LLM Observability

Anthropic recently disclosed Petri, a tool for auditing behavioral drift across 300,000 queries. This highlights a critical reality for developers: LLM behavior is not static, and production monitoring is no longer optional.

Discover how Clay, a leader in GTM automation, manages massive LLM scale using LangSmith for tracing, evaluation, and monitoring while optimizing performance through advanced API strategies.

An in-depth exploration of why agent frameworks remain essential as LLMs evolve, focusing on system architecture, observability, and the importance of high-performance API backends like n1n.ai.