AI + Technology

For decades, I managed creative and marketing teams, and the hardest part of the job was never the creative work itself. It was getting useful feedback. Clients, executives, and even internal teams struggled to articulate what they wanted. Most people do not know how to critique.

They assume it means pointing out what they do not like, but that is not enough. Real critique is the ability to give clear, constructive direction. It means knowing not just what is wrong, but what is missing and how to improve it. And here is the uncomfortable truth. If you think you are great at giving feedback, you probably are not.

That gap between what people think they are communicating and what they actually say is about to become a major problem. The rise of artificial intelligence, specifically large language models like GPT, is forcing more people to interact with technology in a way they never had to before. These tools do not generate brilliance out of thin air. They rely entirely on the quality of the input. If you cannot articulate what you need, the results will be generic, ineffective, or completely wrong.

The Challenge of Giving Good Direction

Most people do not realize how bad they are at giving direction because they have never had to be precise. In a traditional work setting, creative teams fill in the gaps. A designer, writer, or strategist will take vague feedback and refine it. They will read between the lines, ask follow-up questions, and adjust based on experience. If a client says, “I want something bold,” a good creative team knows to clarify. Does bold mean bright colors? Does it mean strong typography? Does it mean aggressive messaging? The client may not even know. A skilled creative professional deciphers those requests and turns them into something meaningful.

Artificial intelligence does not do that. It does not have the instincts or experience to fill in the blanks. It only knows what it has been given. If the prompt is vague, the response will be vague. If the direction is generic, the output will be generic. Without strong input, the AI will return the lowest common denominator response because that is what vague prompts produce.

This is the fundamental flaw in how most people will approach prompt engineering. They assume AI will do the heavy lifting, when in reality, it is only as good as the instructions it receives.

Why Most People Will Struggle

Most people do not refine ideas before asking for results. They are used to reacting to what is in front of them rather than proactively shaping what they want. In a business setting, they give feedback after a concept has already been created. They do not start with a clear vision. Instead, they wait until they see something they do not like and react. AI does not work that way. It does not give you a first draft to react to unless you specifically ask for one. It will only generate what you tell it to generate. If you do not know exactly what you want, you will not get anything useful back.

This is why prompt engineering is an actual skill and why most people will struggle with it. Writing a good prompt requires the ability to think ahead, structure an idea clearly, and provide details that guide the AI toward the desired outcome. That means being specific, giving context, and understanding what kind of output you are looking for before you ever type the first word.

Few people are naturally good at this. Most people will rely on trial and error, which is fine in small doses but inefficient at scale. The people who thrive in this new era will be the ones who understand how to give clear, structured direction and refine their input instead of blaming the AI when they get a weak result.

The Future of AI is a Thinking Problem

There is a misconception that artificial intelligence will replace thinking. In reality, it demands better thinking. The real power of AI is not in automating creativity but in enhancing it. However, that only happens if the people using it know how to think critically, articulate ideas clearly, and refine their approach.

For decades, creative professionals have struggled to get good feedback from clients and executives. Now that same challenge is being applied to AI. The difference is that AI will not push back, ask clarifying questions, or read between the lines. It will simply give you what you asked for, even if what you asked for was not what you meant.

The future of AI is not just about the tools getting smarter. It is about people getting better at thinking, articulating, and directing. Without those skills, even the most powerful AI will just be spinning its wheels, producing output that is as weak and unfocused as the prompts that generated it.

How to Write Better Prompts and Use AI More Effectively

Since AI relies on human input, using it well is about mastering the art of direction. Here are eight ways to write better prompts and get more valuable responses.

1. Be Specific
   Vague prompts lead to vague results. Instead of saying, “Write about marketing,” say, “Write a 500-word article on why brand consistency improves customer trust, with three real-world examples.”

2. Provide Context
   AI does not know what you are thinking. If you need something in a certain tone, for a specific audience, or in a unique format, spell it out. “Explain content strategy like you are teaching a college marketing class” is much better than just asking for a definition.

3. Give an Example
   If you have a preferred style or structure, reference it. “Write this in the style of a New Yorker think piece” or “Make it sound like a TED Talk opening monologue” gives the AI a reference point.

4. Use Iteration
   The first response from AI is rarely perfect. Use follow-up prompts to refine the answer. If a response is too generic, ask, “Make this more detailed with industry-specific insights.”

5. Avoid Overloaded Requests
   Do not ask for too much in one prompt. “Write a blog post, summarize it in bullet points, generate five social media captions, and create a headline” is too much at once. Break it into steps for better results.

6. Ask for Alternatives
   If you are looking for fresh ideas, tell the AI to generate multiple options. “Give me three different angles on why brand loyalty is declining” will get you better results than just asking for a single response.

7. Use Constraints
   Limitations improve creativity. Instead of saying, “Write an ad for a new fitness app,” say, “Write a 10-word tagline for a fitness app that targets busy professionals.”

8. Know When to Stop
   AI is a tool, not a replacement for thinking. If the output feels robotic, uninspired, or off the mark, stop tweaking the prompt and start reworking the idea itself. AI can help shape an idea, but it cannot create something truly original without human input.

Reverse Prompt Engineering: The “View Source” of AI

In the early days of the internet, if you wanted to understand how a webpage was built, you could right-click and hit View Source. It exposed the raw HTML behind the design, letting anyone see how the structure worked. Those who knew how to read it could learn, tweak, and build better sites.

Reverse prompt engineering is the AI equivalent. After writing an article, I pasted it into a custom GPT and asked it to generate the prompt that could have been used to create it. Instead of just using AI to generate content, this method reveals how structured prompts shape high-quality outputs.

If you want better AI results, do not just tweak responses—study the prompts that create them. Understanding the mechanics of a strong prompt is what separates casual users from those who can actually get AI to work for them.

Example Reverse Engineered Prompt

*”Write a long-form article on why most people will struggle with prompt engineering. The article should be structured with clear sections and avoid unnecessary bolding, excessive bullet points, and em dashes. It should reflect the perspective of an experienced creative and marketing leader who has spent decades managing teams and dealing with the challenges of getting useful feedback.

Start by explaining why most people do not know how to critique effectively and how this lack of clarity makes AI tools difficult to use. Discuss the role of prompt engineering in generating high-quality AI output and why vague or poorly structured prompts lead to generic or weak results.

Include a section on why most people struggle with giving direction, using real-world examples of how creative professionals interpret vague client feedback and why AI does not have the ability to fill in the gaps.

Add a practical section outlining eight ways to write better prompts and use AI more effectively. This should include strategies like being specific, providing context, using iteration, avoiding overloaded requests, and setting clear constraints.

Conclude with a discussion on why AI is not a replacement for human thinking but a tool that requires better articulation, critical thinking, and refinement to be effective.

The tone should be direct, sharp, and no-nonsense, with a mix of dry wit and strategic insight. Assume the audience is intelligent and already familiar with AI concepts, so do not over-explain. Avoid corporate jargon and marketing clichés. Keep the structure clean with clear section breaks and avoid excessive formatting. Use strong, confident language without over-reliance on AI-generated fluff.”*