Building reliable AI agents requires treating them as distributed systems, not just better models. The ReAct (Reasoning and Action) pattern forms the foundation: observe, think, act, verify, repeat. On top of that, production-grade reliability requires verification layers that check post-conditions after every action, guardrails that constrain what agents can access and do, human-in-the-loop escalation for uncertain or risky decisions, and observability through distributed tracing. Amazon Nova Act is used as a case study, demonstrating how this layered architecture achieves ~90% reliability at scale for browser automation workflows. The SDK allows Python-based workflow definitions deployable to AWS with CloudWatch monitoring and IAM access control.
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