In many ways… this is also similar to agents! Just as we are seeing the rise of **vertical** agents, we also think that we will see the rise of **vertical** memory
@hwchase17
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Defining Memory in AI Applications: Beyond the Hype
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The idea of memory is tantalizing, but also really vague What does it even mean for an application to have memory? Much like agents, there's a lot of hype and interest in this area, without a clear definition of what is actually means
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Application-Specific Memory Implementation in AI Systems
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We saw that applications that successfully implemented memory were implementing it in an application specific way A coding app may care about a users language, preferred libraries, and proficiency level A companion app may care about a users name, age, friends, etc
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LangGraph Introduces Long-Term Memory Support for Agents
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We're launching "long-term memory" support in LangGraph At its core, long-term memory is "just" a persistent document store that lets you *put*, *get*, and *search* for memories you've saved Why so simple?
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LangGraph Launches Long-Term Memory Support for AI Agents
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We put a lot of efforts into some great resources around this launch! Memory is a under explored and very open ended topic… more than anything, we wanted to share how we are thinking about it and get feedback Blog post: https://
blog.langchain.dev/launching-long
-term-memory-support-in-langgraph/
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Conceptual docs: -
LLM Agency: How Agentic Applications Control Their Flow
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The more agentic an application is, the more an LLM decides the control flow of the application
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Building AI Agents with LangGraph and LangSmith
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Interesting thread that mirrors how we see agents being built: 1. Break complicated task into a highly controllable domain specific workflow (LangGraph) 2. Test each component thoroughly (LangSmith)
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Voice Agents with ReAct Architecture and LangChain Tools
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Excited to start exploring voice agents! Some notes: – ReAct style architecture is the only "cognitive architecture" that is really support – tough to customize the agent logic
– But thats fine! ReAct agents are still good!
– Can use all existing LangChain tools easily -
Replit Agent Fireside Chat with President Pirroh
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Doing a live fireside chat with @pirroh (President, Replit) about their Replit Agent in ~2 hrs If you could ask him anything, what would you want to know?
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Language Agents: From Reasoning to Acting with Shunyu Yao
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Language Agents: From Reasoning to Acting Went to Latent Space podcast as a guest cohost to interview @ShunyuYao12 Shunyu's ReAct paper was a big part of initial LangChain, so was fun to dive deep into that (among other things!)