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.
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.
Learn Agentic AI
Weekly. Patterns for shipping agents that work. MCP, scorecards, regression tests, prompts, model comparisons.
