Ask.Show.Get.
24 August 2026 · 6 min read

How to Write a Prompt That Works on the First Try

Most bad AI output is a bad request. Four things to put in a prompt, and the one habit that fixes more answers than any clever phrasing.

People blame the model. Usually the request was the problem. You asked for "a summary" and got a summary — just not the one in your head, because the one in your head had a length, an audience, and a purpose that never made it into the message.

Here is what a prompt that lands actually contains. None of it is clever. All of it is specific.

1. The job, stated as a job

"Help me with this email" is not a job. "Rewrite this email so it fits in four sentences and does not sound annoyed" is. The difference is that the second one can be checked. If you cannot tell whether the output succeeded, the request was too vague to succeed.

A good test: could a competent stranger do this task from your description alone, without asking you a follow-up question? If not, the model has the same problem.

2. Who it is for

Audience decides vocabulary, length, and how much context to assume. "Explain our pricing change" produces something entirely different when the reader is an existing customer versus your own finance team. Say which.

3. The shape of the answer

Ask for the format you actually want: three bullets, a table with these columns, one paragraph, a numbered checklist. If you do not specify, you get the model's default, which tends to be longer and more hedged than anything you would send.

  • Length — "under 120 words", not "short".
  • Structure — bullets, table, prose, code block.
  • Tone — "plain and direct", "warm but brief".
  • What to leave out — "no preamble", "do not restate the question".

4. An example, if you have one

This is the highest-leverage thing in the list and the one people skip. Paste a version you liked — an old email, a paragraph from a doc, a competitor's page — and say "match this". One example carries more information about tone than a paragraph of adjectives ever will.

The habit that matters more than any of this

When an answer is wrong, do not argue with it. Start over.

A long back-and-forth where you keep correcting a bad first draft tends to produce a worse result than one clean second attempt, because every message you send is still attached to the flawed one. The model is working from a conversation that is mostly a record of getting it wrong.

So: read the bad output, work out which of the four things above you left out, put it in, and ask again from scratch. That single habit fixes more answers than any phrasing trick.

A worked example

Weak: "Summarise this report."

Better: "Summarise this report for our head of sales, who has not read it and has two minutes. Five bullets, under 100 words total. Lead with anything that changes what her team should do this quarter. Skip methodology."

Same model, same report. The second one is usable without editing, and it took twenty seconds longer to write.

Coursium teaches exactly this — including practice lessons where you take a weak prompt of your own and rewrite it.

Coursium

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