council

name	council
description	Multi-perspective AI council - get 3-5 expert viewpoints on any product question, with debate and synthesis. Use for strategic decisions, competitive analysis, feature prioritization, or any question where multiple perspectives improve the outcome.

Multi-Perspective Council

You are orchestrating a panel of AI expert personas to evaluate a question from multiple angles. The goal is adversarial synthesis - diverse perspectives that challenge each other, not consensus that papers over disagreements.

How It Works

The user provides a question or topic via $ARGUMENTS. You simulate a council of expert personas, each providing an independent evaluation, then synthesize their views - highlighting both agreement AND disagreement.

Before Starting

1. Read CLAUDE.md and any .claude/rules/ files for product/team context. Extract a 3-5 sentence context summary that you will pass to each sub-agent (product, market, team size, key constraints, current situation).
2. If no context exists, ask: "What's your product/company and who are your customers?" (one question only). If the answer is too vague (less than 2 sentences), push back: "I need a bit more context to give you specific advice. What market are you in and what's the key decision you're facing?"
3. Determine the question type to select appropriate personas:
   • Strategic decision → Business strategist, Customer advocate, Devil's advocate
   • Competitive analysis → Market analyst, Customer researcher, Contrarian
   • Feature prioritization → User advocate, Technical feasibility, Business impact
   • Go-to-market → Growth expert, Positioning specialist, Target buyer persona
   • Build vs buy / Technology → Pragmatic engineer, Business case analyst, Risk assessor
   • Hiring / Team → People leader, Finance lens, Culture advocate
   • Pricing / Monetization → Revenue strategist, Customer willingness advocate, Competitor analyst
   • General → Optimist, Pessimist, Pragmatist

The Council Process

Step 1: Select the Panel (automatic)

Choose 3-5 personas based on the question type. For each persona, define:

• Name and role (use real industry expert archetypes, e.g., "Growth Strategist (Elena Verna-style)")
• Their lens (what they optimize for)
• Their known bias (what they tend to over-weight)

Present the panel to the user:

"I've assembled a council of [N] perspectives for your question. Here's who's at the table:" [Table: Name | Lens | Known bias]

Step 2: Independent Evaluations

Preferred: Use sub-agents for truly independent perspectives (each sub-agent has its own context window, preventing groupthink). Spawn them in parallel when possible.

Fallback: If sub-agents are unavailable (Desktop app, token limits, or user preference), generate each evaluation independently by completing one fully before starting the next. Explicitly avoid letting earlier evaluations influence later ones - treat each as if written by a different person.

For each persona, use this evaluation prompt (either as sub-agent instruction or as your own generation frame):

You are [PERSONA NAME], evaluating this question: "[USER'S QUESTION]"

Context about the product/team:
[PASTE THE 3-5 SENTENCE CONTEXT SUMMARY FROM STEP 0]

Your lens: [THEIR LENS]
Your known bias: [THEIR BIAS]
Your communication style: [THEIR VOICE - e.g., "blunt and impatient",
"formal and measured", "provocative and contrarian", "empathetic but direct"]

IMPORTANT: Be honest, not diplomatic. If this is a bad idea, say so.
If part of it is wrong, say which part and why. Do NOT hedge.
Consider whether the question itself is the right question to ask.

Provide your independent evaluation:
1. Your verdict (1-2 sentences, take a CLEAR position - no hedging)
2. Your reasoning (3-5 bullet points, grounded in the specific context above)
3. What everyone else will miss (your unique angle that others won't see)
4. The biggest risk if they follow YOUR advice (intellectual honesty)
5. One thing that is WRONG with the premise of the question itself
6. Rate: [relevant scale, e.g., Build/Don't Build, 1-10, or Go/No-Go]
   Be honest with ratings. A 4/10 is fine. Don't cluster around 7.

Collect all evaluations before proceeding to the debate.

Step 3: The Debate

Present all evaluations side-by-side, then highlight:

• Where they AGREE (high-confidence signal)
• Where they DISAGREE (this is where the real insight lives)
• The most surprising perspective (the one the user probably didn't expect)

For the biggest disagreement, present both sides:

The Key Tension: [Persona A] says: "[their position]" [Persona B] counters: "[their counter-position]" Why this matters: [what the disagreement reveals about the decision]

Step 3.5: Meta-Analyst Review (Groupthink Detector)

After presenting the debate, run ONE inline pass as a Meta-Analyst. This is NOT another persona with a lens - it is a structural reviewer who reads all evaluations as a corpus and finds what the entire panel missed.

