Understanding Agents
Agents are intelligent voice assistants powered by advanced AI models. They are the core component that handles conversations, understands user intent, and executes actions during phone calls.Agent Components
System Prompt
The system prompt is the most critical component of an agent. It defines: Personality and Tone: How the agent speaks and interacts with users. Should it be formal or casual? Friendly or professional? Capabilities: What the agent can and cannot do. Clearly define the agent’s purpose and limitations. Instructions: Step-by-step instructions for handling different scenarios, edge cases, and error conditions. Context: Information about your business, products, services, or domain that the agent needs to know. Best Practices: Guidelines for the agent to follow, such as always confirming important information or asking clarifying questions when needed.Model Configuration
Model Selection: Choose the AI model that best fits your needs:- GPT-4: Best for complex reasoning, nuanced conversations, and handling edge cases
- Claude: Excellent for long context windows and detailed analysis
- GPT-3.5: Good balance of cost and performance for simpler use cases
Voice Configuration
Voice Provider: Choose a voice provider (ElevenLabs, etc.) that matches your quality and cost requirements. Voice Selection: Select a specific voice that matches your brand. Consider factors like gender, age, accent, and tone. Speaking Speed: Adjust how fast the agent speaks. Slower speeds are better for complex information, faster for simple confirmations. Voice Stability: Control how consistent the voice sounds. Higher stability means less variation in tone and delivery.Functions
Functions allow agents to interact with external systems and perform actions: Function Definition: Define what the function does, what parameters it accepts, and what it returns. API Integration: Connect to external APIs to fetch data, update systems, or trigger actions. Error Handling: Define how the agent should handle function failures or errors. Function Chaining: Some functions can call other functions, enabling complex workflows within a single agent.Agent Lifecycle
Creation
When creating an agent:- Define Purpose: Clearly define what the agent is meant to do
- Choose Model: Select the appropriate AI model
- Write Prompt: Craft a detailed system prompt
- Configure Voice: Select voice settings
- Add Functions: Define any required functions
- Test: Test the agent thoroughly before deployment
Configuration
Ongoing configuration includes: Prompt Refinement: Continuously improve the system prompt based on real conversations and feedback. Function Updates: Add, modify, or remove functions as your needs evolve. Voice Tuning: Adjust voice settings to optimize for your use case. Model Optimization: Experiment with different models and settings to find the best balance of quality and cost.Deployment
Before deploying an agent:- Test in Simulation: Use the simulation feature to test thoroughly
- Review Prompt: Ensure the prompt is clear and complete
- Check Functions: Verify all functions work correctly
- Test Voice: Listen to how the agent sounds
- Monitor First Calls: Closely monitor the first real calls
Monitoring and Optimization
Review Conversations: Regularly review call transcripts to identify areas for improvement. Analyze Metrics: Track success rates, user satisfaction, and goal achievement. Iterate Prompt: Use AI Studio to quickly iterate on prompts based on real data. Optimize Costs: Monitor token usage and costs, optimize prompts to reduce unnecessary tokens.Advanced Agent Features
Context Management
Conversation History: Agents maintain context throughout a conversation, remembering previous exchanges. Context Limits: Be aware of context window limits. Very long conversations may exceed limits. Context Strategy: Choose how to manage context - append new messages, summarize old ones, or use sliding windows.Multi-Turn Conversations
State Management: Agents can maintain state across multiple conversation turns. Goal Tracking: Agents can track conversation goals and work toward completing them. Clarification: Agents can ask clarifying questions when information is unclear.Error Handling
Graceful Degradation: Agents should handle errors gracefully, providing helpful messages rather than technical errors. Fallback Strategies: Define fallback behaviors when functions fail or errors occur. User Communication: Clearly communicate errors to users in a helpful, non-technical way.Agent Best Practices
Prompt Engineering
Be Specific: Vague prompts lead to unpredictable behavior. Be as specific as possible about desired behavior. Provide Examples: Include examples of good interactions in your prompt. Set Boundaries: Clearly define what the agent should and shouldn’t do. Test Iteratively: Continuously test and refine prompts based on real conversations.Function Design
Keep Functions Focused: Each function should do one thing well. Validate Inputs: Always validate function inputs before processing. Handle Errors: Functions should return clear error information. Document Functions: Clearly document what each function does and how to use it.Voice Optimization
Match Brand: Choose voices that match your brand identity. Test Quality: Always test voice quality on actual phone calls, not just in the dashboard. Optimize Speed: Adjust speaking speed based on content complexity and audience.Next Steps
Workflows
Learn how to build complex call routing and processing with workflows.