
Skills are dynamic, modular instructions that enhance agent performance in specialized domains, loaded progressively to optimize resource use. Testing involves evaluating skill effectiveness through controlled environments and performance comparisons, with best practices emphasizing modular design, consistent environments, and metrics like skill invocation. Evaluating skills requires systematic approaches, including task definition, metric tracking, and observability tools like LangSmith to ensure reliable performance and failure analysis.
Managed Deep Agents gives developers a managed way to build, run, and deploy Deep Agents with built-in runtime, streaming, sandboxes, evals, memory, and auth.

LangSmith Bring Your Own Cloud is now generally available on AWS, giving Enterprise teams managed observability, evaluation, and deployment inside their own VPC.

Learn what AI agents are, how they work in an LLM loop, and where workflows fit so you can build reliable, production-ready autonomous systems.
