Turn Your AI Into a Boardroom of Experts

Flip One Answer Into Debate

January 18, 2026

Last week I asked an AI a “simple” strategy question and got a confident answer in five seconds. It sounded smart. It was also the kind of advice that gets people stuck: clean, generic, and weirdly eager to please. Then I tried a different approach and watched the whole thing change. The AI started disagreeing with itself, flagging risks, and arguing over tradeoffs like a real team would. The result wasn’t just better writing. It was a sharper decision.

The single biggest mistake people make with AI is treating it like a solitary intern instead of an executive leadership team.

Most of us fall into a trap where we ask a chatbot a question and accept the first, singular answer it spits out. That linear approach is fine for basic facts, but it falls apart the moment you need real judgment. I came across a great post by a Reddit user that flips the dynamic: instead of asking for one opinion, you simulate a boardroom of conflicting experts and force the AI to debate itself before giving you an answer.

In partnership with

Dictate prompts and tag files automatically

Stop typing reproductions and start vibing code. Wispr Flow captures your spoken debugging flow and turns it into structured bug reports, acceptance tests, and PR descriptions. Say a file name or variable out loud and Flow preserves it exactly, tags the correct file, and keeps inline code readable. Use voice to create Cursor and Warp prompts, call out a variable like user_id, and get copy you can paste straight into an issue or PR. The result is faster triage and fewer context gaps between engineers and QA. Learn how developers use voice-first workflows in our Vibe Coding article at wisprflow.ai. Try Wispr Flow for engineers.

Last week I asked an AI a “simple” strategy question and got a confident answer in five seconds. It sounded smart. It was also the kind of advice that gets people stuck: clean, generic, and weirdly eager to please. Then I tried a different approach and watched the whole thing change. The AI started disagreeing with itself, flagging risks, and arguing over tradeoffs like a real team would. The result wasn’t just better writing. It was a sharper decision.

The single biggest mistake people make with AI is treating it like a solitary intern instead of an executive leadership team.

Most of us fall into a trap where we ask a chatbot a question and accept the first, singular answer it spits out. That linear approach is fine for basic facts, but it falls apart the moment you need real judgment. I came across a great post by a Reddit user, Complex-Ice8820, that flips the dynamic: instead of asking for one opinion, you simulate a boardroom of conflicting experts and force the AI to debate itself before giving you an answer.

This isn’t just about getting “better output.” It’s about surfacing blind spots you didn’t know you had. When you force the model to wear multiple hats, you reduce the “echo chamber” effect where it tries to be agreeable. The author calls this a Multi-Agent Orchestrator, and it’s a practical way to use role-play inside Large Language Models for high-level problem solving.

The Multi-Agent Orchestrator Concept
The idea is simple: assign the AI a Lead Orchestrator whose job is not to answer your question directly, but to run a structured discussion between distinct personas. In the Reddit example, the “boardroom” includes a Creative Director, a Data Scientist, and a Legal Advisor.

What makes it powerful is segmentation. When the AI is the Creative Director, it leans into novelty, messaging, and audience psychology. When it becomes the Legal Advisor, it narrows into compliance, liability, and risk. When it switches to the Data Scientist, it turns skeptical and asks what the numbers actually support. You’re not getting a blended smoothie of advice. You’re getting three sharp lenses, and the tension between them creates clarity.

Why The “Three-Perspective” Model Works
The author picked those three roles for a reason. They map cleanly to a classic decision framework: Desirability, Viability, and Feasibility.

Desirability (Creative Director) pushes for what people want and what will grab attention. Viability (Data Scientist) asks if it will work in the real world and what evidence supports it. Feasibility (Legal Advisor) adds the guardrails and friction every serious plan runs into.

If you ask a standard prompt like “How should I market this product?” you often get a list of pleasant-sounding tactics that aren’t grounded in constraints. With the boardroom setup, the AI generates an idea, attacks it, defends it, and reshapes it before you ever see the final recommendation.

AI-native CRM

“When I first opened Attio, I instantly got the feeling this was the next generation of CRM.”
— Margaret Shen, Head of GTM at Modal

Attio is the AI-native CRM for modern teams. With automatic enrichment, call intelligence, AI agents, flexible workflows and more, Attio works for any business and only takes minutes to set up.

Join industry leaders like Granola, Taskrabbit, Flatfile and more.

*Ad

Other awesome AI guides you may enjoy

The Magic of the “Master Strategy” Synthesis
The most important step is the final instruction: synthesize the conflicting advice into a single Master Strategy.

Without that, you’re just reading three mini-essays and doing the hard thinking yourself. The Reddit user shifts the cognitive load back onto the AI. The Lead Orchestrator has to act like a CEO: absorb the Creative Director’s ambition, respect the Legal Advisor’s warnings, weigh the Data Scientist’s probabilities, then choose a path that holds together.

This is where AI can actually feel like a partner. Not because it “knows everything,” but because it can compare patterns, spot contradictions, and merge tradeoffs into something usable.

Customizing Your Boardroom
The corporate boardroom is just a template. You can swap personas for almost any situation.

For solopreneurs: Direct Response Copywriter, Brand Storyteller, Skeptical Customer. For developers: Senior Architect, Junior Developer, Security Auditor. For personal planning: Gourmet Chef, Strict Nutritionist, Budget Planner.

The point is to invite criticism on purpose, so your plan gets stronger before it touches the real world.

Prompt of the Day
Here is the structure shared by the Reddit user (paste it into your LLM of choice):

The Boardroom Prompt:
You are a Lead Orchestrator. You will simulate a discussion between a Creative Director, a Data Scientist, and a Legal Advisor regarding [Insert Your Goal Here].

Each persona must provide 200 words of feedback from their specific worldview.

Finally, you will synthesize their conflicting advice into a single Master Strategy.

I highly recommend checking out the full post to see how others are tweaking this workflow for their specific industries!

AI in CX that grows loyalty and profitability

Efficiency in CX has often come at the cost of experience. Gladly AI breaks that trade-off. With $510M in verified savings and measurable loyalty gains, explore our Media Kit to see the awards, research, and data behind Gladly’s customer-centric approach.

*Ad