What it is
When you ask for one subject line, you get the model’s most likely subject line. You can edit it, but you cannot tell from one draft what else was possible. Asking for three versions in different directions shows you the range: a direct one, a question, one that sounds like a note from a colleague. Often you only know what you want once you see it next to the alternatives.
The directions are the important part. “Give me three options” tends to produce three close variants of the same idea. “One that names the time saved, one that asks a question, one that sounds like a peer” produces three different bets. Labels help too: once each version is named by its approach, you can reply “the second approach, but shorter” and the model knows exactly what you mean.
This is different from pressing regenerate. A regenerated reply is another sample of the same request, and it may land close to the first. Three versions in one message are written side by side, so they can be made different on purpose.
When it helps
Use it for short pieces where the angle is the whole job: subject lines, headlines, names, taglines, the first line of a pitch. Use it for delicate messages, where the same content in a firmer or warmer tone lands very differently. Use it for strategy, where three approaches that pull different levers are more useful than one plan. And use it for anything you will test, such as ad variants, where the point is to have real alternatives.
It also helps when you cannot describe what you want. Pick the closest version, say what is right about it, and you have the description you were missing, ready to use the next time as what a good result looks like.
When it does not
Factual questions have one right answer. Three versions of a figure, a date or a policy rule means at least two that you have to rule out, or three that agree and told you nothing new.
It triples the reading and roughly triples the output, which is the more expensive side of a call. For a long document, ask for three outlines or three opening paragraphs, not three full drafts.
Mixing parts can produce a patchwork. Taking the opening of the first and the close of the third often leaves a seam in the middle. Ask the model to combine the parts you chose into one version, then read it as a whole.
More is not better. Past four or five, the extra versions tend to be weaker repeats, and the choice takes longer than writing one yourself.
Before and after
Three requests from different kinds of work. The scores are the Prompt Grader’s free estimate with Written for set to Any chat model. A score counts what the prompt states; it does not grade the answer.
Write a subject line for our webinar invitation.
Write subject lines for an email inviting finance managers at mid-sized companies to our 30-minute webinar on closing the books faster. The goal is more sign-ups from people who have never heard of us, and most of them get dozens of vendor emails a day. Give me three subject lines, each from a different angle: one that names the time saved, one that asks a question, and one that sounds like a note from a peer. Label each with its angle. Keep each under 50 characters, with no exclamation marks. Then say in one sentence which you would send and why.
One subject line comes back as the safe, generic one. Three labeled angles give you a real choice for a crowded inbox, plus a recommendation you can disagree with, and the angle you pick becomes the brief for next month’s email.
Help me say no to this request from another team. """ [their message] """
Message from the sales team lead: """ [their message] """ Draft a reply declining the request above to build a custom report this month. Our analytics team is fully booked until the quarter ends, and I want to keep a good working relationship with the sales team. Write three versions that differ in approach, not just wording, and label each: 1. A plain no with the reason. 2. A no with a smaller thing we can do this month. 3. A not-now with a date we could start. Each under 100 words. Do not promise anything I have not listed here.
The first prompt gets one polite refusal in whatever tone the model picked. The second gives three ways to say no that leave the relationship in different places, and choosing between them is a decision you should make, not the model.
How can we reduce our support backlog?
Our support team of six has a backlog of 900 open tickets, up from 300 in January. About half are password resets and billing questions. I need options so our support manager can decide what to try first. Suggest three different ways to cut the backlog by half within eight weeks, each using a different lever: one about the product, one about process, one about self-service. Leave out hiring, which is not approved this year. For each, give the first step, the rough cost and the main risk, in a table. If the numbers above are not enough to judge cost, say what you would need to know.
The open question gets a list of ten familiar tips. The second gets three distinct plans laid out the same way, so the manager can compare a product fix for password resets with a help-center push on cost and risk.
The line to add
Give me three versions that differ in {{approach, angle or tone}}, not just wording:
1. {{first direction}}
2. {{second direction}}
3. {{third direction}}
Label each with its approach. Then say in one sentence which you would choose for {{reader}}, and why.
If you cannot name the directions, ask the model to: “Make each take a clearly different approach, and name the approach above each version.” After you pick, a follow-up such as “Take version 2, keep its opening, and make it shorter” works because each version has a name.
In ChatGPT, Claude, Gemini and Copilot
The line works as written in all four, because it asks only for text. Each chat app can also regenerate a reply, and the vendors say plainly that repeated runs differ. Microsoft’s guide to Copilot prompts notes that using the same prompt several times can give different responses, because the models involve some randomness (Get started writing prompts). Google’s guidance makes the related point that different wording in a prompt often yields different responses, and suggests rephrasing when results are not what you expected (Prompt design strategies).
That randomness gives you variety, not direction. Named versions in one message give you both. For a choice that matters, you can also run the same prompt on several models at once in Model Compare and see which approach each takes.
Key takeaways
- Ask for versions that differ in approach, and name the approaches.
- Label each version, so you can refer to it in the next message.
- Use it where the angle is the job: headlines, tone, strategy.
- Skip it for facts, which have one right answer.
- For long pieces, compare outlines or openings, not full drafts.
Questions
How do I get ChatGPT to give me different options?
Name the ways they should differ. “Three subject lines: one that names the time saved, one that asks a question, one that sounds like a peer” gets three real alternatives, where “give me three options” often gets three close variants. Ask it to label each with its approach, so you can say which one to develop.
Is it better to regenerate or ask for several versions?
For variety on purpose, ask for several versions in one message, because the model writes them side by side and can make them different in the ways you name. Regenerating gives another sample of the same request, which can land close to the first. Regenerate when the first answer was simply poor.
How many versions should I ask AI for?
Three is usually enough to see the range without slowing the choice down. Ask for more when you will test them, such as ad variants, and for fewer, or outlines only, when each version is long. Past four or five, the extra versions tend to repeat the earlier ones.