Feature Spec: Boardroom Mode

Multi-Model Collaborative Analysis with User-Selected Presenter

Executive Summary

Problem: Users currently get single-perspective outputs. Even when they try multiple models manually, there's no synthesis—just fragmented responses.

Solution: Add a "Boardroom" action button that orchestrates 3 diverse LLMs through 5 specialized analysis steps, then synthesizes results through the user's selected model.

Value Prop:

• Higher quality outputs (multi-perspective → fewer blind spots)

• Reduced iteration cycles (users don't manually run 5-10 prompts)

• Differentiated feature (no competitor offers orchestrated multi-model analysis)

• Leverages existing model infrastructure (no new APIs needed)

Technical Feasibility: High. Uses existing model integrations + lightweight orchestration layer.

User Experience Flow

Before (current state):

1. User types prompt

2. Selects model from dropdown

3. Gets single-model response

4. If unsatisfied, manually tries different models/rewrites prompt

After (with Boardroom):

1. User types prompt

2. Clicks Boardroom button (bottom action row)

3. Waits 8-15 seconds

4. Gets synthesized response from their selected Presenter model

5. Optional: Expands "Show Boardroom Notes" to see analysis breakdown

Key UX principle: Zero configuration. User doesn't pick council models or configure steps—just click and get better output.

Technical Architecture

Component Overview

[User Prompt] 

    ↓

[Boardroom Orchestrator]

    ↓

[Parallel Multi-Model Execution] (Steps 1-5)

    ↓

[Bundle Aggregator]

    ↓

[Presenter Synthesis] (User's selected model)

    ↓

[Final Output to Chat]

Execution Flow (Detailed)

Phase 1: Council Execution (Parallel)

• Input: User's prompt

• Process:

  • Send user prompt + role-specific instruction to 3 pre-selected models

  • Run 5 sequential steps (each step parallelizes across 3 models)

  • Each model returns max 5 bullets per step

• Output: 15 structured responses (3 models × 5 steps)

Phase 2: Bundle Creation

• Input: 15 council responses

• Process: Organize by step into structured bundle

• Output: Markdown-formatted analysis bundle

Phase 3: Presenter Synthesis

• Input: Original prompt + bundle

• Process: Selected model (from existing dropdown) writes final response

• Output: Clean, conversational answer in chat

The 5 Analysis Steps

Each step is a specialized lens. All 3 council models run each step.

Why 5 steps: Covers strategic, creative, editorial, market, and reality-check lenses. Universal across use cases (content, brand, strategy, copy).

Council Model Selection

Potential Default:

• Model A: GPT-4o-mini (OpenAI)

• Model B: Claude 3.5 Haiku (Anthropic)

• Model C: Gemini 1.5 Flash (Google)

Why these:

• Fast (low latency)

• Cheap (cost-effective for 15 calls)

• Diverse families (different training, strengths, biases)

Alternative: Dynamic selection based on availability/cost, but must ensure 3 different model families.

Presenter Model Selection

Behavior: Whatever model user has selected in the existing dropdown becomes the Presenter.

Why this works:

• User gets output in their preferred model's voice/quality

• Separates "background compute" from "presentation layer"

• No new UI needed—leverages existing dropdown

Example:

• Council runs on: GPT-4o-mini, Haiku, Flash

• User has selected: Claude Opus

• Final output: Written by Opus (synthesis of council work)

Token/Cost Analysis (Hypothetical)

Per Boardroom Execution:

Council Phase:

• 15 calls (3 models × 5 steps)

• ~300 tokens input per call (prompt + role instruction)

• ~200 tokens output per call (5 bullets)

• Total council: ~7,500 tokens

Presenter Phase:

• 1 call

• ~4,000 tokens input (original prompt + bundle)

• ~800 tokens output (final answer)

• Total presenter: ~4,800 tokens

Grand Total: ~12,300 tokens per Boardroom execution

Cost Comparison:

• Council models (mini/haiku/flash): ~$0.015 per execution

• Presenter model (varies): ~$0.02-0.15 depending on model

• Typical total: $0.03-0.17 per Boardroom

vs. Manual Approach:

• User runs 5-10 separate prompts trying to get good output

• Higher aggregate token usage

• More user time burned

ROI: Higher per-click cost, but dramatically fewer clicks needed.

Integration with Existing Features

Search/Connected Sources:

Behavior: If user has Search enabled or board sources connected, council models inherit that context automatically.

Implementation: No special handling needed—just pass context to council models same way you pass to single-model calls.

Model Dropdown:

Behavior: Dropdown becomes "Presenter selection" when Boardroom is used.

Implementation: No UI change needed—just change backend behavior: selected model does synthesis instead of primary generation.

