How to Write Better AI Prompts That Actually Deliver
A four-part framework to help professionals prompt with precision, not just enthusiasm.
AI prompts need more than keywords – they need context, clarity and direction,Use the CATS model: Context, Angle, Task, Style,Think of prompting as a conversation, not a one-shot request
What makes a good AI prompt? It's a deceptively simple question, but one that now echoes through boardrooms, bootcamps and HR briefings across Asia. As tools like ChatGPT, Microsoft Copilot and Gemini become baked into daily workflows, the ability to "think with AI" is emerging as a defining digital skill. Yet many users still find themselves let down by vague, underwhelming answers. The problem isn’t the AI itself – it’s how we ask.
Why Prompting Matters Now
With AI adoption on the rise across sectors from education to ecommerce, companies are quietly rethinking what "digital fluency" means. Where once it was enough to master spreadsheets or PowerPoint, today's knowledge workers are expected to interface with large language models. Prompting is becoming the new typing: a basic skill that quietly underpins productivity.
Yet many early adopters have hit the same wall. You ask a smart question. You get a flat, generic answer. It feels like asking a Michelin chef for a good meal and being served dry chicken. The truth is, AI responds to probabilities. It gives you the most common response unless told otherwise. For a deeper dive into how people are actually using AI, see our article on [/business/by-year-end-we-will-have-built-100-agents-across-three-industries-here-are-the-takeaways].
The CATS Approach to Prompting
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To move beyond bland outputs, professionals need a simple prompting framework. One popular approach gaining traction in enterprise training sessions is CATS: Context, Angle, Task, and Style.
Context: Set the scene. Don’t just say, "Write a proposal." Say, "I’m a nonprofit director crafting a grant proposal for an environmental education project in Jakarta." Upload relevant documents. Explain constraints. Make it specific. Angle: Use AI’s role-playing strength. Ask it to adopt a tone or persona: "Act as a sceptical investor reviewing this pitch deck," or "Respond as a supportive mentor helping a junior employee rewrite this email." Task: Be explicit. Instead of "Help with my presentation," say, "Suggest three ways to make the opening slide more engaging for SME founders." Style: AI is a chameleon. Want a formal report? Bullet points? A punchy executive summary? Say so. Clarify the voice: technical, conversational, persuasive?
Together, these four elements help transform prompts from guesswork into guided collaboration. For more on what makes a good model, explore [/life/small-vs-large-language-models-explained].
It’s Not Just the Prompt – It’s the Context
Beyond wording, savvy users are learning to manage what researchers call "context engineering". This refers to everything that surrounds the prompt: memory, chat history, uploaded files, examples, and the cumulative logic of the conversation.
The more you treat the interaction like a back-and-forth exchange rather than a vending machine, the more useful the AI becomes. Ask follow-up questions. Push back. Request tweaks. If you spot useful phrases or structure in a long reply, paste them into a new session and build from there. Learn how to refine your prompts by teaching AI your specific writing style with [/news/customise-chatgpt-s-tone-warmth-enthusiasm-structure].
AI Fluency Is Human-First
But here’s the rub. Even the best prompt in the world won’t save you if you over-trust the machine. AI chatbots sound human, but they don’t think. You do.
Errors, hallucinations and inaccuracies are part of the package, especially when the system improvises without enough direction. Treat AI as your sparring partner, not your oracle. Your job is to bring the judgement, precision and domain knowledge. AI's job is to accelerate and amplify. For an in-depth understanding of AI's limitations and current capabilities, refer to the AI Index Report.
As Asia’s digital economy matures, AI fluency will quietly separate the merely tech-aware from the truly productive. So next time you fire up a chatbot, ask yourself: are you giving it chicken, or something to really cook with?
Latest Comments (4)
This CATS framework sounds proper useful, especially with all the hype around AI chatbots these days. It’s not just about getting more from the tech, but really about empowering us to work smarter. I think many here in Singapore are feeling the pressure to leverage AI, and clearer prompts are a definite game-changer for efficiency. Good stuff!
Interesting read! The CATS model seems quite neat for structuring prompts. I was just wondering, when thinking about the "Angle" part, how do you suggest we fine tune it for more nuanced, culturally specific topics here in Asia, especially when a straight forward Western perspective might miss the mark? Good job simplifying the process, cheers.
Interesting framework, the CATS model seems quite practical. I'm a bit wary, though, if 'style' can truly be codified for AI. Prompt engineering is vital, no doubt, but some creative flair is hard to articulate, isn't it? Still, a useful guide for professionals across Asia and beyond. Will give it a whirl.
This CATS framework sounds like just what the doctor ordered! I’ve been seeing so many people in my network, especially the younger professionals, struggling to get useful output from AI tools. It's almost like everyone's quick to adopt the technology, but not quite sure how to ‘talk’ to it effectively. This article really highlights that crucial gap. It is a bit concerning, though, how much emphasis we're now placing on 'prompt engineering' as a skill. Are we losing some of our fundamental thinking abilities if we rely too heavily on AI, even with excellent prompts? Still, for practical day-to-day work, this looks like a brilliant guide.
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