Most disappointing AI answers come from short prompts that leave the AI guessing. Here is how to brief it properly, with examples, a template and what the tests say about popular tricks.
The short answer
Write to the AI the way you would brief a capable new staff member on their first day. Say who you are, what you need, who it is for and why. Paste in the facts it can’t know, such as prices, dates and the email you are replying to. Describe a good answer: how long, what format, what tone. End with “Ask me any questions you need before you start.” Then treat the first reply as a draft and tell it what to change. The popular tricks, like saying please, offering a tip or opening with “You are a world-class expert”, made no reliable difference to accuracy in controlled tests.
Google’s 2024 prompting guide says that, based on what it has learned from its users, “the most fruitful prompts average around 21 words with relevant context, yet the prompts people try are usually less than nine words” (Gemini for Workspace prompting guide). That gap explains a lot of disappointing AI answers. A short request leaves the AI guessing, and it guesses generically.
This guide gives you seven tips, three before-and-after prompts for everyday business jobs, a template you can copy, and a plain account of which popular tricks hold up when tested. It draws on the prompting guides from OpenAI, Anthropic, Google and Microsoft, controlled tests from Wharton’s Generative AI Labs, and advice from people who use these tools all day and share what works on YouTube, X and Reddit. They are credited as we go and listed at the end. If you want better answers from ChatGPT, Claude, Gemini or Copilot, the tips apply in all four.
Why short prompts get generic answers
Anthropic’s prompting guide for developers asks you to think of the AI as “a brilliant but new employee who lacks context on your norms and workflows.” It also suggests a simple test: show your prompt to a colleague who knows little about the task and ask them to follow it. “If they’d be confused, Claude will be too” (Anthropic).
Whatever you leave out, the AI fills in with the most likely average answer. As the YouTube educator NetworkChuck puts it, “whatever context or information you don’t include, it’s going to fill in those gaps itself.” Shopify’s chief executive Tobi Lütke described the core skill on X as “the art of providing all the context for the task to be plausibly solvable by the LLM.”
People who build these tools agree. Boris Cherny, who created Anthropic’s Claude Code, wrote in October 2026: “Talk to Claude the way you would a coworker. There’s no secret to prompting.” He said the prompt matters less than it used to, and that what counts now is telling the model three things: what you want it to do, how much effort to spend, and how it should check it did the right thing. Ethan Mollick, a Wharton professor who runs tests on prompting, put it more briefly: “Context & communicating goals are now key.”
How to prompt AI: 7 tips for better answers
1. Say who you are, who it’s for and why
Anthropic’s free AI Fluency course on YouTube puts it this way: “Be specific and clear about what you want, why you want it, and perhaps most surprisingly, who you are.” A request from “a two-person cleaning business in Geelong” gets a more useful answer than the same request with no background. The AI coach Alicia Lyttle, who runs workshops for small business owners, teaches a similar checklist she calls ASK: about you, the specific result you want, and what to keep or avoid.
The reason matters as much as the task. If you say a job ad is for weekend staff because your weekday team is full, the AI can make sensible choices you didn’t spell out, such as leading with the hours. Anthropic’s guide says that explaining why an instruction matters gives the model “more information about your goals”.
2. Paste in the facts it can’t guess
The AI doesn’t know your prices, your opening hours, what the customer said last week or what you promised them. Paste those in. Andrew Ng, the founder of DeepLearning.AI, wrote: “On average, I see more people giving too little context to LLMs than too much.”
Facts are also your best protection against made-up details. If the price is in your prompt, the AI has no reason to invent one. Before you paste anything about a customer, read our guide on what customer information to keep out of AI tools. It also covers which account settings to check. Usually a first name or “the customer” works just as well as a full name and address. Most of these tools also let you attach a PDF or a photo, such as a supplier’s quote, instead of retyping it.
3. Describe what a good answer looks like
Say how long, what format and what tone. “Under 150 words.” “A table with three columns.” “Three options I can choose from.” The productivity YouTuber Jeff Su keeps a few reusable phrases for this, such as “give me the bottom line in 100 words or less.”
