
LangSmith Sandboxes offer secure, isolated environments for agents to run code, ensuring safety and control by isolating each agent's execution. These sandboxes use hardware-virtualized microVMs with their own kernels, persisting state across sessions, and preventing unauthorized access. They provide resource limits, credential management, and lifecycle control to prevent excessive resource consumption. Agents must treat output as untrusted and avoid passing raw output back to models, with non-agentic reads recommended for sensitive workflows. Sandboxes support snapshots, forks, and logging, and managed sandboxes offer a simplified interface for reliable and secure execution.
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.
