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TwilioPaul KampTutorial
How to Test and Fix Voice AI Agent Prompts with Twilio Conversation Relay and Cekura
Summary
This tutorial demonstrates building a voice AI agent with Twilio Conversation Relay, Node.js, and the OpenAI API, then testing and fixing its prompts using Cekura automated platform, a Twilio Startup Searchlight award winner. Conversation Relay manages real-time voice tasks like speech-to-text, text-to-speech, interruption detection, and turn management over WebSockets, while developers control business logic, tools, and AI integration. Cekura defines evaluation metrics, generates test conversations with realistic caller scenarios—interruptions, topic changes, and unexpected requests—and runs baseline tests to uncover prompt gaps. After analyzing failure reports, developers update the system prompt and re-run tests; fixing a fee-waiver bug raised the pass rate from below 70% to the 90-95% target in one refinement. The tutorial emphasizes that prompts are source code requiring version control and automated testing for reliable voice AI agent behavior.
Context
Voice AI agents often break when callers interrupt, change topics, or ask unexpected questions, exposing prompt gaps that can lead to incorrect promises. Automated testing helps catch these issues before deployment.
Approach / What changed
The solution uses Twilio Conversation Relay for real-time voice streaming and turn management, combined with an automated testing loop using Cekura: define evaluation metrics, generate test conversations simulating realistic caller behaviors, run baseline tests, analyze failure reports, update the system prompt with precise policy instructions, and re-run the test suite to validate fixes.
Takeaways
Conversation Relay handles real-time voice streaming—speech-to-text, text-to-speech, interruption detection, turn management—over WebSockets, while developers control business logic and AI tools.
Cekura can automatically generate test conversations that simulate realistic caller behaviors like interruptions and unexpected requests to uncover prompt bugs missed by manual testing.
After identifying a failure, updating the system prompt with precise policy instructions—such as restricting fee waivers to eligible account tiers—can raise the pass rate from below 70% to 90-95% in one refinement round.
FAQ
What prompt bug did Cekura find in the initial agent?
Cekura found that the initial system prompt did not restrict fee waivers to Gold and Platinum accounts. As a result, the voice agent offered a fee waiver to a Premium account holder who did not qualify, violating the bank's policy. The bug was fixed by adding explicit eligibility rules to the prompt.
How do I update a prompt after seeing failures in Cekura?
Review the failure reports to identify unmet policies or logic gaps. Update the system prompt with precise instructions addressing the root cause, such as adding 'Fee waivers apply only to Gold and Platinum accounts.' Then re-run the test suite to confirm the fix raised the pass rate.
Why might my pass rate barely change after a prompt update?
The troubleshooting section advises checking that your new prompt addresses all feedback, not just symptoms. A metric stuck at 0% across runs likely indicates a broken evaluator, not a bad agent. A new yellow row may require fixing the evaluator and re-evaluating metrics.
Source and freshness
- Source
- twilio.com
- Published
- Added to Yomu
Summaries are generated from the original by a language model. Check the original before relying on it.
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