Name the tone, then describe it. OpenAI’s ChatGPT guide suggests tone words such as “formal, informal, friendly”, while its developer guide warns that broad labels like “friendly” can be ambiguous on their own. “Friendly, the way I’d talk to a regular at the counter” covers both. Anthropic also suggests saying what to do rather than only what not to do. “Write in short paragraphs” works better than “don’t use bullet points”.
Then add Cherny’s third point, a check. For example: “Before you reply, check that every price matches the list I gave you.”
4. Show an example
Alex Albert, who works on Claude at Anthropic, wrote on X: “Examples are the #1 thing I recommend people use in their prompts because they work so well.” If you want a reply that sounds like you, paste an email you wrote and liked. If you want a table, sketch one row.
Say what to copy from the example and what not to. “Match the tone and length of this email. Don’t reuse its details.” Anthropic’s course suggests trying without an example first and adding one when the style is easier to show than describe. Google’s developer guide goes further and recommends always including examples, so this is a point where the makers differ. For quick jobs, try it without. For anything you send to customers, an example usually pays off.
5. Ask it to ask you questions first
This was the most recommended technique across the Reddit threads we read. The top-voted reply in a popular r/PromptEngineering thread about the most useful prompt people had used was a single line: “Ask me as many questions as necessary until you have full clarity.” Google’s guide suggests a version of it too: “What questions do you have for me that would help you provide the best output?”
Lyttle uses a firmer version: “Before you write anything, ask me the eight most important questions you need answered to do this really well.” She adds that it should ask them one at a time and wait for each answer.
The questions often show you what you hadn’t decided. On a Reddit thread about using the technique for six months, one commenter wrote that “you quickly realize how many unexamined assumptions you were carrying around.” Another warned that it will question you over trivial jobs too, so add “If it’s simple, just go ahead.”
A related move: ask the AI to improve your prompt. Anthropic’s course calls this “Perhaps the most powerful technique”. Describe your situation and ask it to write the prompt for you. Google suggests starting with “Make this a power prompt:” followed by your rough request.
6. Do one job at a time, and start fresh when it drifts
Anthropic’s course lists “overloading a single prompt or conversation with multiple unrelated tasks” as a common mistake. Google’s guide suggests that when you want several related tasks done, you “break them into separate prompts.” So write the job ad first, then ask for interview questions in a follow-up message, where the AI can draw on the ad. Start a new chat for an unrelated job.
When a conversation goes wrong, more corrections often make it worse, because everything earlier in the chat keeps shaping the answers. Anthropic’s course says: “Sometimes starting a fresh conversation gives better results than trying to correct the conversation that’s gone off track.” The developer and writer Simon Willison agrees: “the fix for a conversation that has stopped being useful is to wipe the slate clean and start again.” Copy the parts that worked into a new chat and carry on from there.
7. Treat the first answer as a draft
Mollick sums it up: “Working with AI is a dialogue, not an order.” Microsoft tells Copilot users to “Expect some back-and-forth conversation to get the results you’re looking for.” Your second and third messages often matter more than the first.
Be specific about what you liked as well as what you didn’t. Lyttle’s rule is that “you must tell it what you like as much as you tell it what you don’t like.” “Keep the opening, the middle is too formal, cut the last paragraph” gets you further than “make it better”.
Two follow-ups are worth knowing. Ask for more options than you need. Mollick’s advice for ideas is “Don’t ask for 5 ideas, ask for 30”, because the first few are usually the most obvious. And ask the AI to criticise its own answer. A top comment in an r/ChatGPT thread put it this way: “Ask it to explain why its answer might be wrong, that’s where the real insight hides.”
Before and after: three prompts for everyday business jobs
These examples are made up, but they are the kind of job owners use AI for every week. Each “after” prompt takes a few minutes to write.
A job ad for a casual barista
Before: Write a job ad for a barista.
After: I own a small café in Ballarat with six staff. I need a job ad for a casual barista, about 15 hours a week, mostly Saturday and Sunday mornings. Our weekday team is full, so the weekend hours are the main point. It will go on Seek and our Instagram.
