Building trust in AI agents: A production-ready evaluation framework with Amazon Bedrock AgentCore
TL;DR
Autonomous AI agents fail softly: latency stays flat while answer quality quietly erodes. This post shares a nine-stage evaluation framework, built on Amazon Bedrock AgentCore, that catches silent quality regressions across the full agent lifecycle, from first commit to live production.
Nauti's Take
Production agents need evaluation gates at commit, before release, and in live operation. Start with reproducible test cases for answers, tool calls, and failure scenarios, then track cost and data access alongside quality.
AWS offers a useful framework, yet the post itself does not prove that AgentCore will reliably cover every architecture or workload.
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