Deep Agents Core

Build an AI agent with middleware by using the `create_deep_agent` function, which automatically integrates essential middleware for task planning, filesystem access, context management, and sub-agent delegation. It abstracts away complex configuration for multi-step task capabilities.

Middleware integration in an AI agent framework is the process of automatically incorporating essential modules for task planning, context management, memory, and sub-agent delegation. This abstracts away complex configuration, simplifying sophisticated agent creation.

Yes, you can configure custom tools and memory when creating AI agents. The framework offers extensive options for customizing agent behavior, allowing you to add specific tools, manage memory configurations, and define specialized skills.

Use an agent framework with sub-agent delegation when starting any new project that requires an AI agent with multi-step task capabilities, file management, or the ability to spawn specialized sub-agents for sophisticated workflows.

Yes, this AI agent framework works with LangChain. It leverages the LangChain ecosystem and addresses critical fixes for store, backend, and skill file structure requirements to ensure proper agent harness architecture.

Deep agents fail to manage context and planning correctly if the SKILL.md format or harness architecture is improperly configured. The framework addresses critical fixes for store, backend, and skill file structure requirements to ensure proper middleware integration.