11 entries
Keyword: langsmithX post:Swapna Kumar Panda
Swapna Kumar Panda has compiled eleven practical courses focused on agentic AI. The selection covers beginner-friendly tutorials as well as in-depth curricula on LangGraph, Claude Code, enterprise RAG, and multi-agent workflows.
4.8kbookmarks167.5kviews
Repository:langchain-ai/langchain
LangChain is an open-source framework designed for building agents and LLM-powered applications in Python and JavaScript/TypeScript. It provides modular building blocks, third-party integrations, and specialized tools like LangGraph and Deep Agents.
145.7kstarsPython
From Video: AI Weekly Updates: Open-Source Model Surge, Agent Harnesses, and Meta's AI Reality Check
Repository:langchain-ai/langgraph
LangGraph is an open-source orchestration framework by LangChain designed to build, manage, and deploy durable, stateful AI agent workflows with robust memory and human-in-the-loop support.
41.1kstarsPython
From Video: Weekly AI Roundup: DeepSeek Harness, Model Routing, and Scaffolding Shifts
Link:LangChain
LangGraph is an open-source (MIT-licensed) runtime and low-level orchestration framework by LangChain, designed for building stateful, reliable AI agent workflows.
From Video: Weekly AI Roundup: DeepSeek Harness, Model Routing, and Scaffolding Shifts
Article:LangChain Inc.
LangGraph by LangChain Inc. is an orchestration runtime designed for building and managing long-running, stateful AI agents. It enables developers to combine deterministic, hand-coded logic with LLM-driven steps within a single graph. Operating independently of the core LangChain library, LangGraph emphasises durable execution, state persistence, and human-in-the-loop controls.
From Video: Weekly AI Updates: Model Releases, Agent Harnesses, and Developer Tooling (August 2026)
Link:LangChain
LangChain introduces Deep Agents, an open source agent harness built for long-running, autonomous workflows with native planning, context handling, and subagent orchestration.
Article:Victor Moreira
LangChain has announced Managed Deep Agents, an API-first hosted runtime in LangSmith designed for long-running AI agents. Developers can maintain agent configurations in their own repositories while LangSmith manages execution, state persistence, sandboxes, and context.
Article:Jacob Talbot
At its Interrupt conference, LangChain announced a range of updates to LangSmith, including the autonomous LangSmith Engine, the trace-optimised SmithDB database, Managed Deep Agents, general availability for secure Sandboxes, Context Hub, an LLM Gateway, and updates to LangSmith Fleet.
Link:langchain.com
LangChain outlines its end-to-end platform for building, testing, deploying, and operating AI agents. Alongside open-source frameworks like LangGraph and Deep Agents, the offering features tools such as LangSmith Engine and an LLM Gateway for governance.
From Video: Weekly AI Roundup: DeepSeek Harness, Model Routing, and Scaffolding Shifts
Link:docs.langchain.com
The official LangChain documentation homepage provides an overview of the tools and services covering the entire AI agent development lifecycle.
From Video: Cognition President Russell Kaplan on Coding Agents, Benchmarks, and Model Routing
VideoVideo:AI Engineer
Nick Ung and Akshay Sharma from Lyft present an end-to-end framework for evaluating customer support AI agents. They detail why default offline simulations produce misleading pass rates and show how fine-tuned adversarial user simulators and calibrated LLM judges create trustworthy benchmarks.
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