Before we talk about how to prompt well — let's look at where things are going wrong right now.
Seven elements. Every strong prompt for a creative professional task contains most or all of them. The more you include, the less the AI has to guess.
Before it generates a single word, give the AI a professional identity. This changes its vocabulary, its assumptions, its level of formality, and even the sources it draws on. A news reporter and a brand copywriter will write the same event very differently — so tell it which one to be.
Give the AI the background it would need to brief a new hire on this project. What's the organization? What's the campaign or story? What's already happened that this content responds to? The more specific the situation, the more specific the output.
State your deliverable clearly. Don't say "write something about" — say exactly what you want: a press release, a 90-second podcast intro, three Instagram captions, a homepage hero paragraph. Vague goals produce vague outputs.
Audience definition is one of the highest-leverage elements in any prompt. The same message written for a city council editor and a college freshman will sound completely different. Tell the AI who will read or hear this — their age, role, expertise level, and relationship to your organization.
Specific facts, people, dates, data points, or structural elements that must appear in the output. If the AI doesn't know a detail, tell it — or instruct it to leave a placeholder so you can fill it in. Never assume the AI will invent accurate specifics.
Word limits, words or phrases to avoid, topics to exclude, things that are off-brand or legally sensitive. Constraints save you from the AI defaulting to its most generic, safest output. If you've ever received a response full of "exciting opportunities" and "thrilled to announce" — a constraint would have fixed that.
Tell the AI exactly what the output should look like: AP style, bullet points, a script with speaker cues, a headline followed by three paragraphs, a table. Without a format spec, the AI picks one for you — and it's usually the wrong one for how you'll actually use the content.
Before the AI writes anything, have it ask you 3–5 clarifying questions. This is one of the most powerful moves in professional prompting. It forces the AI to surface gaps in your brief before it starts generating — and it often reveals what you forgot to include.
Add this line at the end of any prompt:
The questions the AI asks will tell you exactly where your brief was incomplete. Answer them, then let it write.
The same task. The same AI. Two very different prompts — and two very different results. Look for which framework elements are missing in the weak version.
The first response is a draft, not a deliverable. Iteration is how professionals use AI — not prompting once and accepting whatever comes back.
If the output is close but not right, don't rewrite the entire prompt. Identify the specific problem and address only that. "Make the opening more direct." "Cut this to 200 words without losing the key facts." "The tone is too formal — make it sound like a person, not a brochure." Targeted follow-up is faster and more effective than starting over.
If the AI keeps missing the style or format you want, show it. Paste in a sentence, a paragraph, or even a full piece and say: "Match this tone" or "Follow this structure." A single good example outperforms a paragraph of description. This technique is called few-shot prompting, and it is one of the most reliable tools you have.
Sometimes the content is right but the structure makes it hard to use. Ask the AI to reorganize, reformat, or restructure without rewriting the substance: "Give me this as a bulleted list." "Put the most important point first." "Convert this to a script with speaker cues." Format changes cost nothing but a follow-up prompt.
"Write something about our event" forces the AI to invent everything — the angle, the audience, the length, the purpose. Be specific about what you need and why.
Without knowing who will read or hear this, the AI defaults to a generic adult audience. That's rarely who you're actually writing for.
The AI will choose a format — usually the most common one for that type of content. If you need something specific (AP style, a script, three short paragraphs), say so.
No word limit, no tone guidelines, no list of things to avoid — and you'll get the AI's defaults. Defaults are what all generated content sounds like before you make it yours.
Packing five deliverables into one prompt splits the AI's attention. Build each piece separately, then assemble. One prompt, one focused output.
Pick one real-world task. Write your first instinct prompt. Then rebuild it using the seven-element framework and the "Ask me questions" technique. Submit both versions with a short reflection.
Select the one you'll work on today. You'll use this same task for both your weak and strong prompt.
Write the prompt you would have written before today's class. Don't overthink it — just write what you would naturally type. This is your "before."
Now copy this into ChatGPT, Claude, or Gemini and read what comes back. Note where it fell short.
Add the following line to the end of a revised prompt and send it. Read the AI's questions carefully — they'll show you what your brief was missing.
Answer the questions, then let it generate. That answered version becomes the basis of your strong prompt below.
Rewrite your prompt using the seven-element framework: role, context, goal, audience, requirements, constraints, format. Use what the AI's questions revealed.
In 2–3 sentences: what specifically changed between your first and second prompt, and how did the AI's output improve as a result?
Key terms from Lesson 2, plus a discussion on who AI writes well for — and who gets left behind.
The input you give an AI — your question, instruction, or request. The quality of a prompt directly determines the quality of the output. Prompting is a learnable professional skill, not a technical one.
The practice of deliberately structuring your inputs to an AI to get better, more useful outputs. Prompt engineering is not about writing code — it's about communicating with precision. Every element of the seven-part framework is a form of prompt engineering.
The process of refining AI output through multiple follow-up prompts rather than accepting the first response. Professional AI workflows almost always involve iteration — treating the first output as a rough draft, then prompting further to improve, correct, or redirect it.
A technique where you provide one or more examples of what you want, and the AI uses them as a pattern to follow. Instead of describing a style in words, you show it. "Match the tone of this paragraph" is a form of few-shot prompting — and it is often more effective than any description you could write.
Asking the AI to perform a task with no examples — relying entirely on your written instructions. Most everyday prompting is zero-shot. It works well for clear, well-defined tasks. It struggles when the style, format, or nuance is hard to describe but easy to show.
A set of instructions given to an AI before the conversation begins, establishing its role, behavior, and constraints for the entire session. When a company deploys an AI assistant with a specific personality or set of limits, those are defined in a system prompt. As a user, you're working within whatever system prompt the platform has set — though you can usually override much of it with a strong enough role definition in your own prompt.
A workflow design principle where a human reviews, verifies, and makes final decisions on all AI-generated content before it is published or submitted. The AI drafts; the human decides. This is the professional standard — not optional. No framework, no matter how well-constructed, replaces editorial judgment.
LLMs learn from whatever text they were trained on. That text reflects the demographics, assumptions, and blind spots of its authors — which skews heavily toward English-language, Western, educated, and affluent sources. An AI asked to write for a specific community it has little training data on will produce output that feels generic, flattened, or subtly off. Recognizing this isn't a reason to avoid AI — it's a reason to edit critically and know your audience better than the model does.
The style and perspective an AI falls back on when no specific audience, role, or tone is specified. The default voice tends to be generic, formal, American-English, and corporate-adjacent. It is the voice of AI slop. Strong prompting — especially audience definition and constraints — is what moves the output away from the default and toward something that actually serves your readers.
A statement attached to any work product created with AI assistance, describing which tools were used and for what purpose. In this course, disclosure is required on all graded work. In professional practice, disclosure standards vary by outlet — but the direction of the industry is toward more transparency, not less. Getting comfortable with disclosure now puts you ahead of colleagues who are still hiding their AI use.
Lesson 2 · Planning and Prompting for Creative Professionals