The Chanl Blog
Insights on building, connecting, and monitoring AI agents for customer experience — from the teams shipping them.
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235 articles · Page 16 of 20
Your Voice AI Platform Is Only Half the Stack
VAPI, Retell, and Bland handle voice orchestration. Memory, testing, prompt versioning, and tool integration? That's all on you. Here's what to build next.
Your AI agent remembers everything — should your customers be worried?
Privacy-first memory design for AI agents: what to store, what to forget, how to give customers control, and how to stay compliant across GDPR, HIPAA, and multi-channel deployments.
From Analytics to Action: Turning Conversation Data Into Agent Improvements
Most teams collect call data and never use it. Learn how to close the loop from analytics to insight to prompt change to scorecard validation — and actually improve your AI agents.
Gartner Says 80% Autonomous by 2029. Here's What Nobody's Talking About.
Gartner predicts 80% autonomous customer service by 2029. But the gap between today's AI agents and that future requires testing, monitoring, and quality infrastructure most teams don't have.
The Knowledge Base Bottleneck: Why RAG Alone Isn't Enough for Production Agents
RAG works beautifully in demos. In production, stale data, chunking failures, and unscored retrieval quietly sink your AI agents. Here's what actually fixes it.
The MCP Marketplace Problem: Why Standardized Integrations Need Standardized Testing
5,800+ MCP servers, 43% with injection flaws. Standardized protocol doesn't mean standardized quality. Why every MCP integration needs automated testing.
Prompt Engineering Is Dead. Long Live Prompt Management.
Why production AI teams need version control, A/B testing, and rollback for prompts — not just clever writing. The craft has changed.
Real-Time Monitoring for AI Agents: What to Watch and When to Panic
What dashboards actually matter for production AI agents. Alert fatigue, anomaly detection, and the metrics that predict failures before customers notice.
Scenario Testing: The QA Strategy That Catches What Unit Tests Miss
Discover how synthetic test conversations catch edge cases that unit tests miss. Personas, adversarial scenarios, and regression testing for AI agents.
Scorecards vs. Vibes: How to Actually Measure AI Agent Quality
Most teams 'feel' their AI agent is good. Here's how to build structured scoring with rubrics, automated grading, and regression detection that holds up.
The Tool Explosion: Managing 50+ Agent Tools Without Losing Your Mind
As agents get more capable, tool sprawl becomes a real operational problem. Here's how to organize, test, and monitor function calling at scale before it breaks in production.
AI Agent Memory: Build Your Own or Buy Off the Shelf?
Comparing Mem0, Zep, Letta, and custom memory for AI agents. We break down architecture trade-offs, compliance risks, and when each approach makes sense.
Learn Agentic AI
Weekly. Patterns for shipping agents that work — MCP, scorecards, regression tests, prompts, model comparisons.
