Articles tagged “best-practices”
14 articles
7 FastMCP mistakes that break your agent in production
FastMCP servers that work locally often fail at scale. Seven common mistakes, from missing annotations to monolithic tool sets, and how to fix each one.
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.
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.
Smarter Escalation: When Should Voice AI Refuse to Answer?
Industry research shows that 60-65% of enterprises struggle with AI escalation decisions, leading to customer frustration and compliance risks. Discover when voice AI should refuse to answer and how to build smarter escalation frameworks.
How AI Voice Systems Handle Accents (And Why Most Get It Wrong)
AI voice systems still fail millions of speakers with non-standard accents. Here's why that happens, what inclusive voice design actually looks like, and how to build agents that understand everyone.
How callers actually think about AI — and where every assumption breaks
Industry research reveals that 60-65% of callers develop incorrect mental models of AI systems. Discover how understanding caller psychology transforms voice AI design and reduces frustration.
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.
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.
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.
Can AI learn to apologize? The uncomfortable truth about synthetic empathy
Industry research shows that 55-60% of enterprises are exploring synthetic empathy in AI systems. Discover the ethical implications and practical applications of AI emotional intelligence.
Voiceprint Spoofing and Security: Defending Against Synthetic Voice Fraud
Industry research shows that 80-85% of enterprises lack adequate protection against voiceprint spoofing attacks. Discover comprehensive strategies for defending against synthetic voice fraud.
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