The Harness is a Context Manager on Behalf of the Model What happens when the context window fills up and who decides? This decision is exte…

The Harness is a Context Manager on Behalf of the Model What happens when the context window fills up and who decides? This decision is external to the model - The Harness designer must have some opinion here! Decisions like this are crucial in turning a model into a great product for end users. The context window is a sacred boundary beyond which all model computation actually happens. Context engineering is important because designing what gets passed over this boundary is the main determinant of agent performance. Harness design is how you decide how this boundary gets managed. Our create_agent primitive in LangChain exposes the one of the simplest Harnesses for builders to extend, a ReAct loop with support for tools, middleware (hooks), and model choice It’s a great place to start in agent building because it forces you to think through and contend with all of the design details that transform a simple agent loop into a purpose-built agent for your tasks The first time you hit the context boundary in a simple agent loop, the API will just error out and your agent run will end. The API contract only supports a max number of tokens. A harness helps you get in line with the API contract by managing context via strategies like truncation, compaction, offloading, and targeted context eviction This is just one decision to think about in Harness Design, many more come up as you build such as agent specialization via Subagents, Tool design, Skill design, and more. Each of these are important in extending a model to make it into a useful product for users. create_agent is a great level of abstraction to start building agents. Builders can go up a level to deepagents for a more out of the box agent experience and even further to Fleet as a more out of the box product experience. Or they can go down to the runtime execution level to LangGraph like @caspar_br had talked about starting from a simple harness to build a great agent helps you learn fundamentals of how models work + good design patterns that turn them into great agents and products

Source: Harrison Chase (X) | 2026-05-02