On Agent Frameworks and Agent Observability

Agent frameworks remain essential for building with LLMs, evolving through generations from simple chaining (`langchain`) to flexible orchestration (`langgraph`) and autonomous harnesses (`deepagents`). Recognizing that quality and debugging are the biggest barriers to production, the LangSmith observability platform was intentionally built to be independent of any single framework. This framework-agnostic design allows any developer to analyze their agent's behavior, as its true logic is documented in detailed traces rather than just code. These traces are the foundation for understanding and monitoring non-deterministic AI systems, making observability a critical part of the building process itself.