Most people tell an AI to “be concise” and then wonder why they still get a wall of text. The fix that works better is simple: give the model an actual number, and give it a way out when the topic really is big.
That’s the idea behind a tiny prompt line shared by u/FaithlessnessNew1824 on r/PromptEngineering. Instead of a vague adjective, they set a budget: answer in at most six sentences, and if you need more, ask first. Their outputs became readable almost overnight. It’s a small change, but it turns a fuzzy wish into a rule the model can actually follow.
The Key Idea
A length limit works when the model can measure it. A cap with an escape hatch works even better, because it stops the model from quietly ignoring the cap. Think of it like a budget at the grocery store. “Spend a reasonable amount” gets you a full cart. “Spend $50, and check with me if you need more” gets you exactly what you came for.
Old Way vs New Way
The old way: “Please be concise.”
The problem is that “concise” means nothing in particular to a model. A short answer for one topic is a long one for another. Ask for a concise explanation of how a car engine works and you might get four paragraphs. Ask for a concise answer to “what’s the capital of France” and you get one word. The model has no yardstick, so it guesses, and it usually guesses long. Worse, the guess changes from one run to the next, so you can’t even rely on the same prompt behaving the same way twice.
The new way: “Answer in at most six sentences. If you need more, ask first.”
Now there’s a number to count against. And the “ask first” clause fixes a failure mode the author called out directly. Without it, the model decides the topic is too important for your cap and sails right past it. With it, the model has a legitimate move: stop, tell you the answer needs more room, and let you decide. You stay in control of the length instead of arguing with the model about it after the fact.
Practical Steps 📏
- Pick a number. Sentences are easier to count than words, and models handle them more reliably. Six was the sweet spot for the original poster, and one commenter agreed it works well in practice. If six feels tight for your use case, try eight, but pick one number and stick with it for a few days before changing it.
- State it as a ceiling, not a target. “At most six sentences” is clearer than “around six.” A ceiling lets a simple question get a two-sentence answer, which is exactly what you want.
- Add the escape hatch. “If you need more, ask first.” This is the part that makes the limit stick. A good test is to ask something genuinely complex, like comparing three database options, and check that the model pauses to ask instead of cramming everything into one dense paragraph.
- Add a formatting guard. The author also uses “no bullet points unless I ask” so the model doesn’t turn six sentences into a nested list. Without this, some models respect the sentence count but split every sentence into its own bullet, which brings the clutter right back.
- Adjust by task. Don’t go much below the sweet spot. One commenter noted that shorter caps made the model start dropping important context. A quick summary of an email can live with three sentences. A debugging explanation probably can’t.
A Starter Template ✍️
“Answer in at most six sentences. If you need more room, tell me and ask before continuing. No bullet points unless I ask for them.”
Paste it into your system prompt or the top of a chat and see what changes. If you use custom instructions in your favorite chat app, this is a great candidate for that spot, since it applies to every conversation without you retyping it.
Why This Works
Another commenter put it well: a concrete length constraint removes ambiguity, but allowing clarification before expanding is just as important. You get short answers by default, and depth on demand. The model stops guessing what you want and starts following a rule it can check itself against. It also saves you time on the reading side. Instead of scanning a long reply to find the one useful paragraph, you get the core answer first and decide whether you want the deep dive.
Try It Today 🏴☠️
Take your most-used prompt and swap “be concise” for a real number plus the ask-first line. Run it five times and compare. Then tell me in the comments: do you give your model an exact number, or do you still just say “keep it short”? I’m curious what your sweet spot turns out to be!
Frequently Asked Questions
Q: Should you give the model an exact number or just say keep it short?
Give it an exact number. Commenters said a specific cap like six sentences works much better than a vague instruction like be concise, which the model interprets differently each time. One commenter found six to be the sweet spot, since anything shorter started dropping important context.
Q: Why add the ask first clause instead of only a hard cap?
Without it, the model tends to ignore the cap whenever it decides the topic is big. The clarification option gives it a way to handle complex questions without blowing past the budget. Another commenter pointed out that this balances short answers with enough flexibility for harder questions.
Q: Where in the prompt should the length rule go?
One commenter moved the length line to the very end of the prompt and saw better compliance, which they guessed was recency bias. That’s an anecdote, not a tested rule, so run a few prompts with the line at the end and in the middle before you commit to one spot.
the tiny length budget line i add so the model stops writing walls of text
by u/FaithlessnessNew1824 in PromptEngineering