AI Agents Guide

Get expert-level feedback and insights from 9 specialized AI agents through evaluation and discussion modes.

🤖 What are AI Agents?

AI Agents are specialized artificial intelligence experts that provide targeted feedback on your business ideas. Each agent brings unique expertise and perspective, simulating the experience of consulting with multiple industry experts.

🎯 Two Interaction Modes

📊 Evaluation Mode

Purpose: Get structured, comprehensive assessments from multiple expert perspectives.

How it works:

1. Select one or more agents to evaluate your idea
2. Agents provide detailed scores and feedback
3. Each agent focuses on their area of expertise
4. Results are presented in an organized dashboard

Best for:

• Initial idea assessment
• Comparative analysis across different expert views
• Identifying strengths and weaknesses
• Getting comprehensive feedback quickly

💬 Discussion Mode

Purpose: Have in-depth conversations with individual agents about specific aspects of your idea.

How it works:

1. Choose a specific agent to discuss with
2. Ask questions or request specific insights
3. Have a back-and-forth conversation
4. Get detailed explanations and personalized advice

Best for:

• Deep-diving into specific concerns
• Getting detailed explanations of feedback
• Exploring alternative approaches
• Asking follow-up questions

👥 Meet the 9 AI Agents

🎯 **Product Manager Agent**

Expertise: Product strategy, roadmaps, feature prioritization

Focus Areas:

• Market-product fit analysis
• Feature development strategy
• User story validation
• Product positioning

Example Questions:

• "How should I prioritize features for my MVP?"
• "What's the biggest risk to product-market fit?"
• "How can I validate this feature idea?"

💰 **Business Strategist Agent**

Expertise: Business models, competitive analysis, market entry

Focus Areas:

• Revenue model optimization
• Competitive positioning
• Market sizing and entry strategy
• Business model viability

Example Questions:

• "What's the best monetization strategy for this idea?"
• "How should I differentiate from competitors?"
• "What are the key risks to this business model?"

🎨 **UX Designer Agent**

Expertise: User experience, design thinking, usability

Focus Areas:

• User journey mapping
• Interface design principles
• Accessibility considerations
• User research insights

Example Questions:

• "What would the ideal user flow look like?"
• "How can I improve the user experience?"
• "What are potential usability issues?"

🔧 **Tech Expert Agent**

Expertise: Technical feasibility, architecture, implementation

Focus Areas:

• Technical complexity assessment
• Platform and technology choices
• Scalability considerations
• Development timeline estimation

Example Questions:

• "How technically feasible is this solution?"
• "What technology stack would you recommend?"
• "What are the main technical challenges?"

📈 **Marketing Expert Agent**

Expertise: Go-to-market strategy, customer acquisition, branding

Focus Areas:

• Customer acquisition strategies
• Brand positioning
• Marketing channel optimization
• Growth hacking techniques

Example Questions:

• "How should I acquire my first customers?"
• "What's the best marketing strategy for this audience?"
• "How can I build brand awareness quickly?"

💵 **Finance Expert Agent**

Expertise: Financial modeling, funding, unit economics

Focus Areas:

• Revenue projections
• Cost structure analysis
• Funding requirements
• Financial sustainability

Example Questions:

• "What would the unit economics look like?"
• "How much funding would I need?"
• "Is this financially viable?"

⚖️ **Risk Analyst Agent**

Expertise: Risk assessment, regulatory compliance, mitigation strategies

Focus Areas:

• Market risks identification
• Regulatory compliance issues
• Operational risk assessment
• Risk mitigation planning

Example Questions:

• "What are the biggest risks to this idea?"
• "What regulatory issues should I consider?"
• "How can I mitigate these risks?"

🏢 **Industry Expert Agent**

Expertise: Industry-specific insights, market dynamics, trends

Focus Areas:

• Industry trend analysis
• Market dynamics understanding
• Competitive landscape insights
• Sector-specific challenges

Example Questions:

• "What industry trends should I be aware of?"
• "How is this market changing?"
• "What do successful companies in this space do differently?"

📊 **Data Analyst Agent**

Expertise: Analytics, metrics, measurement strategies

Focus Areas:

• KPI identification
• Measurement frameworks
• Data collection strategies
• Performance analysis

Example Questions:

• "What metrics should I track?"
• "How should I measure success?"
• "What data do I need to collect?"

🚀 Getting Started with AI Agents

Step 1: Access AI Agents

1. Ensure you have a Plus Plan subscription
2. Navigate to your idea page
3. Look for the "AI Agents" section
4. You'll see the "Alpha" badge indicating this is a cutting-edge feature

Step 2: Choose Your Mode

For Evaluation Mode:

• Click "Start Evaluation"
• Select which agents you want feedback from
• Wait for comprehensive assessments

For Discussion Mode:

• Click "Start Discussion"
• Choose a specific agent to chat with
• Begin your conversation

Step 3: Review and Act

• Read through agent feedback carefully
• Take notes on key insights and recommendations
• Use feedback to refine your idea or strategy
• Come back for additional rounds of feedback as your idea evolves

💡 Best Practices

Getting the Most from Evaluations

Prepare Your Idea Well:

• Ensure your Value Canvas is complete and detailed
• Include specific information about your target market
• Be clear about your business model and assumptions

Select Relevant Agents:

• Choose agents based on your current questions or concerns
• Start with 3-4 agents rather than overwhelming yourself
• Consider your idea's stage - early ideas benefit from Product Manager and Business Strategist feedback

Review Systematically:

• Compare scores across different agents
• Look for consistent themes in feedback
• Identify conflicting opinions and understand why they differ

Maximizing Discussion Value

Ask Specific Questions:

❌ "What do you think of my idea?"
✅ "Given my target market of small business owners, what's the biggest 
   challenge to customer acquisition for this solution?"