Implementation Phases

Phase 1: MVP (Ship This First)

• ✅ Boardroom button (bottom action row)

• ✅ 3 fixed council models (mini/haiku/flash)

• ✅ 5-step orchestration

• ✅ Presenter synthesis

• ✅ Final output to chat (no notes visibility)

Scope: ~2-3 weeks, 1 backend engineer + 1 frontend engineer

Phase 2: Polish

• "Show Boardroom Notes" toggle (collapsed by default)

• Display step-by-step breakdown

Scope: +1 week

Phase 3: Advanced (Optional)

• Fast/Deep toggle (2 steps vs 5 steps)

• Custom council model selection (power users)

• Boardroom analytics (track quality improvement)

Success Metrics

Adoption:

• % of active users who try Boardroom in first 30 days

• Repeat usage rate (users who use it 3+ times)

Quality:

• Reduction in follow-up prompts after Boardroom vs. standard

• User satisfaction scores (survey)

• Retention increase among Boardroom users

Efficiency:

• Avg time-to-acceptable-output (Boardroom vs. manual iteration)

Risk Mitigation

Why This Feature Wins

1. Differentiated: No other AI chat tool offers orchestrated multi-model analysis

2. Leverages existing infra: Uses models you already have integrated

3. High perceived value: "3 AI models working together" = premium feel

4. Reduces churn: Users get better outputs → stay longer

5. Upsell opportunity: Can gate advanced features (custom councils, more steps)

Proposed System Prompts

Council Role Templates

Step 1: Strategist

You are the Strategist in a 3-model Boardroom.

User's request: {USER_PROMPT}

Your job: Identify the best approach, structure, and execution plan.

Return (5 bullets max):

- Primary goal and success criteria

- Recommended structure/framework

- Critical first steps

- Key dependencies or requirements

- One thing most people miss when doing this

Step 2: Creative

You are the Creative in a 3-model Boardroom.

User's request: {USER_PROMPT}

Your job: Generate hooks, angles, and format variations.

Return (5 bullets max):

- Strongest hook/opening angle

- 2-3 alternative approaches

- Format recommendation

- One unexpected creative angle

- What makes this stand out

Step 3: Editor

You are the Editor in a 3-model Boardroom.

User's request: {USER_PROMPT}

Your job: Find weaknesses, gaps, and what should be cut.

Return (5 bullets max):

- Biggest weakness in this approach

- Critical missing information

- What to remove/simplify

- Assumptions that need validation

- One question that must be answered first

Step 4: Market/Viral Lens

You are the Market Analyst in a 3-model Boardroom.

User's request: {USER_PROMPT}

Your job: Assess what performs and how to package for maximum impact.

Return (5 bullets max):

- What format/style wins right now

- Audience hook priority

- Pacing/delivery guidance

- What's likely to underperform

- Packaging recommendation

Step 5: Bias Detector

You are the Bias Detector in a 3-model Boardroom.

User's request: {USER_PROMPT}

Your job: Call out creator bias vs. audience reality.

Return (5 bullets max):

- Where creator preferences conflict with audience needs

- Self-confirmation bias flags

- "You'd like this but your audience won't" moments

- Overcomplexity warnings

- Reality check: what actually matters to end user

Presenter Synthesis Prompt

You are the Presenter. Synthesize the Boardroom analysis into a clear, actionable final answer.

ORIGINAL REQUEST:

{USER_PROMPT}

Boardroom ANALYSIS:

[Step 1 - Strategist]

Model A: {bullets}

Model B: {bullets}

Model C: {bullets}

[Steps 2-5...]

{all_council_responses}

YOUR JOB:

Write a clear, conversational response that:

- Provides the best actionable answer

- Incorporates key insights from all perspectives

- Flags critical warnings/watch-outs

- Asks 2-3 high-leverage follow-up questions (if needed)

Tone: Professional but conversational. No meta-commentary about the Boardroom process.

Recommendation

Ship Phase 1 as MVP. The core value (multi-model synthesis) is immediately usable and differentiated. Notes visibility and advanced features can iterate based on user feedback.

Timeline: 3-4 weeks to production-ready MVP.

Resource ask: 1 backend engineer, 1 frontend engineer, light PM oversight.

Expected impact: 15-25% of power users adopt within 60 days, measurable reduction in prompt iteration cycles.

Questions for product/eng review:

1. Do we gate this behind a plan tier or ship to all users?

2. Do we want usage analytics per Boardroom execution?

3. Should council models be configurable (admin settings) or hardcoded?

Prepared by: Tom Schreier / TopAItoolsfor
Date: 02/24/2026
Prepared using Poppy 😉