{"id":71661,"date":"2025-05-01T10:25:18","date_gmt":"2025-05-01T09:25:18","guid":{"rendered":"https:\/\/www.strattoncraig.com\/insight\/whats-missing-from-your-ai-prompts\/"},"modified":"2025-05-01T10:25:18","modified_gmt":"2025-05-01T09:25:18","slug":"whats-missing-from-your-ai-prompts","status":"publish","type":"post","link":"https:\/\/www.strattoncraig.com\/us\/insight\/whats-missing-from-your-ai-prompts\/","title":{"rendered":"What\u2019s missing from your AI prompts?"},"content":{"rendered":"

AI isn\u2019t magic. It\u2019s maths, language and incredible amounts of processing power. But that doesn\u2019t mean AI can read minds (yet). For now at least, you need to tell it exactly what you want to get the best results.<\/p>\n

We\u2019ve probably all had the following experience when first trying to get to grips with AI: you type in your request and hit enter. Instead of being presented with something dazzling, the AI\u2019s output hasn\u2019t hit the mark at all. So you decide to just do the task yourself.<\/p>\n

For a lot of people, this is the gap between AI expectations and AI reality in a nutshell. We\u2019re told that this powerful technology can do everything, but we keep getting bland, generic answers that will take a lot of time to fine-tune into something of real quality and value.<\/p>\n

But is this a case of user error or a flaw in the system? The truth is that as powerful as AI is, it also (currently) has clear limitations. It doesn\u2019t understand what you want \u2013 it predicts it based on the instructions and context you give it.<\/p>\n

So, if you\u2019re not getting the results you want from AI, the reason is probably that you aren\u2019t asking it in the right way.<\/p>\n

Why inputs matter more than you think<\/h3>\n

Your \u2018prompt\u2019 is all the information you give to an AI before it starts. If your prompt is vague, the result will be vague too.<\/p>\n

if you don\u2019t give AI direction, it\u2019ll fill in the gaps with guesswork.<\/p><\/blockquote>\n

Imagine if you contracted someone to do extensive interior designing of your home and the only instruction you gave them was that you \u201cwanted the place to be redder\u201d. You might come back to find the designer has wrongly interpreted your request as meaning you want crimson walls, maroon carpets and cherry-red furniture. Not because the designer is bad, but because your brief was.<\/strong> AI works the same way: if you don\u2019t give it direction, it\u2019ll fill in the gaps with guesswork.<\/p>\n

That\u2019s why strong inputs are essential.<\/p>\n

When you get specific, add detail, and provide structure, the AI has more to work with. Think of it less like a search engine and more like briefing an eager intern.<\/p>\n

Prompting myths that might be holding you back<\/h3>\n

Many beginner AI users fall into the same traps. Here are some of the most common misconceptions that might be influencing your outputs:<\/p>\n

\u201cYou only need one prompt.\u201d<\/strong><\/p>\n

Not quite. Effective prompting is iterative. A great input will get you a lot closer to the goal, but most of the time you start with something broad, see what comes back, and then tweak, expand or clarify. It\u2019s a dialogue \u2013 not a one-and-done transaction.<\/p>\n

\u201cThe AI should know what I mean.\u201d<\/strong><\/p>\n

How could it? It only knows what you tell it. If you want a blog post in a certain tone, or a list in a specific format, or a summary that includes particular points, you need to spell it out.<\/p>\n

\u201cIf it gets it wrong, the tool doesn\u2019t work.\u201d<\/strong><\/p>\n

Actually, a not-quite-right answer is a helpful signal. It shows where your prompt lacked clarity or context. It\u2019s your cue to refine.<\/p>\n

The anatomy of a good prompt<\/h3>\n

There\u2019s no one-size-fits-all formula, but effective prompts tend to have a few things in common:<\/p>\n

A clear instruction<\/h5>\n

What do you want the AI to do? Write? Rewrite? Summarise? Critique? Be precise.<\/p>\n

A specific output<\/h5>\n

Don\u2019t just say, \u201cwrite a post about sustainability.\u201d Say, \u201cwrite a LinkedIn post about our sustainability goals in a confident, professional tone, using no more than 100 words.\u201d<\/p>\n

Relevant context<\/h5>\n

What does the AI need to know to do the task well? That might include your audience, purpose, tone, brand guidelines, or relevant background.<\/p>\n

A defined format<\/h5>\n

Should it give you bullet points? A headline and intro? A numbered list? The more structure you include, the better.<\/p>\n

A useful example<\/h5>\n

Showing what \u2018good\u2019 looks like can be powerful. If you\u2019ve got a reference point or an ideal outcome in mind, include it. For example, if you don\u2019t have a tone of voice, you can just copy in text from a blog you want to emulate and tell the AI to write in that style.<\/p>\n

Thinking in workflows, not just outputs<\/h3>\n

In the next few years, what will separate the AI leaders from the rest of the pack is the ability to slot AI into their processes in a way that enhances value. The aim of the game here isn\u2019t replacing people, it\u2019s enabling them with AI solutions deployed in a strategic way.<\/p>\n

Instead of just asking AI to complete a task, think about how it could support a broader process. Imagine it as an intern \u2013 capable, fast, but in need of guidance.<\/p>\n

Say you\u2019re writing a client proposal. You could break the process into steps like:<\/p>\n