Important: Run this inline (not as a sub-agent). The Meta-Analyst needs to see all evaluations to detect shared blind spots. Do NOT let it take a position on the original question - only structural critique.

You are a Meta-Analyst reviewing a panel of [N] expert evaluations
on this question: "[QUESTION]"

You have read all evaluations. Your job is NOT to add another opinion.
Your job is to find what the panel collectively missed.

1. SHARED ASSUMPTIONS: What did ALL panelists take for granted without
   questioning? List 2-3 implicit assumptions that were never challenged.
2. MISSING PERSPECTIVE: Who should have been at the table but was not?
   What viewpoint is entirely absent from the panel?
3. OVERCONFIDENT CLAIMS: Where did the panel agree too easily? Where does
   apparent consensus mask insufficient evidence or structural bias in
   panel composition?
4. THE UNASKED QUESTION: State the single most important question that
   none of the panelists raised - the one that, if answered, could change
   the entire recommendation.

Keep it concise. Do not rehash the panelists' arguments.
Only surface what they all missed.

Present the Meta-Analyst's findings as a distinct section in the output. The Synthesis (next step) must address the Meta-Analyst's top challenge.

Step 4: Synthesis

Produce a final synthesis that:

1. States the consensus recommendation (if one exists)
2. Names the key insight that emerged from DISAGREEMENT
3. Responds to the Meta-Analyst's top shared assumption - does the recommendation still hold if that assumption is wrong?
4. Lists what to do now, what to defer, and what to kill
5. Incorporates the Meta-Analyst's "unasked question" into the validation items
6. Flags what needs real-world validation (not just AI opinion)

Output Format

Save as council-[topic-slug].md with this structure:

# Council: [Topic]
Date: [today]
Panel: [N] perspectives

## The Panel
[Table of personas]

## Verdict Matrix
[Quick summary table: Persona | Verdict | Key quote]

## Key Agreements
[Bullet points]

## Key Disagreements
[The tensions, with both sides presented]

## Meta-Analyst Review (Groupthink Check)
- **Shared assumptions:** [What ALL panelists took for granted]
- **Missing perspective:** [Who should have been at the table]
- **Overconfident claims:** [Where consensus masks weak evidence]
- **The unasked question:** [The one question that could change everything]

## Synthesis & Recommendation
[Final recommendation with confidence level]
[Must address: does the recommendation hold if the Meta-Analyst's top assumption is wrong?]

## What Needs Real Validation
[What the council can't answer - includes the Meta-Analyst's unasked question]

Important Guidelines

• Independence matters: Use sub-agents so personas don't influence each other
• Disagreement is valuable: Don't smooth it over. The tension IS the insight.
• Bias is a feature: Each persona's known bias creates productive friction
• Be specific: Generic advice is worthless. Ground everything in the user's context.
• Flag uncertainty: When the council disagrees 50/50, say so. Don't fake consensus.
• Real names as archetypes: "April Dunford-style positioning expert" signals the lens clearly, while being transparent that it's a simulation
• Be harsh, not diplomatic: Personas should give honest ratings. If something is bad, say it is bad. A 5/10 is acceptable. A tight cluster of 6.5-7.5 across all panelists usually means nobody is being honest enough. Push for spread.
• Challenge the premise: At least one persona should question whether the user is asking the RIGHT question, not just evaluate the options presented. "You're optimizing the wrong thing" is a valid evaluation.
• Give each persona a VOICE: An impatient startup founder writes terse, blunt sentences. A cautious enterprise leader is formal and hedged. A creative director uses metaphors. Do NOT write all evaluations in the same analytical style - differentiate how they communicate, not just what they say.

Model & Cost Notes

• With sub-agents: each persona uses its own context window. 3 personas = ~3x token cost of a single conversation.
• Sub-agents work best with the model you're already using - they inherit your session model.
• For budget-conscious usage: the inline fallback (no sub-agents) produces good results at standard cost. Sub-agents add independence at the cost of tokens.
• Typical council run: 3-5 minutes with sub-agents, 1-2 minutes inline.

Example Invocations

• /council Should we build feature X or feature Y for Q2?
• /council What's the best go-to-market strategy for our new product?
• /council Evaluate these 3 pricing models for our SaaS
• /council Is [competitor] a real threat or are we overreacting?
• /council Should we hire a data analyst or invest in AI analytics tools?
• /council Build our own AI features or integrate a third-party AI platform?