LangAlpha: AI Equity Analysis Platform Made by the LangChain Community LangAlpha automates equity research from queries. Using LangGraph's multi-agent system, agents synthesize market data, news, and financials into institutional-grade reports in minutes. Check out the
@langchain
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Production-Ready AI Agents with Persistent Storage and Memory Patterns
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Oracle AI Developer Hub Production-ready AI agents with persistent storage. Six memory patterns for LangChain agents using Oracle AI Database for scalable context management, plus RAG with evaluation frameworks. Repository: https://
github.com/oracle-devrel/
oracle-ai-developer-hub/blob/main/notebooks/memory_context_engineering_agents.ipynb
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Made by the LangChain -
Serverless Deep Agent with LangGraph on AWS Bedrock
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Serverless Deep Agent with LangGraph Thomas builds a stateful AI agent on AWS Bedrock AgentCore, solving state management with LangGraph's checkpointing and langgraph-checkpoint-aws integration. Watch the full tutorial: https://
youtube.com/watch?v=N7Fpo6
npQZA
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Made by the LangChain -
zkStash SDK: Persistent Memory for AI Agents
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Persistent Memory with zkStash SDK Made by the LangChain Community zkStash is a TypeScript SDK for persistent memory in AI agents. Integrates with LangChain via MCP tools or middleware, using Zod schemas for structured storage of preferences and conversations. Docs:
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Building Enterprise Agents with Deep Agents and Runloop
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Building Enterprise Agents with Deep Agents Learn to build and deploy enterprise AI agents using Deep Agents and Runloop. Uses Runloop to run code safely in sandboxes Watch the full tutorial: https://
youtube.com/watch?v=rj5OhG
ujPoE
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Made by the LangChain Community -
Managing Deepagents Memory: Learning and Reflection Over Time
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Managing Deepagents Memory Memory allows agents to learn tasks, knowledge, or preferences over time. Here, we overview two ways to update Deepagent-CLI memory: direct instruction and reflection over past Deepagent sessions. : https://
youtu.be/3aS1A-0775s -
Build Your First AI Agent: Workshop for Women Builders
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Ready to build your first AI agent? Join @langchain x @TavilyAI on Feb 5th at Herald Square for an evening dedicated to women and gender-diverse builders. In this hands-on workshop, you will build and deploy your own AI agent, no coding required. What’s in store:
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New LangChain Academy Course: Building Agents with Python
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🔗 New LangChain Academy Course: Introduction to LangChain (Python) 🔗
— LangChain (@LangChain) 18 décembre 2025
Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider.
In this course, you’ll create agents that can reason, use tools, and take… pic.twitter.com/ixcarxVJ1BNew LangChain Academy Course: Introduction to LangChain (Python) Learn how to build with LangChain – our open source framework that makes it easy to start building agents with any model provider. In this course, you’ll create agents that can reason, use tools, and take
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Pairwise Annotations: Preferences Over Scores for Agent Evaluation
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⚖️ Pairwise Annotations: Scores are hard, preferences are easy.
— LangChain (@LangChain) 17 décembre 2025
Agents handle tasks that are tough to score but easy to compare: support responses where tone matters, code refactors where both work but one feels cleaner, product specs where "good" is subjective.
In practice,… pic.twitter.com/SEvnmXTEcZPairwise Annotations: Scores are hard, preferences are easy. Agents handle tasks that are tough to score but easy to compare: support responses where tone matters, code refactors where both work but one feels cleaner, product specs where "good" is subjective. In practice,
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LangSmith Tracing with Claude Code Agents Feedback Loop
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LangSmith + Claude Code / Deepagents Pairing LangSmith tracing w/ code agents provides a powerful feedback loop. Here, we show examples of that w/ langsmith-fetch + Claude Code / Deepagents. langsmith-fetch CLI: https://
github.com/langchain-ai/l
angsmith-fetch
… : https://
youtu.be/zpgFl4N4DIc