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beginnerAI

AI Basics (Level I)

What an AI assistant is actually good for, where it will let you down, and how to use it on real work without getting burned.

41 lessons8 sections
Need to Know HQPractical engineering courses, written by people who ship
$14.99
  • Buy once, yours for good
  • 41 lessons across 8 sections
  • Progress tracking across devices

What you'll learn

  • Know which of your Tuesday tasks an assistant is genuinely good at
  • Recognise the four ways it goes wrong, and check for them before you send anything
  • Ask for what you want and get it first time instead of on the fourth attempt
  • Understand what changes when an assistant is connected to your files, mail and tickets
  • Know what is safe to paste at work, and what to check before you do

Course content

8 sections · 41 lessons

What this thing actually isThree short lessons to replace whatever impression you have picked up from headlines, plus a practice set.4 lessons
  • What you are actually talking toFree preview2m
    Read this lesson

    The one-sentence version

    It is an assistant you talk to in writing, which is extremely good at working with language — reading it, rewriting it, summarising it, drafting it — and which has read an enormous amount of text.

    Three things it is not

    • Not a search engine. A search engine finds documents that exist. This produces text that reads well. Those are different jobs, and confusing them is the source of most bad experiences.
    • Not a database. It does not "look up" your customer record. It has no record of anything unless someone put it in front of it.
    • Not a person. No memory of you between conversations, no judgement about consequences, no stake in being right.

    What that means practically

    It is superb at the part of your job that is moving language around — and useless at the part that requires knowing a fact nobody has told it. Almost everything in this course is a consequence of that one split.

    The question you actually came with

    Is it coming for my job?

    The honest answer is that nobody credible knows, and anyone giving you a percentage is making it up. What we can say from watching this thing work:

    • It is good at the parts of a job that involve producing text, and bad at the parts that involve knowing what is true, deciding what matters, and being accountable.
    • The tasks it does well are usually the ones you least enjoy — the first draft, the summary, the reformatting, the "can you write this up".
    • The people getting the most out of it are not the ones who trust it most. They are the ones who know precisely what it is bad at, which is the entire third section of this course.

    Treat it as a fast, tireless, slightly unreliable assistant who has read everything and remembers nothing. That framing will serve you better than either the hype or the panic.

  • What "it predicts the next word" means for you2m
  • The chat window and "the API"2m
  • Practice: what kind of tool is this?9m
What it is genuinely good atSeven kinds of real work, with what you give it, what comes back, and what a good result actually looks like. This is the section to steal from.8 lessons
  • Summarising something long2m
  • Rewriting: the blunt email and the exec summaryFree preview3m
    Read this lesson

    The highest-value thing in this course for most people, and the one that pays for itself the first week.

    The blunt email

    You have written what you actually think:

    Mark — this is the third time your team has missed the cutoff. We can't keep
    rebuilding the report because someone couldn't be bothered to submit on time.
    I need this fixed, not explained again.

    Send that and you have a different problem tomorrow. The ask:

    Rewrite this so it stays firm about the deadline and the impact, but is something I can send to a peer in another department without it becoming an HR conversation. Keep it short. Do not add pleasantries I did not write.

    What comes back:

    Hi Mark,
    
    The submission deadline was missed again this month, which meant rebuilding
    the report after the cutoff. That's the third time this quarter and it's
    costing us most of a day each time.
    
    Can we agree a way to make the deadline stick — either an earlier internal
    cutoff on your side or a reminder from us the day before? Happy to do
    whichever is easier for your team.
    
    Thanks,

    Same message. Same firmness. No incident.

    The exec summary

    The opposite direction. You have four paragraphs of accurate technical detail, and your director will read the first two lines.

    Below is my write-up of the outage. Turn it into three sentences for a director who does not know what a load balancer is: what broke, what the impact on customers was, and what stops it happening again. No jargon. Do not use the word "mitigation".

    Why this works so well

    You supply all the facts. It supplies the register. There is nothing for it to invent, which removes the main failure mode entirely.

    The one check that matters

    Read it for meaning drift. Rewriting occasionally softens a commitment into something stronger or weaker than you meant — "we will fix this by Friday" appearing where you wrote "we're looking at it". Read the rewrite as if you were the recipient, and specifically look for promises you did not make.

