Prompt Engineering: Why It Matters and How To Do It Right
The ability to communicate effectively with AI systems is becoming a core marketing competency. Here's what prompt engineering actually means for marketing leaders.
Originally published in Chronicles of Change, October 2023.
There’s a new skill emerging in marketing that didn’t exist two years ago, and it’s more important than most leaders realise. Prompt engineering — the art and science of communicating effectively with AI systems — is rapidly becoming as essential as copywriting or data analysis in the modern marketing toolkit.
What Prompt Engineering Actually Is
Strip away the jargon and prompt engineering is fundamentally about communication. It’s the practice of crafting inputs to AI systems that produce useful, accurate, and relevant outputs. It sounds simple. It isn’t.
A poorly constructed prompt produces generic, hallucinated, or irrelevant output. A well-constructed one produces work that rivals — and in some domains exceeds — human expert output. The difference isn’t the AI model. It’s the quality of the instruction.
Why Marketing Leaders Should Care
Scale of Content Operations
Marketing teams are under pressure to produce more content across more channels than ever before. AI can help — but only if your team knows how to direct it effectively. The difference between a team that uses AI well and one that doesn’t isn’t budget or tools. It’s prompt literacy.
Quality Control
Without skilled prompting, AI-generated content is mediocre at best and damaging at worst. Brand voice consistency, factual accuracy, audience relevance — all depend on how the AI is instructed. “Write me a blog post about X” will give you exactly the kind of generic content that erodes brand equity.
Strategic Advantage
Organisations that develop prompt engineering as a core competency will move faster, produce better work, and extract more value from their AI investments. Those that treat it as a novelty will find themselves outpaced.
Principles of Effective Prompting
1. Context Is Everything
The most common prompting mistake is insufficient context. AI doesn’t know your brand, your audience, your competitive landscape, or your strategic objectives unless you tell it. Effective prompts front-load context before requesting output.
2. Be Specific About Format and Tone
“Write a LinkedIn post” is a poor prompt. “Write a 200-word LinkedIn post for B2B marketing leaders, in a confident but conversational tone, focusing on [specific topic], ending with a thought-provoking question” is dramatically better. Specificity drives quality.
3. Use Examples
Show the AI what good looks like. Include examples of previous content that worked well, demonstrate the style you want, provide a template. Few-shot prompting — giving the model examples of desired output — consistently outperforms zero-shot instructions.
4. Iterate, Don’t Accept
First outputs are drafts, not finals. The skill isn’t in writing one perfect prompt — it’s in the iterative dialogue that refines output toward excellence. Think of it as a conversation with a very capable but literal-minded colleague.
5. Build Prompt Libraries
Effective prompts are organisational assets. Build libraries of tested, proven prompts for common use cases. Share them across teams. Iterate on them collectively. This transforms individual skill into institutional capability.
The Leadership Implication
Prompt engineering isn’t just a tactical skill for your content team. It’s a strategic capability that determines how effectively your entire organisation leverages AI. As a leader, your role isn’t to become the best prompt engineer — it’s to ensure your organisation develops this competency systematically.
Invest in training. Create space for experimentation. Recognise and reward prompt literacy. The organisations that get this right in 2023-2024 will have a compounding advantage that their competitors will struggle to close.