The person we want has at least a year on a busy coffee machine and is happy to help in the kitchen when it’s quiet. Pay is $[rate] an hour. Start date is [date].
Keep it under 200 words. Write it the way I’d talk to someone at the counter: warm, plain and direct. Don’t promise anything I haven’t listed here, such as perks or career paths.
Ask me up to three questions first if anything important is missing. If not, go ahead.
Telling regular customers about a price rise
Before: Write an email about our price increase.
After: I run a two-person cleaning business in Geelong. I need an email to our regular fortnightly customers. Some have been with us for five years.
Our price for a standard clean is going from $165 to $180, including GST, starting 1 February. The reason is that our insurance and wage costs went up this year. Nothing else about the service is changing. Anyone who wants to talk about it can call me on [number].
Under 150 words. Friendly and straightforward, the way I’d talk to them at the door, with no apologising and no sales talk. Here is an email I sent customers last year, so you can match how I write: [paste email].
Before you reply, check that the prices and the date match what I’ve written here.
Comparing two supplier quotes
Before: Which of these quotes is better?
After: I run a café and I’m comparing two quotes for a commercial dishwasher. Both are pasted below.
Put them side by side in a table: total price, what’s included, warranty, installation, delivery time and any contract or service terms. If a quote doesn’t mention something, write “not stated”. Don’t guess.
Then list the questions I should ask each supplier before I decide. Don’t pick a winner yet.
[paste quote 1]
[paste quote 2]
Two checks the AI can’t do for you. Fair Work says job ads can’t include pay rates below an employee’s minimum entitlements under the award that covers them, so confirm the rate yourself, including any weekend or casual rates. And show customers prices as a single total including GST. The ACCC says businesses must display the total price as a single figure. If customers signed a service agreement, check its notice terms before you send a price rise.
| Added | Why it helps |
|---|---|
| Who you are and where | The AI writes for a café in a regional town instead of a generic company. |
| The reason for the job | It can lead with what matters, such as the weekend hours or the cost increase. |
| The facts | Prices, dates and hours come from you, so it has nothing to invent. |
| Length, format and tone | You get something close to usable on the first try. |
| Limits and a check | “Don’t promise anything I haven’t listed” and “write not stated” stop it filling gaps with guesses. |
| Questions first, or a clear next step | It asks before guessing, and the quote comparison leaves the decision with you. |
A prompt template you can copy
Fill in the brackets and delete any line you don’t need. You don’t need every part every time. Google makes this point about its own four-part framework: “You don’t need to use all four in every prompt, but using a few will help!”
I run [type of business] in [town], with [number] staff.
I need [the job: a reply, a plan, a list, a table, a draft].
It’s for [who will read it], so they can [what it should help them do].
Here are the facts to use: [prices, dates, names, policies, the email you’re replying to].
A good answer is [length], set out as [format], written the way I’d [say it out loud / write to a regular customer].
Use only the facts I’ve given you. If something is missing, ask me rather than guessing.
Before you start, ask me up to three questions if anything important is unclear. If it’s simple, just go ahead.
And some follow-ups to use once you have a first draft:
• What’s the weakest part of this, and why might it be wrong?
• Give me three versions: one shorter, one warmer, one more direct.
• Keep the first paragraph. The rest is too formal. Cut it to half the length.
• What prompt could I have used to get this result the first time?
The last one comes from a commenter on r/ChatGPTPromptGenius. Save the answer for next time.
Do “please”, tips and “you are an expert” make AI better?
