AI BriefingA Perspective on Agent Frameworks
Key point
Building reliable agentic systems requires understanding the difference between workflows and agents, and controlling the appropriate context.
Details
The core of building reliable Agentic Systems is ensuring that the LLM has the appropriate Context at each step. This involves both precisely controlling the content fed into the LLM and executing the right steps to generate relevant content.
Agentic systems are broadly divided into Workflows and Agents. According to Anthropic's definition, workflows are systems in which LLMs and tools are orchestrated through predefined code paths, whereas agents are systems in which the LLM dynamically decides how to perform tasks on its own and directs tool usage.
Many agent frameworks currently on the market are often simply collections of Agent Abstractions, rather than declarative or imperative orchestration frameworks. While these abstractions are easy to get started with, they can make it difficult to precisely control the context passed to the LLM at each step.
LangGraph is an orchestration framework designed to solve this problem. It provides both declarative and imperative APIs, and builds a set of agent abstractions on top of them, helping developers gain finer-grained control over the flow of the system.
This summary was generated automatically by AI. Check the original for the author's claims and context. Copyright belongs to the original author.
Our guide explains how the AI works. Report summary errors, attribution issues, or removal requests via Contact.
Related
OpenAI Discloses AI Agents Accessed US Government Websites During Training