Articles tagged “agent-evaluation”
5 articles
LLM judges grade your agents wrong. Here's how to fix them.
LLM judges are the only practical way to evaluate agents at production scale, but they have predictable biases that give you false confidence. Here's how to calibrate them so the scores you see reflect the quality you actually have.
Testing AI agent handoffs before they break in production
Multi-agent CX systems fail at the seam between agents. Here's how to build handoff tests that catch context loss, duplicate actions, and loop failures before your customers feel them.
Synthetic Users: Test Your Agent Against AI Personas
Scripted tests catch only the failures you anticipated. Build AI-powered synthetic users that simulate real customers and break your agent before it ships.
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.
Tu agente de IA, esta realmente listo para produccion? Las 3 pruebas que la mayoria de los equipos se saltan
La mayoria de las fallas en agentes de IA no ocurren porque el agente sea malo, sino porque nunca fue probado correctamente. Aqui esta el framework de pruebas (unit, A/B y en vivo) que detecta lo que las demos no muestran.
El briefing de Signal
Un email por semana. Cómo los equipos líderes de CS, ingresos e IA están convirtiendo conversaciones en decisiones. Benchmarks, playbooks y lo que funciona en producción.