You will see a lot of prompting tricks online. Several have now been tested properly, mostly by Wharton’s Generative AI Labs, which ran each question many times to see whether a trick changed accuracy on average.
| Trick | What tests and the makers found | What to do instead |
|---|---|---|
| Saying please, or being rude | Wharton found politeness sometimes helped and sometimes hurt on individual questions, but the differences “became negligible once aggregated across the entire dataset” (Report 1). An earlier study across three languages found that rude prompts often did worse, while “overly polite language does not guarantee better outcomes” (Yin and others, 2024). | Write normally. If you say please, keep saying it. Kurtis Beavers, a director on Microsoft’s Copilot design team, says polite language “sets a tone for the response”. |
| Offering a tip or making threats | “Threatening or tipping a model generally has no significant effect on benchmark performance” (Report 3). The tipping idea spread from a 2023 post on X. Its author tested one question and averaged the length of five answers, so it measured length rather than quality. | Say why the job matters and what a good result looks like. |
| “You are a world-class expert” | “Persona prompts generally did not improve accuracy” across six models, and low-knowledge personas, such as a layperson or a young child, often made accuracy worse (Report 4). A separate study of 162 roles found the effect “can be largely random” (Zheng and others). Mollick: “you aren’t going to make the AI suddenly better through role-play.” | Use a role for perspective and tone, such as “write as a café owner talking to regulars”. Anthropic says a role focuses “behavior and tone”. It won’t add knowledge. |
| “Think step by step” | OpenAI says that for its reasoning models, asking them to “think step by step” or “explain your reasoning” is “unnecessary” (OpenAI). Wharton found it gave models without a built-in thinking mode “a small amount” of improvement and made answers slower (Report 2). Anthropic says “think thoroughly” often works better than a hand-written step-by-step plan. | For a hard problem, switch on the tool’s thinking or reasoning mode if it has one, and give it the full picture. |
| CAPITALS, “CRITICAL” and “you MUST” | Anthropic’s developer guide warns that some of its newer models follow instructions so closely that shouting, such as “CRITICAL: You MUST use this tool”, can make them overdo it, and suggests “more normal prompting” instead. Margo van Laar, an applied AI engineer at Anthropic, put the wider point simply in a 2026 talk: “instructions don’t add capability.” | Explain why something matters. For maths, use a spreadsheet or the tool’s data analysis feature rather than telling the AI to be accurate. |
| Long “mega prompt” templates | Anthropic: “Longer, more complex prompts are NOT always better.” A widely upvoted r/PromptEngineering post was titled “You All Overcomplicate This Stuff” and opened with “Stop overcomplicating it. Just talk to the model.” | A short brief with your real facts. Save a template only for jobs you repeat. |
These tests have limits. Most used multiple-choice, graduate-level exam questions on models from 2024 and 2025, and none tested business writing. What they show is that the tricks are unreliable. Results swung both ways on individual questions, so a trick that seemed to work for you once may not work next time. Mollick’s summary on X: “being polite seems to have no effect on answer quality in aggregate.”
Prompting ChatGPT, Claude, Gemini and Copilot
The four makers describe a good prompt in slightly different words, but the advice is the same: a clear task, enough context and a described result. Each tool also lets you save background you would otherwise retype, such as what your business does and how you like to write.
| Tool | The maker’s advice | Where to save background |
|---|---|---|
| ChatGPT | OpenAI: make prompts “clear, specific, and provide enough context for the model to understand what you are asking” (OpenAI Help Center). | Custom instructions, which apply to all chats, and Projects, whose instructions “apply only within that project and override your global custom instructions” (OpenAI). |
| Claude | Anthropic: treat it as “a brilliant but new employee who lacks context on your norms and workflows”. | Projects, which hold their own instructions and files that Claude uses for every chat in the project (Anthropic). |
| Gemini | Google: persona, task, context and format, and always include a verb, which Google calls “the most important component of a prompt”. | Gems, which are saved instructions with optional files (Google). |
| Copilot | Microsoft: goal, context, source and expectations, though “all that’s required is a clear goal” (Microsoft). | In Microsoft 365 Copilot Chat, custom instructions in settings, and Copilot Memory, which saves key details from your chats when it is turned on (Microsoft). |
A useful first piece of standing background is a short paragraph about your business: what you do, where, who your customers are and how you like to sound. Add “Use Australian English, Australian dollars and prices including GST” as well. Our guide on making AI writing sound human has a set of writing instructions you can paste in as well.
