Articles tagged “quality-assurance”
14 articles
Memory bugs don't crash. They just give wrong answers.
Memory bugs don't crash your agent. They just give subtly wrong answers using stale context. Here are 5 test patterns to catch them before customers do.
AI Agents Are Great. Until They're Not. When to Put Humans Back in Control
AI agents can handle 80% of your customer interactions with no problem. The other 20% is where your reputation is made or broken. Here's how to design escalation that actually works.
Your Agent Passed Every Dev Test. Here's Why It'll Fail in Production
A 4-layer testing framework for AI agents (unit, integration, performance, and chaos testing) so your agent survives real customers, not just controlled demos.
Is Your AI Agent Actually Ready for Production? The 3 Tests Most Teams Skip
Most AI agent failures happen not because the agent is bad, but because it was never properly tested. Here's the testing framework (unit, A/B, and live) that catches what demos miss.
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.
Voice AI Can Read Your Mood — Here's What That Changes
How emotion-aware voice AI detects customer sentiment in real time, adapts responses, and cuts escalations by 25-40% — plus the ethics you can't ignore.
The Multilingual Voice AI Challenge: Breaking Language Barriers While Maintaining Quality
Explore the technical complexities of multilingual voice AI including accent adaptation, cultural context, and quality assurance across languages.
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.
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.
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.
Testing Bias: How to Measure and Reduce Socio-linguistic Disparities in AI
A practical guide to detecting and measuring bias in AI voice and chat agents. Covers specific metrics, testing approaches, scorecard design, and what teams actually do when they find disparities.
Learn Agentic AI
One lesson a week — practical techniques for building, testing, and shipping AI agents. From prompt engineering to production monitoring. Learn by doing.
