Iro AI Blog
Why your AI prompts aren't working (and how to fix them)
Five reasons prompts fail — and the quick fixes that turn vague output into useful work.
Iro AI Blog
Five reasons prompts fail — and the quick fixes that turn vague output into useful work.
"Write a marketing plan" gets you generic slop because the model has to guess everything. The fix is specificity: who it is for, what the goal is, and what the constraints are.
You are a head of marketing at a 12-person SaaS startup. Write a 6-week launch plan for a $99/mo product. Include weekly deliverables, an owner, and a KPI for each. Keep it under 400 words.
Same model, completely different result.
Models behave differently depending on who you tell them to be. "You are a senior copy editor" produces sharper edits than no role at all. Add the context it needs, too — the audience, the prior decisions, the format of the source material. Without context, the model invents it, and that is where wrong answers come from.
Iro AI turns ideas like the ones in this post into 5-minute exercises with feedback. Free tier, Pro from $0.96/week ($49.99/year, 7-day free trial).
If you do not say what the output should look like, you get a wall of prose. Specify it as a contract: a table, a bulleted list, JSON, a three-sentence summary. "Return only a markdown table with columns Task, Owner, Due" stops the model from rambling and makes the output something you can actually use.
The first draft is the worst draft. The single highest-leverage move is to make the model critique and improve its own answer: "List three weaknesses of that draft, then rewrite to fix them." It costs a few seconds and almost always improves the result.
For anything where style or format matters, show — do not tell. Two or three examples that bracket the range you want teach the model faster than a paragraph of instructions. This is the few-shot pattern, and it is the fastest fix for "close, but not quite right."
Most failed prompts break one of those five rules. A reliable opener that covers most of them: role, goal, context, constraints, and output format — then a self-critique pass. That structure is the backbone of practical prompt engineering.
The fastest way to internalise it is reps. Iro AI's Prompt Lab grades your real prompts and shows you exactly which of these mistakes you are making; the ChatGPT path applies the same moves inside the tool.
Iro AI turns ideas like the ones in this post into 5-minute exercises with feedback. Free tier, Pro from $0.96/week ($49.99/year, 7-day free trial).
Usually because the prompt is too vague. Add a role, the goal, context, constraints, and an output format, and the answers get specific fast.
Nine times out of ten it is the prompt. The same model produces very different output depending on how you specify the task.
Ask the model to critique and rewrite its own first draft. It is the highest-leverage move for the least effort.
Practice with feedback. Iro AI's Prompt Lab scores your prompts and points out what to fix.