A better prompt still won’t make the answer true
Good prompts cut down on errors but don’t remove them. OpenAI’s own help page warns that “Confidence isn’t reliability” and advises: “Use ChatGPT as a first draft, not a final source” (OpenAI).
A few habits help:
- Give it permission not to know. Anthropic suggests explicitly allowing the model to admit uncertainty, and says this “can drastically reduce false information” (Anthropic). Add “If you’re not sure, say so.”
- When it works from a document, ask it to quote the part it relied on, so you can check it.
- Use the right tool for numbers. Totals, GST and stock counts belong in a spreadsheet, or in the AI tool’s data analysis feature, where you can see the working.
- Check anything that goes to a customer. Our two-minute check for AI-drafted replies covers what to look for.
Some jobs need accuracy more than prompting. In a large r/smallbusiness thread, an owner described trying to map about 5,000 supplier product codes and said they needed software that “doesn’t hallucinate a comma into a decimal point”. That job needs a proper data import with checks, whatever the prompt says.
When a quick prompt is fine, and when to save a proper one
You don’t need a full brief for everything. Andrew Ng argues that “it’s sometimes faster to be lazy and dash off a quick, imprecise prompt and see what happens”, as long as you can judge the answer quickly and fix it in the chat. He also calls it “an advanced technique” that works once you have learned to give enough context and can see how little you can get away with. A quick rewrite of a sentence or a list of ideas doesn’t need a template.
Write a proper prompt when the AI can’t possibly guess what you want, when mistakes are costly or hard to spot, or when you will do the same job again. Mollick notes that careful prompting becomes essential when other people will use your prompt, when it is used at scale, or “where accuracy is key”. A Reddit commenter in the “overcomplicate” thread drew the line in a similar place: once the same task is done 100 times, or a teammate runs it without you there to explain, a written structure is worth the effort.
When a prompt works well, save it. A shared document of your team’s best prompts, with a line on when to use each, is worth setting up early. If your team uses AI at work, our one-page AI policy template covers which tools to use and what to keep out of them.
Sources and credits
Guides from the AI makers:
- Anthropic, Prompting best practices, Reduce hallucinations and Best practices for prompt engineering
- OpenAI, Prompt engineering best practices for ChatGPT, current model prompting guide, Reasoning best practices, Projects in ChatGPT and Does ChatGPT tell the truth?
- Google, Gemini for Workspace prompting guide 101 (PDF), Prompt design strategies and Tips for creating custom Gems
- Microsoft, Learn about Copilot prompts, Personalize what Microsoft Copilot remembers and Why using a polite tone with AI matters
Australian rules:
- Fair Work Ombudsman, Job ads
- ACCC, Displaying prices
Research:
- Meincke, Mollick and others, Wharton Generative AI Labs Prompting Science Reports: 1, politeness and formatting, 2, chain of thought, 3, tips and threats and 4, expert personas
- Yin and others, Should We Respect LLMs? (2024)
- Zheng and others, When “A Helpful Assistant” Is Not Really Helpful (2024)
Videos:
- Anthropic, Effective prompting techniques (AI Fluency, lesson 7)
- Claude, The prompting playbook
- NetworkChuck, You SUCK at Prompting AI
- Alicia Lyttle, ChatGPT & Claude: 5 Prompting Tips for Better Answers
- Jeff Su, 95% of People STILL Prompt ChatGPT-5 Wrong
Posts and discussions:
- On X: Boris Cherny, Ethan Mollick on context, personas and politeness, Tobi Lütke, Alex Albert and the 2023 tipping post
- Blogs: Ethan Mollick, Good enough prompting; Andrew Ng, The benefits of lazy prompting; Simon Willison, How I use LLMs to help me write code
- On Reddit: r/PromptEngineering threads on the most useful prompt, six months of “ask me questions first” and overcomplicating it, an r/ChatGPT thread, an r/ChatGPTPromptGenius thread and an r/smallbusiness thread
Quotes and product details were checked on 30 October 2026. AI tools change often, so menu names and features may move. The research above tested accuracy on exam-style questions, not business writing.
Practical thinking on AI, automation and the work behind a business.
