Prompt Engineering: The dos and don’ts of getting AI to work for your organisation.
“Garbage in, garbage out.” This old adage has never been more relevant than in the world of AI. A well-crafted prompt can mean the difference between a chatbot that spits out generic nonsense and one that delivers insightful, accurate responses. As AI continues to reshape industries, mastering the art of prompt engineering has become an essential skill for anyone leveraging conversational AI.
What is prompt engineering?
Simply put, prompt engineering is the practice of designing effective inputs for AI models to get the most useful outputs. It’s like giving instructions to an intern – be too vague, and they’ll be lost; be too rigid, and they might miss creative solutions. Striking the right balance is key.
At its core, prompt engineering involves:
- Understanding how AI interprets language
- Structuring queries to minimise ambiguity
- Iterating on prompts to refine responses
The basics: Getting AI to work for you
Before diving into advanced techniques, you need to get the fundamentals right. Here’s how:
1. Be clear and specific
AI models are powerful, but they’re not mind readers. Instead of asking, “Tell me about history,” say, “Summarise the key events of World War II in under 200 words.” The more precise you are, the better your results.
2. Use Context to Your Advantage
If you’re working with an AI assistant that doesn’t have memory, make sure to pack relevant details into your prompt. For example, instead of “Write a summary of this article” try, “Write a 200-word summary of the following article for a professional audience: [insert text].”
3. Set constraints and formatting expectations
Want bullet points? A table? A specific tone? Ask for it. Compare:
- “Explain blockchain.” (Too vague)
- “Explain blockchain in three bullet points, using simple terms suitable for a business executive.” (Much better)
Taking it to the next level
Once you’re comfortable with the basics, it’s time to refine your approach. Here are some pro-level strategies:
1. Experiment with role-based prompts
AI responds differently based on context. Instead of a general request, try framing the AI as an expert:
- “You are a financial analyst. Explain the implications of rising interest rates on the housing market.”
- “You are a legal expert specialising in data privacy. Summarise the key aspects of GDPR compliance.”
This technique improves specificity and relevance to your sector and use case.
2. Chain your prompts
AI models don’t always nail complex tasks in one go. Instead of expecting perfection upfront, break requests into steps. Example:
- “Generate a list of key trends in AI for 2024.”
- “Summarise each trend in two sentences.”
- “Write an engaging LinkedIn post based on these insights.”
3. Iterate
Great prompts aren’t born; they’re refined. If an AI response misses the mark, tweak your input. Try changing the phrasing, adding constraints, or using a different approach. A small change—like switching “Explain X” to “List three key takeaways about X”—can make a huge difference.
The don’ts: What to avoid
Even the best AI users fall into common traps. Here’s what not to do:
1. Don’t overcomplicate your prompts
More words don’t always mean better results. Keep your prompts structured but avoid unnecessary complexity. Instead of: “Can you possibly provide me with a well-thought-out, highly detailed explanation of the main themes present in the novel 1984?” Try: “Summarise the key themes of 1984 in 150 words.”
2. Don’t assume AI understands nuance perfectly
AI models struggle with ambiguity. If you ask, “What’s the best way to write?” you’ll get a vague answer. Specify what you mean by “best”—efficient? Persuasive? SEO-optimised?
3. Don’t rely on a single prompt
One-shot prompts rarely yield the best results. Instead of expecting a perfect answer right away, engage in a back-and-forth, refining as you go. AI is a tool, not an oracle.
Final thoughts
Prompt engineering isn’t magic—it’s a skill that improves with practice. The more you experiment, the better you’ll get at extracting valuable insights from AI. Whether you’re generating content, analysing data, or automating workflows, mastering prompt engineering will give you a significant edge.
AI is only as good as the questions we ask. Ask better, and you’ll get better.
