I'm curious what you'd suggest in the early stages...
# ❓・ai-evy-supportv
Vib'in😎
03/25/2026, 3:10 AM@AI Evy I'm curious what you'd suggest in the early stages of building a voice AI agency. In many cases I spend a lot of time determining the right build flow. Not neccesarily single vs multi prompt, but more about the architecture. In all of my agents that I've built, its taken serious amounts of time and I ask myself if there are easier ways to quickly determine the correct flow based on specific criteria. How have you all dealt with this? Are there tools that helped Is it just grinding to learn as much as you can or is there a simpler way, maybe even retell guidance that I've overlooked? I know there are prompt generators when creating the agent but doesnt always translate.
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AI Evy
03/25/2026, 3:10 AMThanks for tagging me @Vib'in😎. I'll look through relevant sources and get back to you shortly.
AI Evy
03/25/2026, 3:10 AMudes :
- Identity section (role and expertise)
- Style Guardrails (conciseness, tone)
- Response Guidelines (formatting, confirmation patterns)
- Task Instructions (specific steps)
- Objection Handling
This structured approach offers reusability, maintainability, and clarity for LLM comprehension .
**
AI Evy
03/25/2026, 3:10 AM### Answer
Based on the available sources, here's guidance on determining the right architecture for your voice AI agents:
When to Switch from Single/Multi Prompt to Conversation Flow
The documentation provides clear criteria for choosing between agent types. Consider switching to Conversation Flow agents when you encounter [(1) ]() :
- **Multiple decision branches**: More than 3-4 conditional paths
- **Tool coordination**: Using 5+ different functions/tools
- **State management**: Tracking multiple variables throughout the conversation
- **Reliability concerns**: Single prompt shows inconsistent behavior
Benefits of Conversation Flow for complex scenarios :
- Each node focuses on one specific task
- Deterministic tool calling and transitions
- Easier to debug and optimize individual steps
- More predictable agent behavior
Rapid Testing Approach
Retell provides the LLM Playground for quick iteration without making actual calls [(2) ]() . This enables :
- Rapid prototyping and debugging of agent responses
- Testing different conversation scenarios
- Immediate feedback on agent behavior
- Faster development iterations
Recommended Testing Workflow
The documentation outlines a phased approach [(3) ]() :
Phase 1: Development Testing - Use LLM Playground to iterate on prompts, debug function calling logic, test edge cases, and validate dynamic variables
Phase 2: Quality Assurance - Use LLM Simulation Testing to create comprehensive test scenarios and run regression tests after changes
Structuring Your Prompts
For either agent type, use sectional prompts for better organization [(1) ]() . The recommended structure incl
AI Evy
03/25/2026, 3:10 AM
To learn more, see the sources I considered:
[[1] Prompt Engineering Guide](https://docs.retellai.com/build/prompt-engineering-guide)
[[2] Manually test your agent](https://docs.retellai.com/test/llm-playground)
[[3] Testing Overview](https://docs.retellai.com/test/test-overview)
AI Evy
03/25/2026, 3:10 AMFeel free to tag @AI Evy with additional questions. I also appreciate feedback, it helps me improve.