Panel of Experts Prompting: Using AI Like a Boardroom, Not an Intern

Most people prompt ChatGPT like it’s an intern.

“Write me a marketing email.” “Fix this code.” “Explain this concept.”

But what if you used it like a boardroom of experts?

The Panel of Experts Technique

Here’s the prompt structure:

“I want you to simulate a panel of experts discussing [topic]. The panel includes:

• [Expert 1 with specific credentials]
• [Expert 2 with different perspective]
• [Expert 3 with contrarian view]

Each expert should share their perspective on [question], and they should respond to each other’s points.”

Why This Works

LLMs have absorbed expertise from countless perspectives. When you ask a generic question, you get a generic answer, a blend of all those perspectives into something safe and mediocre.

But when you ask for a specific expert’s perspective, you access a more focused subset of the training data. And when you create dialogue between experts, you get something closer to real intellectual discourse.

A Real Example

Bad prompt:

“What’s the best database for my startup?”

Good prompt:

“I’m building a startup that handles user-generated content with high write volume. Simulate a panel discussion:

• A PostgreSQL expert who has scaled databases at Stripe
• A MongoDB advocate who has built content platforms
• A contrarian database architect who believes most startups overcomplicate data storage

Each should argue for their approach and respond to the others’ points.”

The second prompt yields a nuanced discussion that covers:

• Actual trade-offs (not just “it depends”)
• Real-world experience and war stories
• Contrarian perspectives that challenge assumptions
• Synthesis that helps you make a decision

Variations That Work

The Mentor Panel

“Simulate advice from:

• Paul Graham on startup strategy
• Patrick Collison on building developer tools
• Naval Ravikant on making decisions under uncertainty”

The Technical Review

“Review this architecture as if you were:

• A senior SRE concerned about operational burden
• A security engineer looking for vulnerabilities
• A product engineer worried about developer experience”

The Devil’s Advocate

“Make the strongest possible case against [my idea], as if you were:

• A competitor trying to find weaknesses
• A skeptical investor looking for deal-breakers
• A customer who’s been burned before”

Tips for Better Panels

1. Make experts specific. “A PostgreSQL expert who scaled Stripe’s databases” beats “a database expert.”

2. Include contrarians. The best panels have someone who disagrees with the premise.

3. Ask for interaction. “Respond to each other’s points” generates richer discussion.

4. Give context. The more specific your situation, the more relevant the advice.

5. Follow up. “What would [Expert 1] say to [Expert 2]’s point about X?”

When Not to Use This

This technique is overkill for simple questions. Don’t use it for:

• Factual lookups
• Straightforward coding tasks
• Summarization

Use it for:

• Strategic decisions
• Architecture choices
• Anything where “it depends” is the likely answer

The Meta-Point

The panel technique works because it fights the averaging problem in LLMs. Generic prompts yield generic answers because the model averages across all possible responses.

Specific personas narrow the search space. Dialogue creates synthesis. The result is something closer to what you’d get from actually consulting experts.

You’re not making the AI smarter. You’re helping it access the expertise it already has.

Try it on your next big decision. The boardroom is always in session.