Update README.md (#831)

README.md

@@ -21,8 +21,7 @@ LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [A
 
 ### Why use LangGraph?
 
-LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. LangGraph provides fine-grained control over both the flow and state of your agent applications. It implements a central [persistence layer](https://langchain-ai.github.io/langgraphjs/concepts/persistence/), enabling features that are common to most agent architectures:
-
+LangGraph powers [production-grade agents](https://www.langchain.com/built-with-langgraph), trusted by Linkedin, Uber, Klarna, GitLab, and many more. LangGraph provides fine-grained control over both the flow and state of your agent applications. It implements a central [persistence layer](https://langchain-ai.github.io/langgraphjs/concepts/persistence/), enabling features that are common to most agent architectures:
 - **Memory**: LangGraph persists arbitrary aspects of your application's state,
 supporting memory of conversations and other updates within and across user
 interactions;
@@ -358,6 +357,10 @@ Then we define one normal and one conditional edge. Conditional edge means that
 * [API Reference](https://langchain-ai.github.io/langgraphjs/reference/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
 * [LangGraph Platform](https://langchain-ai.github.io/langgraphjs/concepts/#langgraph-platform): LangGraph Platform is a commercial solution for deploying agentic applications in production, built on the open-source LangGraph framework.
 
+## Resources
+
+* [Built with LangGraph](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship powerful, production-ready AI applications.
+
 ## Contributing
 
 For more information on how to contribute, see [here](https://github.com/langchain-ai/langgraphjs/blob/main/CONTRIBUTING.md).

libs/langgraph/README.md

@@ -21,8 +21,7 @@ LangGraph is inspired by [Pregel](https://research.google/pubs/pub37252/) and [A
 
 ### Why use LangGraph?
 
-LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. LangGraph provides fine-grained control over both the flow and state of your agent applications. It implements a central [persistence layer](https://langchain-ai.github.io/langgraphjs/concepts/persistence/), enabling features that are common to most agent architectures:
-
+LangGraph powers [production-grade agents](https://www.langchain.com/built-with-langgraph), trusted by Linkedin, Uber, Klarna, GitLab, and many more. LangGraph provides fine-grained control over both the flow and state of your agent applications. It implements a central [persistence layer](https://langchain-ai.github.io/langgraphjs/concepts/persistence/), enabling features that are common to most agent architectures:
 - **Memory**: LangGraph persists arbitrary aspects of your application's state,
 supporting memory of conversations and other updates within and across user
 interactions;
@@ -358,6 +357,10 @@ Then we define one normal and one conditional edge. Conditional edge means that
 * [API Reference](https://langchain-ai.github.io/langgraphjs/reference/): Review important classes and methods, simple examples of how to use the graph and checkpointing APIs, higher-level prebuilt components and more.
 * [LangGraph Platform](https://langchain-ai.github.io/langgraphjs/concepts/#langgraph-platform): LangGraph Platform is a commercial solution for deploying agentic applications in production, built on the open-source LangGraph framework.
 
+## Resources
+
+* [Built with LangGraph](https://www.langchain.com/built-with-langgraph): Hear how industry leaders use LangGraph to ship powerful, production-ready AI applications.
+
 ## Contributing
 
 For more information on how to contribute, see [here](https://github.com/langchain-ai/langgraphjs/blob/main/CONTRIBUTING.md).