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:
@langchain
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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 -
LangSmith Named Among Brex’s Top 25 Fastest-Growing Software Vendors
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We’re excited to share that LangSmith, the agent engineering platform for observability, evaluation, and deployment, has been named one of @brexHQ's Top 25 Fastest-Growing Software Vendors of 2025 🎉 https://t.co/qn6I37d72A
— LangChain (@LangChain) 17 décembre 2025We’re excited to share that LangSmith, the agent engineering platform for observability, evaluation, and deployment, has been named one of @brexHQ
's Top 25 Fastest-Growing Software Vendors of 2025 -
Fastweb and Vodafone Deploy Agentic Customer Service at Scale
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Fastweb + Vodafone (Swisscom Group), one of Europe’s leading telecom providers, is building Super TOBi, which brings agentic customer service to massive scale. Using LangSmith, they are: Achieving 90% response correctness and 82% resolution rates across ~9.5M customers
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State of Agent Engineering Report Released
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Read the full report here https://
bit.ly/state-of-agent
-engineering
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