Picture two plumbers, both using the same AI tool on the same Tuesday morning, both typing pretty much the same request: “write a follow-up text for a customer who hasn’t paid their invoice.” The first gets back three stiff paragraphs about “maintaining positive customer relationships” that read like they were written for nobody in particular, because they were. The second gets back four short lines that sound exactly like something he’d actually send: firm, polite, mentions the invoice number, gives a ten-day window, ready to copy straight into a text message. Same tool, same rough question, wildly different result. The only thing that changed is how each of them asked. That’s the whole skill in this guide. Not a trick, not a plugin, just a handful of habits that turn “AI gave me some rubbish” into “AI just wrote that for me in twenty seconds, and it’s actually good.”

Say exactly what you want

Most disappointing AI answers trace back to the same root cause: the request was vague, so the answer came back vague to match it. Type “write something for my Instagram” and you’ll get five hundred generic words that could belong to any small business in the country, because that is genuinely all the AI has to go on. It isn’t being lazy. It’s answering the question you actually asked, not the one you had in your head.

Compare that with: “Write a two-line Instagram caption for a photo of a finished oak staircase. Casual tone, one relevant emoji, no hashtags, end with ‘message us for a quote’.” That isn’t a harder question. It just closes off the guessing. Length, format, tone, what to leave out, all decided by you instead of invented on the fly.

This matters more once money is involved. A landscaper asking for “a quote email” leaves the AI to guess the price, the timeline and what’s included. A landscaper asking for “a quote email for a 40 square metre patio, £3,200 including materials, work starting the week of the 3rd and taking four to five days” gets a draft worth sending, because there was nothing left to make up.

Show it what “good” looks like

If you want AI writing to actually sound like you, the single best fix is embarrassingly simple: paste in something you’ve already written and ask it to match that. A cafe owner who wants a specials board written in her own voice doesn’t need to explain what her voice is. She copies in three old descriptions, pastes them into the chat, and says “write three new ones in this exact style.” The AI now has something real to copy instead of a vague brief to interpret, and the result stops sounding like a stock photo of a business.

The same trick works for anything you send regularly. A bathroom fitter chasing a supplier over a late delivery can paste in a firm-but-friendly email he sent last month and ask for a new one “in this tone, about this order.” It costs thirty seconds, and it’s one of the most reliable ways to stop AI writing sounding like AI writing.

Tell it who to be

One sentence at the start of your request, naming the job it should do, changes the whole answer. “You are an experienced electrician talking to a nervous first-time customer about a full rewire” gets a calmer, more reassuring reply than no instruction at all. “You are a hard-nosed accounts manager chasing a six-week-late invoice” gets something with a bit more spine. Same underlying question, but naming the role sharpens both the tone and the judgement behind the answer.

You don’t need to overthink it. A joiner asking for help pricing a built-in wardrobe could simply add “you’re a joiner with twenty years of experience quoting bespoke furniture” before the actual question. One line, and the answer stops sounding like a call centre script and starts sounding like a tradesperson who knows the job.

Break big jobs into stages

Ask an AI for one enormous thing in a single message, a full kitchen renovation proposal, a whole year of social posts, a complete staff handbook, and you’ll usually get something shallow that tries to cover everything and does none of it well. Big jobs get better when you split them into stages, the same way you’d never quote a full extension off one glance at a photo.

A joiner putting together a proposal for a fitted office might ask for the materials list first, check it, then ask for the timeline, check that, then ask for both to be pulled into one client-ready document. Each step is small enough to review properly, so mistakes get caught early instead of buried in six pages you skim and send anyway.

Talk to it like a new team member, not a vending machine

The first answer you get is a draft, not a finished job, and it helps to treat it that way. If a junior member of staff handed you a first attempt at a customer email, you wouldn’t bin it and start again. You’d say “good start, make it shorter” or “a bit warmer” or “add our opening hours at the end.” AI takes that kind of feedback just as well, in the same conversation, without you having to explain the whole job from scratch again.

A dog groomer who gets back a slightly stiff email announcing a price rise doesn’t need to write her own version instead. “Same message, warmer, and cut it by half” usually gets there in one more go. A vending machine only gives you what you put the money in for. A conversation gets you closer with every reply.

Let it ask you questions first

For anything with a few moving parts, it’s worth handing back some control. Add a line like “before you write this, ask me anything you need to know first” and the AI will often surface gaps you hadn’t thought to fill in yourself. A kitchen fitter pricing a large extension might get asked about skip access, whether the customer is living in the house during the work, or what happens if the plaster underneath turns out to be in poor condition. Those are exactly the questions a good quote depends on, and it’s far better to answer them before the draft than to correct a wrong assumption after.

It feels backwards at first, letting the AI interview you. But a few clarifying questions up front usually save a full rewrite later, and they often catch details you’d forgotten yourself.

Check everything before it goes out the door

None of the above matters if you skip this part. AI can sound completely certain while being completely wrong, and it’s worst with the details that matter most: prices, dates, regulations, measurements, anything with a number attached. It will state a VAT rate or a building regulation with total confidence and no flag that it might be out of date or simply invented.

So the rule is a simple one: nothing AI has drafted goes to a customer, into an invoice, or onto a public page until a person has checked the facts in it. Not the tone, the facts. A window fitter who lets an AI-drafted quote go out with a made-up lead time is heading for an awkward phone call in a fortnight. Treat every AI draft the way you’d treat a quote scribbled by a new apprentice: probably fine, definitely worth a second look before it leaves the building.

Where to take this next

Everything above is a habit, not a piece of software, and habits stick better with practice than with theory. Our course, Writing prompts that work, walks through all of it step by step with real examples you can copy and adapt for your own business.

If you’d rather build a prompt right now, our free Prompt Builder tool walks you through the same structure, context, specifics, role and all, and hands you a finished prompt ready to paste into any AI tool.

And if you’d like to see this done live, in a room, with people who write prompts for a living, that’s exactly what our AI Automation Masterclass in Manchester is for. Tickets are normally £20. This one’s free, a limited-time offer to launch the series.