Exploring the Importance of Agent Infrastructure for Modern Applications

In the rapidly evolving world of technology, the role of agent infrastructure has become increasingly significant. As applications evolve from simple request-response models to more complex, agentic systems, the need for robust infrastructure to support these advancements is crucial, according to the LangChain Blog.

The Rise of Agentic Applications

Over the past year, there has been a noticeable rise in agentic applications. These applications, ranging from workflow copilots to code generation assistants, utilize a combination of tools, memory, and reasoning to accomplish complex, multi-step tasks. This evolution marks a departure from traditional app models, which were primarily focused on retrieval and chat functions, to systems capable of action-taking and reasoning.

These agentic applications redefine how we perceive traditional applications, moving beyond mere input forms and chat interfaces. They operate in the background, processing events and information, and are capable of asking for assistance, showcasing their work, reasoning through problems, and collaborating in groups. However, the traditional stateless, serverless compute models fall short when it comes to supporting these agent-based applications, necessitating a new infrastructure.

Why Agent Infrastructure Matters

The unique demands of agentic workloads require new primitives that traditional web backends and distributed systems fail to provide. This has led to the emergence of a new layer in the tech stack: agent infrastructure. This infrastructure sits between the agent logic and raw compute resources, providing essential structure, control, and reliability.

Agent infrastructure is designed to support durable execution, complex state management, human-in-the-loop coordination, and streaming, without the need for developers to manually assemble these components. The LangGraph Platform is an example of such an infrastructure, designed to deploy and run LangGraph applications efficiently and reliably.

Key Features of Agent Infrastructure

Agent infrastructure offers several critical features:

• Durable Execution: Agent runs can last from seconds to hours, pausing for tool calls, API waits, or human feedback. Infrastructure like LangGraph ensures these processes are safely resumed, preventing timeouts or crashes.
• State Management: Agents require more than just message buffers; they need structured state storage to persist across steps and failures. Agent infrastructure provides this capability out-of-the-box.
• Human-in-the-loop Coordination: Agents often rely on human input for decisions, necessitating a system that supports resumable states and long delays.
• Bursty Concurrency: Real-world applications face unpredictable surges in demand, which can overwhelm traditional systems. Agent infrastructure can handle these spikes through task queues and horizontal auto-scaling.
• Streaming: Agents think and refine their responses over time. Good infrastructure allows for token-level streaming and custom data streaming, enhancing user experience and developer visibility.

LangGraph Platform: A Solution for Agentic Workloads

The LangGraph Platform provides the necessary infrastructure to run agentic workloads in production without the need for extensive custom development. It supports long-running execution, checkpointing, retries, memory management, streaming, and traffic handling out of the box. Developers can deploy agents directly from GitHub with a single click, allowing them to focus on agent logic rather than infrastructure complexities.

The future of application development is agentic, requiring a solid foundational infrastructure to support this shift. Agent infrastructure is the missing layer that enables developers to build beyond traditional stateless prompts, ensuring robust and reliable application performance.

For more detailed insights, visit the LangChain Blog.