The Art of Prompting: How to Get Expert-Level Output from ChatGPT and Claude

Most of us treat AI like a search engine: toss in a few keywords, cross our fingers, and hope for something useful. Then we wonder why their output sounds flat, generic, or robotic. The truth is, tools like OpenAI’s ChatGPT and Anthropic’s Claude aren’t Google. They’re more like brilliant interns; capable of astonishing work, but only if you give them clarity, structure, and direction.

Recently, Anthropic shared its framework for structuring prompts. It’s a template that mirrors many of the best practices professional AI users have already discovered, and when you apply it, the difference is striking. Think of it less as “tricking” the model and more as onboarding a high-potential hire.

Here’s how to get both Claude and ChatGPT to deliver responses that sound less like “AI copy” and more like expert analysis.

Stage 1: Setting the Stage

1. Define the Role and Context
Don’t just ask for a task — assign a role. “Write an email” is vague. “You’re a senior marketing director writing to the CEO about Q4 strategy” provides the scaffolding an LLM needs to simulate expertise.

2. Specify Tone
“Be professional” is too fuzzy. Instead, try: “Use a professional but approachable tone, as if briefing a smart colleague.” Both Claude and ChatGPT thrive on specificity here.

3. Provide Background Data
Feed the model context — reports, prior conversations, style guides, relevant emails. Claude is especially good at handling long context windows, but ChatGPT performs better too when you prime it with details instead of expecting it to improvise.

Stage 2: Structuring the Work

4. Write Detailed Instructions with Boundaries
Constraints sharpen creativity. “Explain in under 500 words,” “Avoid technical jargon,” or “Cite sources in footnotes” give the model a lane to run in. Without guardrails, you’ll get meandering answers.

5. Show Examples
LLMs are pattern machines. A single good example can often teach more than paragraphs of instruction.

6. Use Conversation History
Neither ChatGPT nor Claude has permanent memory between sessions. If you’re continuing a project, re-include the relevant prior exchanges. Think of it as reminding your intern what you talked about yesterday.

7. State the Immediate Task Clearly
After all the context, end with precision: “Now, draft the executive summary in three paragraphs.” It focuses the model’s attention on what matters right now.

Stage 3: Refinement and Output

8. Encourage Step-by-Step Thinking
Add a nudge like: “Think this through step-by-step before answering.” Both Claude and ChatGPT show improved reasoning when prompted to pause and deliberate.

9. Dictate Output Formatting
Don’t assume the model knows how you want results structured. Whether it’s Markdown, bullet points, or XML, be explicit.

10. (Advanced) Use a Prefilled Start
Begin the response for the model — “Executive Summary: …” — and it will mimic the style and structure you’ve cued.

Pro Tips That Work Across Models

• Layer Context Like an Onion: Start broad (role), then narrow (task), then immediate action.
• Constraints Drive Focus: Rules don’t stifle creativity — they sharpen it.
• Examples Trump Instructions: Show, don’t tell.
• The “Think First” Trick: Small cues like “take a deep breath” reliably improve reasoning patterns.

Why This Works

Claude excels at handling massive context and following intricate rules. ChatGPT, on the other hand, is remarkably adaptive and polished in tone, especially when given examples and clear formatting constraints. Both shine when treated like high-capacity collaborators rather than magic boxes.

Before vs. After: ChatGPT Example

Before (weak prompt):

Write an email to employees about remote work policy changes.

Result:
A generic corporate memo that sounds like it could have been copied from a template.

After (strong prompt using best practices):

You are the HR Director at a mid-sized tech company. Write a clear, professional but approachable email to all employees announcing an update to the remote work policy.

Tone: Friendly but authoritative.
Constraints: Keep it under 300 words. Avoid jargon. End with a clear call-to-action.
Background: The new policy allows employees to work remotely up to 3 days a week starting next quarter. The change is based on employee feedback and leadership’s desire to maintain flexibility while supporting collaboration.
Format: Subject line, greeting, 3 short paragraphs, sign-off.

Now draft the email.

Result:
An email that feels tailored, professional, and easy to act on — closer to what a skilled HR professional would actually send.

Final Word

The takeaway? Prompting isn’t about clever hacks or jailbreaks. It’s about communication clarity. With the right framework, you stop getting “AI responses” and start getting output that feels like it came from a seasoned professional.

Next time you open ChatGPT or Claude, don’t just prompt — onboard. Treat the model like the brilliant intern it is. Give it role clarity, rules, and examples, and it will repay you with work that doesn’t just meet expectations but exceeds them.

Click here for the accompanying explainer video