
Harrison Chase argues that companies must own the specific details and systems that define AI behavior, such as models, agent systems, context, and memory, to gain a lasting advantage. Generic AI lacks the unique aspects needed for effective operations, like policy language, regulatory requirements, and customer tiering. To own intelligence, companies need to control the agent system, including the model, harness, and context, and manage the feedback loop to improve AI performance over time. The strategic choice is to own the intelligence that compounds over time, rather than relying on generic infrastructure.
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.