Provide Context:

❌ "How can I improve?"
✅ "I'm seeing low conversion rates in my beta test. Based on my Value 
   Canvas, what might be causing users to drop off?"

Follow Up:

❌ Accept first answer without probing
✅ "That's interesting - can you give me a specific example of how 
   that strategy worked for similar companies?"

Strategic Agent Selection

Early Stage Ideas:

• Product Manager (market fit assessment)
• Business Strategist (model validation)
• UX Designer (user experience feasibility)

Pre-Launch:

• Tech Expert (implementation planning)
• Marketing Expert (go-to-market strategy)
• Finance Expert (funding and economics)

Growth Stage:

• Data Analyst (metrics and measurement)
• Risk Analyst (scaling challenges)
• Industry Expert (competitive positioning)

📊 Understanding Agent Feedback

Evaluation Scores

Each agent provides scores (typically 1-10) based on their expertise:

High Scores (8-10):

• Agent sees strong potential in their domain
• Few concerns or risks identified
• Recommendations are mostly optimizations

Medium Scores (5-7):

• Mixed assessment with both strengths and concerns
• Significant improvements possible
• May require strategic adjustments

Low Scores (1-4):

• Major concerns in agent's area of expertise
• Fundamental issues that need addressing
• May suggest significant pivots or changes

Reading Between the Lines

Consistent Feedback Across Agents:

• High confidence in the insight
• Core issue that needs attention
• Strong validation if positive

Conflicting Agent Opinions:

• Different perspectives revealing trade-offs
• Opportunity to explore multiple approaches
• May indicate need for more research

Agent-Specific Concerns:

• Domain-specific issues that others might miss
• Expertise-driven insights
• Often reveal hidden risks or opportunities

🔄 Iterative Improvement Process

Round 1: Initial Assessment

1. Get broad evaluation from 4-5 diverse agents
2. Identify top 3 issues across all feedback
3. Focus on fundamental problems first

Round 2: Targeted Deep-Dive

1. Select specific agents related to identified issues
2. Use Discussion Mode for detailed exploration
3. Develop specific action plans

Round 3: Validation

1. Implement changes based on feedback
2. Return for follow-up evaluation
3. Measure improvement in agent scores

⚠️ Limitations and Considerations

What AI Agents Excel At

• Pattern Recognition: Identifying common issues and opportunities
• Comprehensive Analysis: Covering multiple expert perspectives quickly
• Consistent Availability: 24/7 access to expert-level insights
• Objective Assessment: No personal bias or agenda

What AI Agents Cannot Do

• Replace Real Users: Cannot substitute for actual user feedback
• Predict the Future: Cannot guarantee market success
• Understand Unique Context: May miss industry-specific nuances
• Make Final Decisions: Should inform, not replace, your judgment

Best Practices for AI Agent Feedback

Use as Input, Not Gospel:

• Treat feedback as expert opinions, not absolute truth
• Validate insights with real market research
• Consider multiple agent perspectives before deciding

Combine with Human Feedback:

• Use alongside user interviews and market testing
• Seek mentor or advisor input on agent recommendations
• Test assumptions in the real world

🛠️ Advanced Techniques

Agent Personality Matching

Different agents have different "personalities" and approaches:

• Product Manager: Systematic, user-focused
• Business Strategist: Big-picture, commercially-oriented
• UX Designer: Empathetic, user-experience focused
• Tech Expert: Practical, implementation-focused

Choose agents whose perspectives align with your current needs.

Cross-Agent Analysis

Look for patterns across agent feedback:

Reinforcing Themes: Multiple agents highlighting the same issue

Complementary Insights: Different agents providing pieces of the same puzzle

Contrasting Views: Agents disagreeing, revealing important trade-offs

Conversation Strategies

Build on Previous Discussions:

Reference earlier conversations: "The Marketing Expert suggested focus on content marketing. How would that affect the metrics you'd recommend tracking?"

Challenge Agent Assumptions:

"You mentioned this market is saturated, but I see these gaps. How would you assess the opportunity differently?"

Request Specific Examples:

"Can you give me an example of a company that successfully navigated this challenge?"

📈 Measuring Success

Tracking Improvement

Quantitative Measures:

• Agent score improvements over time
• Consistency of positive feedback across agents
• Reduction in identified risks or concerns

Qualitative Indicators:

• More specific, actionable feedback from agents
• Shift from fundamental concerns to optimization suggestions
• Alignment between different agent perspectives

Success Indicators

Strong Validation Signals:

• Multiple agents giving scores of 8+ in their domains
• Specific, actionable optimization suggestions
• Agents identifying competitive advantages

Warning Signals:

• Consistently low scores across multiple agents
• Fundamental concerns about business model or market
• Conflicting feedback that can't be reconciled

Next Steps:

• Generate Business Model Canvas (Plus Plan)
• Explore Solution Discovery (Plus Plan)
• Take Validation Actions

Last updated: January 2025

Source: Value Discovery Platform