LangChain has been using agent abstractions for nearly three years, but these have often fallen short in providing developers with adequate control over context engineering, leading to the introduction of a new abstraction called "Middleware" in LangChain 1.0. The core components of LangChain agents—models, prompts, and tools—are simple, and the agent operates by repeating a loop until it decides to finish. However, as complexity increases, developers need more control over factors like agent state and model inputs to ensure reliability, which previous frameworks struggled to offer. Over the past two years, LangChain has made strides in enhancing the flexibility of its agent abstraction by allowing user specifications for runtime configurations, state schemas, prompts, and message lists, among other features. However, this led to an unwieldy number of parameters with interdependencies. The new Middleware in LangChain 1.0 addresses these challenges by providing hooks to modify the core agent loop, allowing for greater customization and composability. This includes pre- and post-model call hooks and the ability to alter model requests dynamically. Middleware also supports the integration of custom state schemas and tools, streamlining various existing LangGraph agent architectures into a unified framework. The alpha release of LangChain 1.0 invites developers to test Middleware with new implementations such as Human-in-the-loop, Summarization, and Anthropic Prompt Caching, aiming to gather feedback for further improvement.