The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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215 articles · Page 17 of 18
Prompt engineering vs. context engineering: What's the next step for voice AI?
While prompt engineering focuses on perfecting inputs, context engineering optimizes the entire conversation environment. Discover why context engineering is becoming the key differentiator in voice AI.
Digital Twins for AI Agents: Simulate Before You Ship
Build digital twins that test your AI agent against thousands of synthetic customers. Architecture, TypeScript code, and the patterns that catch failures.
Silent Monitoring by AI: Quality Assurance Without Human Eavesdropping
Industry research shows that 70-75% of enterprises are implementing AI-powered silent monitoring for quality assurance. Discover how automated QA transforms agent performance without privacy concerns.
Failure Modes: What 'Accidents' in Voice AI Teach Us about Responsible Deployment
When voice AI systems fail, they don't just break. They reveal fundamental truths about how we build, deploy, and trust artificial intelligence. Discover what real-world failures teach us about responsible AI.
The Rise of Hyper-Personalization: Custom-Tuning Agents on the Fly for Every Caller
Industry research shows that 65-70% of enterprises are implementing hyper-personalization strategies for Voice AI. Discover how real-time agent customization transforms customer experience.
Building for Accessibility: Designing Voice AI for Neurodiverse and Disabled Users
Industry research shows that 40-45% of enterprises overlook accessibility in voice AI design. Discover how to create inclusive AI systems that serve all users effectively.
Echo Chambers: Avoiding Feedback Loop Biases in Voice AI Data Collection
Industry research shows that 45-50% of enterprises struggle with feedback loop biases in voice AI. Discover how to avoid echo chambers and ensure diverse, unbiased data collection.
Fail Fast, Speak Fast: Why Iteration Speed Beats Initial Accuracy for AI Agents
The teams winning with AI agents are not the ones with the best v1. They are the ones who improve fastest after launch. Here's how to build a rapid iteration engine for conversational AI.
What HIPAA Taught Us About AI Security (And It Applies to Every Industry)
Healthcare didn't choose to build the most rigorous data security framework in existence. It was forced to. Three decades later, that framework turns out to be the best blueprint for securing AI agents in any industry.
Moving Past "Average Handle Time": New Metrics for Evaluating Conversational AI
Industry research shows that 60-65% of enterprises still rely on Average Handle Time, missing critical conversational AI metrics. Discover the next-generation metrics that drive real business value.
Performance Benchmarks for AI Agents: What Actually Matters Beyond Word Error Rate
Most enterprises obsess over Word Error Rate while missing the metrics that actually predict success. Here's what to measure instead.
What Voice AI Can (and Can't) Learn from Your Best Human Agents
Top human agents do specific things that make them exceptional. Some of those things can be taught to AI. Others can't, at least not yet. Here's an honest breakdown of what transfers and what doesn't.
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