Articles tagged “testing”
14 articles
Who's Testing Your AI Agent Before It Talks to Customers?
Traditional QA validates deterministic code. AI agent QA must validate probabilistic conversations. Here's why that gap is breaking production deployments.
How to Evaluate AI Agents: Build an Eval Framework from Scratch
Build a working AI agent eval framework in TypeScript and Python. Covers LLM-as-judge, rubric scoring, regression testing, and CI integration.
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.
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.
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.
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.
Voice AI Testing Strategies That Actually Work: A Complete Framework for Production Success
Discover the comprehensive testing framework used by top voice AI teams to achieve 95%+ accuracy rates and prevent costly production failures. Includes real case studies and actionable implementation guides.
Automated QA Grading: Are AI Models Better Call Scorers Than Humans?
Industry research shows that 75-80% of enterprises are implementing AI-powered QA grading systems. Discover whether AI models actually outperform human call scorers and how to implement effective automated grading.
Digital Twins for Agents: Replicating the Best, Avoiding the Worst
Digital twins create virtual replicas of voice AI agents for testing, optimization, and training. Discover how this technology is revolutionizing agent development and deployment.
The Voice AI Quality Crisis: Why 78% of Enterprise Deployments Fail Within 6 Months
McKinsey's 2024 data reveals a shocking truth: 78% of enterprise voice AI deployments fail within 6 months, costing companies an average of $3.2M. Discover the hidden causes and proven solutions.
Voice AI Hallucinations: The Hidden Cost of Unvalidated Agents
Discover how voice AI hallucinations can cost businesses thousands daily and learn proven strategies to detect and prevent them before they reach customers.
The 12 Critical Edge Cases That Break Voice AI Agents
Uncover the most common edge cases that cause voice AI failures and learn how to test for them systematically to prevent customer frustration.
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