A better ChatGPT prompt is usually the same request with three things added: what you actually want, the shape of the answer, and the context the model can’t see. You don’t need a framework with an acronym. You need to stop skipping the parts you already know matter.
Most weak prompts aren’t wrong — they’re vague. The model fills the gaps with the most average guess, and you get an average answer. Here are the four fixes that close most of that gap, in the order they matter.
1. Lead with the request, not the backstory
Put the thing you want in the first sentence. Models weight the start of your message heavily, and so do you when you re-read it. If the ask is buried under three lines of context, both of you lose the thread.
Instead of "I’ve been working on a launch email and I have a few ideas but I’m not sure about the tone and…", open with "Write a 120-word launch email for a paid Chrome extension." Then add the context underneath. The request comes first; the setup supports it.
2. Name the output you want
Tell the model the format before it picks one for you. "Give me five bullet points", "return a two-column table", "answer in under 200 words", "output valid JSON with keys title and body". Format is the single highest-leverage word you can add to a prompt, because it removes the guess that wastes the most re-runs.
This is also the fix people skip most. It feels obvious once written down, and it’s the first thing missing when a prompt returns a wall of text you didn’t want.
3. Give it the context it can’t guess
The model doesn’t know who the answer is for, what you’ve already tried, or the constraint that rules out the obvious option. Say it. "For a non-technical founder", "we’re on a free tier so no paid APIs", "I already tried X and it broke because Y". Each line removes a whole category of wrong answer.
A quick test: read your prompt as if you were a competent stranger. If a smart person couldn’t do the task from your words alone, the model can’t either.
4. Show one example when the format matters
When you want a specific style or structure, one example beats a paragraph of description. Paste a good answer and say "match this format". This is the fastest way to get consistent output for anything you’ll ask repeatedly — commit messages, product descriptions, support replies.
| Weak prompt | What’s missing | Stronger version |
|---|---|---|
| Help me write a cover letter | Role, job, length, tone | Write a 200-word cover letter for a junior data-analyst role at a fintech startup. Confident, not corporate. |
| Summarize this article | Length, format, audience | Summarize this article in five bullets for someone who hasn’t read it. One sentence each. |
| Fix my code | Language, error, what you tried | This Python function throws a KeyError on empty input. Here’s the code and the traceback. What’s wrong and how do I fix it? |
Why the first prompt is usually the worst one
Under time pressure, everyone sends the half-formed version first, reads a mediocre answer, then spends three more messages fixing what they should have said upfront. The knowledge isn’t the problem. The moment is — nothing catches the gap while the prompt is still yours to change.
That’s the entire reason BeforePrompt exists: it reads your draft as you type and flags the one or two fixes that matter before you hit send, not after the bad answer comes back. But the habits above work with or without it. Start with format and context; you’ll feel the difference on the next prompt.