Why Your AI Prompts Aren't Working (And How to Fix Them)
Most people talk to AI models the way they'd text a friend who already knows the context. The model doesn't. A prompt that feels clear in your head often lands as vague instructions — and the output shows it.
Here's a short, practical guide: five techniques for writing prompts that get you better results, plus a simple way to check whether your prompts are actually working.
1. Be clear and direct
Ambiguity is the single biggest cause of bad outputs. Say exactly what you want.
❌ Bad
Summarize this.
✅ Good
Summarize the email below in 2–3 sentences. Focus on the main request and any deadline mentioned.
The bad version leaves length, focus, and style entirely to the model. The good version closes those gaps.
2. Be specific about the output
Describe the shape of what you want, not just the task.
❌ Bad
Give me some ideas for blog post titles.
✅ Good
Give me 5 blog post titles about remote work productivity. Each title should be under 10 words, use active voice, and avoid clickbait phrases like "you won't believe."
When you specify format, length, and what to avoid, you stop getting outputs you have to re-prompt three times to fix.
3. Separate your instructions from your content
When your prompt mixes instructions with content (a document, an email, some text to work with), the model can get confused about which is which. A simple fix: label them.
❌ Bad
Translate this to French: I love programming. But keep the tone casual.
(Is "But keep the tone casual" part of what to translate, or an instruction?)
✅ Good
Translate the text below to French. Keep the tone casual.
Text: "I love programming."
You can use labels like "Text:", "Email:", "Article:" — or wrap sections in tags like <email>...</email>. Either way, the model knows what's an instruction and what's raw material.
4. Show examples of what you want
Telling the model what you want is fine. Showing it is better.
❌ Bad
Classify these customer messages as positive, negative, or neutral.
✅ Good
Classify customer messages as positive, negative, or neutral. Examples: "Fast shipping, love it!" → positive "It arrived broken." → negative "Package came Tuesday." → neutral
Now classify: "Took a while but it works."
Two or three examples usually work better than two paragraphs of explanation. Include the tricky cases — that's where the model needs the most guidance.
5. Tell it what to do when it doesn't know
Models will often guess rather than admit uncertainty. If you don't want a made-up answer, say so.
❌ Bad
Based on the article below, when was the company founded?
✅ Good
Based only on the article below, when was the company founded? If the article doesn't say, reply with "Not mentioned in the article."
Small addition, huge improvement in reliability.
How to know your prompt is actually working
Writing a good prompt is half the job. Checking that it works consistently is the other half — most people skip this part and wonder why results feel hit-or-miss.
A simple check anyone can do:
1. Decide what a good answer looks like. Before testing, picture what you'd accept as correct. Specific details, specific format, specific tone.
2. Try it on 5–10 varied inputs. Easy ones, tricky ones, and at least one where the answer should be "I don't know." A prompt that works on one example but fails on the next isn't really working.
3. Run the same input twice. If you get wildly different answers each time and you need consistency, your prompt isn't specific enough yet.
For a prompt you'll use once, eyeball it. For one you'll reuse often — a template, a workflow, something you'll paste every week — keep the test examples somewhere and re-run them whenever you tweak the prompt. You'll catch problems before they waste your time.
The quick checklist
Before sending a prompt, ask:
- Have I said clearly what I want?
- Have I described the output (length, format, style)?
- Is my content separated from my instructions?
- Would an example or two help?
- Have I told it what to do when it's unsure?
Five questions. Thirty seconds. Dramatically better results.
Prompts aren't magic spells. They're instructions — and like any instructions, the clearer and more specific they are, the better the outcome.