How Optimization Works

Converra uses AI-powered simulation to find better versions of your prompts.

The Process

┌─────────────┐     ┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Analyze   │ --> │  Generate   │ --> │  Simulate   │ --> │   Select    │
│   Prompt    │     │  Variants   │     │   & Test    │     │   Winner    │
└─────────────┘     └─────────────┘     └─────────────┘     └─────────────┘

1. Analyze Prompt

Converra analyzes your prompt to understand:

• Structure and formatting
• Goals and constraints
• Potential improvement areas

2. Generate Variants

AI creates alternative versions of your prompt:

• Each variant targets specific improvements
• Variants maintain your core requirements
• Typically 3-5 variants are tested

3. Simulate & Test

Each variant is tested against simulated personas:

• Diverse user types (frustrated, technical, new, etc.)
• Multiple conversation scenarios
• Realistic interaction patterns

4. Select Winner

Performance is evaluated across metrics:

• Task completion rate
• Response quality
• User sentiment
• Goal achievement

The best-performing variant is identified.

What Gets Optimized

Aspect	Example Improvement
Clarity	Clearer instructions, better structure
Tone	More appropriate formality level
Efficiency	Shorter responses that still work
Completeness	Better coverage of edge cases
Consistency	More predictable behavior

Optimization Modes

Exploratory Mode

Best for: Finding improvements quickly

• Fewer simulations per variant
• Faster results (minutes)
• Good for iteration

Validation Mode

Best for: Production decisions

• More simulations per variant
• Statistical confidence
• Takes longer but more reliable

What Stays the Same

Converra preserves your:

• Core purpose and role
• Key constraints and boundaries
• Required output formats
• Brand voice fundamentals

Simulation Personas

Your prompts are tested against diverse users:

Persona	Tests
Frustrated Customer	De-escalation, empathy
Technical User	Accuracy, depth
New User	Clarity, onboarding
Impatient User	Conciseness
Confused User	Patience, explanation

You can also create custom personas matching your actual users.

Metrics Evaluated

Primary Metrics

• Task Completion - Did the AI help the user achieve their goal?
• Response Quality - Was the response accurate and helpful?
• User Sentiment - How would the user feel about the interaction?

Secondary Metrics

• Conciseness - Appropriate length for the context
• Consistency - Similar situations handled similarly
• Safety - Stayed within appropriate boundaries

Example Optimization

Original Prompt:

You are a customer support agent. Help users with their questions.

Optimized Variant (Winner):

You are a customer support agent for TechCorp. Your goal is to
resolve issues quickly while maintaining a friendly tone.

When helping users:
1. Acknowledge their issue
2. Ask clarifying questions if needed
3. Provide a clear solution
4. Confirm the issue is resolved

If you can't resolve an issue, offer to escalate to a specialist.

Improvement: +34% task completion, +28% user satisfaction

Next Steps

• Running Optimizations - Start an optimization
• Understanding Results - Interpret results
• Best Practices - Write optimization-ready prompts