go in the fastest way.

Fundamentals

But what is AI?: Let's demystify the words "artificial intelligence". What it really is, what it isn't, why everyone is talking about it now.
What is a prompt?: The word "prompt" explained without fluff. It's what you write to the AI to get an answer, and how you write it matters more than you'd think.
Your first conversation: Open an AI and put what you've read into practice. No theory: a guided exercise for your first conversation.
How does the AI "understand"?: A look behind the scenes. The AI doesn't really understand: it guesses the next word, one at a time. But it guesses so well that sometimes it feels like magic.
When to trust it (and when not): The AI is wrong with the same confidence as when it's right. Learning to recognize the cases and to verify is the difference between using it well and getting fooled.
What you share when you use AI: What actually happens to your messages after you send them to ChatGPT or Claude? Who sees them, what stays, what you can control. And what you should never put in.

Everyday use

Ask well: Four levers that make the difference between a vague answer and a useful one when you ask the AI.
Photos, images, and files: Uploading a utility bill, a screenshot, a PDF. Modern AIs can see, and you can use that to read the world around you.
Iterate the conversation: The first answer is rarely the right one. The move isn't rewriting from scratch, it's keeping the chat going.
Learn something new: The AI as a personal tutor. Techniques to actually understand, not just get a reply.
Summarize a long document: PDFs, articles, reports, books. How to ask for a summary that's actually useful, and how to know if you can trust it.
Understanding something complicated: Bills, contracts, medical reports, regulations. The AI is an excellent translator of bureaucratese, if you use it well.
Things NOT to do: AI helps with almost everything. But there are cases where delegating the decision is a bad idea, even when the answer looks right.
Write better: The AI as editor on your draft, not as ghostwriter. Three patterns to use it without losing your voice.

At work

AI as a thinking partner: Stress-test an idea before you propose it, anticipate objections, brainstorm with method. Without an explicit constraint AI confirms everything: the value comes from forcing it into discomfort.
Company data and privacy: Whatever you paste into a public AI can leave your company. Three risk levels (red, yellow, green), what changes with Enterprise or Team plans, the NDA gut check, and what to do if your company has no policy yet.
Working with data and tables: Cleaning messy data, Excel or Sheets formulas you can't remember, small analyses on extracts. AI is the right copilot for one-offs, but company data is still company data.
Drafting professional documents: Proposals, briefs, reports. AI as a structured first draft, not as a ghostwriter who writes the whole thing.
Hard emails: Saying no, responding to someone who messed up, giving delicate feedback. Where the wrong word costs.
Preparing a meeting: Structured agenda, preparation brief, actionable extract, follow-up. AI works before and after; the meeting stays the human moment.
Research for work: Mapping a new territory, synthesizing multiple sources, doing live research with citations. AI speeds you up a lot and hallucinates a lot, and method is what separates a solid deliverable from an embarrassing one.
Reuse context with projects: Claude Projects, ChatGPT Custom GPTs, Gemini Gems: same mechanism, three different names. You load once the context that recurs (who you are, what you do, how you write, reference files) and reuse it across every chat in that thread, instead of starting from scratch every time.
Slides and presentations: Outline from a document, tight bullets, speaker notes. AI helps with content, not design; the default produces text-heavy slides, and that's the risk to neutralize.

For students

Ethics of studying: Eight lessons in, the question that closes the module: where does AI's help end and copying begin? The answer is a method of judgement.
Notes from lectures and long texts: Audio transcription, slides, chapters, your own notes. How to compose course material into a study-ready form.
Revise before an exam: Simulated oral exams, written tests with corrections, mind maps and flashcards. AI as a simulated professor that generates the pressure of the test.
Sources and citations: The bibliography is where AI does the most damage in academic work. Telling a made-up citation from a real one is a skill you can learn.
Study a new topic: Formal study against a fixed syllabus. AI as a tutor that stays within your textbook's frame, not one that drifts off.
Translating and comparing texts: Translation is where AI looks perfect and can instead be sneaky. Use it as a study aid for the language, not as a translator you paste from.
When AI tricks you: You're studying a topic for the first time, and the AI answers with confidence. How to notice it's wrong precisely when you can't know.
Writing a thesis: A thesis isn't something you delegate. AI as a second reader that helps you build a months-long project without writing it for you.

Reference

Glossary: The technical words you meet in the lessons, explained in two sentences. With a button to ask your AI to go deeper.
About: AI-Guide is written by Fabrizio La Rosa. Here's what I do, where I come from, and why I decided to write this manual.

Translations

The same manual is available in Italian at https://ai-guide.larosa.work/it/. Every English page has an Italian counterpart at the same path; replace `/en/` with `/it/` in any URL above to get the Italian version.

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