Don't stop at "I get it." Lock That One Job Down first
After the fundamentals, the usual trap is this: you feel like you learned a lot, then you close the laptop and your hands have nothing new to show.
So from here on, every chapter ends with a page like this. It answers one question: after this chapter, what can you actually do today.
Most people hand AI a task and stop at step one: "Help me handle the weekly report." That sentence isn't wrong — it just can't be accepted. If you don't know what output counts as success, you also don't know whether to change the prompt. Push three more steps and it becomes a real requirement.
From a wish to a requirement you can accept
A wish
"Help me handle the weekly report." You have an idea. That's all it is
Lock input and output
In: a week's scattered notes. Out: three takeaways plus a next-week plan
Define what counts as right
All three sections can go straight to your boss. Not one word to rewrite
Pick a plan that holds down hallucination
If it has to cite real numbers, go RAG. Don't let it invent from memory
Why step four gets its own callout
This chapter you learned four ways to hold down hallucination: change the prompt, RAG, tune Temperature, add evals. Which one you pick depends on where your job will go wrong. This is not a four-way preference quiz. Need to cite specific numbers and clauses? Go RAG. Format keeps drifting? Change the prompt and drop Temperature. Running it long-term and afraid it'll quietly get worse? You need evals. Picking the wrong one is fine. Picking none at the start means you leave hallucination for the user to find.
This Chapter's Hands-on Checklist
0 / 3 done
Write that job in four lines
15 min EveryoneFollow the four steps above. Write down the one job you most want to hand to AI: one wish, what the input is, what the output looks like, what counts as right. Sticky note, notes app, anywhere — but it has to be written down, not just an idea in your head.
What counts as done
Try it on 5 real inputs
1 hour Want to test feasibility firstDon't use made-up examples. Dig up five real materials and throw them at it, one at a time, same prompt every time. The point is to see which kind of input makes it start making things up. How good the answers are can wait. Too long? Missing info? Internal jargon? Write down the class that fails.
What counts as done
Draw a human–AI boundary
Half a day Ready to actually build oneSplit the job into "AI does" and "you do." Write down what the handoff looks like. Example: AI drafts and flags every number it's unsure about; you only check the flagged ones. Where you draw the line matters less than this: it has to be checkable.