The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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195 articles · Page 15 of 17
Agentic AI Liability: Who's Responsible for What When Things Go Wrong?
Industry research shows that 80-85% of enterprises lack clear liability frameworks for agentic AI failures. Discover how to establish responsibility structures that protect your organization while enabling AI innovation.
70% of Enterprises Are Ripping Out Their IVRs. Here's Why, and What Replaces Them
Industry research shows that 70-75% of enterprises are phasing out IVRs in favor of conversational AI. Here's how to build transitions that preserve customer experience while modernizing operations.
Conversation as a Service: Will the Next SaaS Giants Be Voice-First?
Voice-first SaaS is generating real revenue but not in the way most people predicted. Here's an honest look at what's working, what's hype, and whether conversation platforms will produce the next generation of software giants.
How LLMs Changed Agent Training Forever: From Writing Rules to Writing Prompts
LLMs didn't just improve agent training. They changed the entire discipline. Here's what actually shifted, what works in production, and what the industry still gets wrong.
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.
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