Every project in this curriculum, from a single email to a system your whole lab relies on, runs through the same four quadrants:

You start top left. Most of the value comes from going back and forth between Structure it and Understand it: you describe the problem, explore it, learn something, and describe it better. Only when you can say what you'll try, why it fits and how you'll check it do you cross to the right-hand side. Building then teaches you more, and often sends you back to the left.

A tool is an answer to a problem you understand. It is never the starting point. "We need an AI chatbot" is a solution looking for a problem. "Customers wait two days for a delivery date" is a problem worth exploring.

In Choose tools you go down a ladder, from the simplest means to the most complex: something that already exists, a small change to it, a template or spreadsheet formula, and AI only for the part that needs it.

What you need to know about AI assistants for Understand it. Four facts decide whether an assistant can help with a task:

So assistants are strong when you can hand over the material and quickly judge the result: drafting, rewording, summarising a document you have, structuring notes, explaining something you can check. They are weak at anything they must recall (references, prices, rules), at arithmetic on your data, and at anything you can't check.

Worked example: one task, four quadrants

Here is the method on one real task, first in a lab, then in a company. Follow the one closer to your work.

Lab: the weekly journal club

Structure it. "Every Thursday I present a paper to six colleagues. Preparing the one-page handout takes me about two hours. A useful result is a handout that is accurate and gets a discussion going."

Understand it. She pastes the paper's text into the assistant and asks for a one-page summary. The summary reads well, and every number in it matches the paper, because the paper was in front of it (fact 1). But it repeats the authors' claims and misses the limitation hidden in the supplementary data. That's when she sees that writing the summary was never the hard part. The critique was. She goes back to Structure it: "A handout with a short summary plus three critical questions, and the questions are mine."

Choose tools. She goes down the ladder. Is there something that already exists? The group's old handouts give a format. Does any part need AI? Yes, the first draft of the summary. The critique stays hers. Nothing here needs an agent (an AI that carries out steps on its own) or an app.

Build it. She pastes the paper and asks for a 200-word summary in the group's format, using only the text provided. She checks every figure and sample size against the paper and writes the three questions herself. The handout is ready in under an hour. What it taught her: the next time-saver is a saved request she can reuse every week (T02-L01 · Get Answers You Can Use from a Chatbot).

Company: "When will my order ship?"

Structure it. "About fifteen customers a week email to ask when their order ships. Each reply takes me five minutes. A useful result is a correct, friendly reply in under two minutes."

Understand it. He asks the assistant to answer one of the emails. The reply is polite and gives a delivery date, which it made up (fact 1: it has no access to the order system). Looking at his own process, he sees that writing the reply was never slow. Finding the date in the order system was. Back to Structure it: "Find the date fast, then send a standard reply."

Choose tools. Going down the ladder: the order system can already filter by customer, and his mail program can store text templates. He uses the assistant once, to draft three reply templates (on time, delayed, partial delivery), because writing is where it's strong. The date comes from the system, never from the assistant.

Build it. He saves the templates, tries them on five real emails and fixes one awkward sentence. Replies now take about two minutes. What it taught him: if the volume doubles, the next step is an automation that looks up the date for him (T05-L01 · Your First Automation: Build It, Break It, Switch It Off). That's another trip around the quadrants.

Notice what happened in both cases. The first try with AI didn't give the result. It gave understanding. That's the loop working. And in the company case, the final solution uses AI for one small part only. That's Choose tools working.

What goes wrong

Starting with the tool. Symptom: "Let's use AI for this" before anyone can say what's slow or broken. Fix: write one sentence in Structure it about who needs what, and why it's hard today.

Skipping Understand it. Symptom: you build the first idea you had, and it solves a problem nobody has. Fix: spend ten minutes looking at how the task is done today and trying the simplest thing, before you decide anything.

Asking it to recall instead of work. Symptom: confident answers about "your institute's policy", a price or a reference, which turn out to be generic or invented. Fix: give it the policy, price list or paper. If you can't, it's the wrong tool for that part.

Taking fluent for checked. Symptom: you forward a well-written paragraph with a wrong name or date in it. Fix: read the result as if a new intern wrote it. The tone tells you nothing.

Building too much. Symptom: a small task turns into an app project. Fix: in Build it, make the smallest thing someone can use this week. Add more only when trying it shows you need to.

Giving up after one bad answer. Symptom: a vague result, and you decide AI can't help. Fix: check what you gave it. Add the material, the audience and an example of the result you want, and try once more.

Do it yourself (30 minutes)

1. Structure it (8 min). List ten tasks from last week that you'll do again. Pick one that takes real time or annoys you. Write it down: who it's for, what makes it hard, what a useful result looks like.
2. Understand it (10 min). How do you do it today? Try the assistant on it with real material (fact 4 first). Note what worked, what didn't, and which of the four facts explains it. Rewrite your problem sentence if you learned something.
3. Choose tools (4 min). Go down the ladder: something that already exists → a small change to it → a template, form or spreadsheet formula → AI assistance for one part. Write down your choice and one reason.
4. Build it (8 min). Make the smallest useful version and try it once, for real.

Exit check

What you hand in: one working first result for a task from your own week, plus five short lines:

• Problem: your final Structure it sentence.
• What exploring changed: what you learned in Understand it, and how it changed the problem.
• Choice: the means you chose, and why it is the simplest that works.
• Result: what you built, and whether it worked when you tried it.
• Next step: the one thing you'd improve on the next trip round the quadrants.

It passes when a colleague can read the five lines and see why you built what you built.

Rule to remember

Understand the problem well enough to build less and achieve more.

Details for experts

Checked on 23 September 2026. You don't need this to follow the book; it's for setting things up or answering a colleague.

If these details change, the rule stays the same: check the settings once, before you paste anything.

Further reading and tools

Next books

• T01-L02 · Check AI Output Before Your Team Relies on It: checking a result quickly before it leaves your desk.
• T02-L01 · Get Answers You Can Use from a Chatbot: what to put in a request so the first answer is usable.
• T01-L03 · Build the Smallest Thing Your Colleagues Can Run Without You: Choose tools in depth, from chat and automation to apps and agents.
• T12-L01 · Decide What You May Paste Into AI at Work: what you may paste, and where.

Tools

• ChatGPT, Claude, Gemini, Microsoft Copilot: Taught. Any one of them works for this book.