  • Drafting the first version2m
  • Pulling structure out of mess2m
  • Explaining something unfamiliar2m
  • Comparing two documents2m
  • Rough notes into a clean write-up2m
  • Practice: good job, or bad job?10m
What it is bad at, and how not to get burnedFour lessons. This is the section that makes the rest of the course safe to act on.5 lessons
  • Made-up specifics, stated confidently2m
  • Arithmetic, counting, and anything that has to add up2m
  • Today's information, and things it was never told2m
  • The habit: what would I check before I send this?2m
  • Practice: spot what needs checking10m
The concepts worth holdingFive ideas that explain nearly every confusing thing an assistant does. Short lessons, and then you are done with theory.6 lessons
  • Prompt, and why the word is doing work1m
  • Context: what it can see right now2m
  • Why the same question gives two different answers1m
  • Why it forgets between conversations1m
  • Hallucination, named plainly1m
  • Practice: explain it to a colleague8m
Asking wellEverything in the last section, turned into something you can do. Three lessons and a practice set, and this is the part that changes your results tomorrow.4 lessons
  • Five things a good ask contains2m
  • One bad ask, one rewrite, both results4m
  • Fixing an answer you did not want2m
  • Practice: rewrite the ask11m
Connecting it to your actual workEverything so far assumed you paste things in. This section is about what changes when you do not have to — the shift that turns a writing tool into something that answers questions about your actual job.8 lessons
  • On its own, it only knows what you pasteFree preview2m
    Read this lesson

    The limitation you have been working around

    Every example so far had you doing the finding. You knew which contract, you went and got it, you opened it, you pasted it.

    That is fine when you know where the document is. It is useless for the question you actually have on a Tuesday, which is usually "didn't we agree something about this last year?"

    The shift

       ON ITS OWN                         CONNECTED
    
       +----------------+                 +----------------+
       |   assistant    |                 |   assistant    |
       +----------------+                 +----------------+
              ^                                  ^   |
              |                                  |   | "go and look"
        you paste in                             |   v
        everything it                     +------+----------------+
        needs to know                     |  shared drive         |
                                          |  mailbox              |
       It knows: this chat.               |  wiki / runbooks      |
       Nothing else.                      |  ticket queue         |
                                          +-----------------------+
    
                                          It knows: this chat, plus
                                          whatever it was connected to.

    What it is called

    There is a standard way of plugging systems into assistants, called the Model Context Protocol — MCP. You will hear the acronym. That is all it is: an agreed way for a company's systems to be made available to an assistant, so that every tool does not need a bespoke integration.

    You do not need to know anything else about it. What matters is what it changes, which is the rest of this section.

    The honest framing

    Nothing about the assistant gets smarter. It gets better informed, which turns out to matter far more. Every failure mode from section three — invented specifics, not knowing your policy, not knowing today — is a symptom of it having nothing in front of it.

    Connecting it is the fix for all of them at once.

  • Your files2m
  • Your email2m
  • Your documentation and runbooks2m
  • Your tickets and issue tracker2m
  • What it can reach, and what it cannot2m
  • When it can act, and what should stop it2m
  • Practice: what would connecting change?9m
Using it at work without getting in troubleThree short lessons and a practice set. Practical, not alarmist — but this is a real lesson for your role, not a footnote.4 lessons
  • What actually happens to what you paste2m
  • Personal account versus the company one2m
  • What not to paste2m
  • Practice: paste it or not?9m
Where this leaves you2 lessons
  • The whole course in one page3m
  • Where to go next

Requirements

  • You use a computer for work — email, documents, maybe a ticket queue
  • No programming, no maths, no prior AI knowledge

Description

Someone has told you the company is adopting AI. Nobody has told you what that means for your Tuesday.

This course is the missing explanation. Not how the technology works — what it is actually good at, where it will quietly let you down, and how to use it on real work without creating a problem for yourself.

Written for: someone who runs systems, lives in email and shared drives, maybe touches a ticket queue or some SQL, and knows nothing about AI beyond headlines. You are competent. You are just new to this one thing.

Not in here: maths, code, model internals, or anything you need to install. Every example is a document, a mailbox, a ticket or a report — the things actually on your desk.

Four questions we answer honestly and early: Is it going to be wrong and make me look stupid? Am I allowed to paste our contract into it? Is it reading my whole mailbox? And the one everybody actually means: is it coming for my job?

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