LangChain Integration Docs: Find information faster with revamped pages & API references See the latest updates to the LangChain integration docs, including a new standardized format and improved API references that can help you find relevant information faster.
UX for Agents, Part 3: Spreadsheet, Generative, and Collaborative UI/UX Learn about spreadsheet UX for batch agent workloads, Generative UI, and collaborative UX with agents.
LangGraph v0.2: Increased customization with new checkpointer libraries LangGraph v0.2 includes new checkpointer libraries for increased customization — including a SQLite checkpointer for local workflows and an optimized Postgres checkpointer to take your app to production. Plus, learn about LangGraph Cloud in open beta.
Dynamic few-shot examples with LangSmith datasets With dynamic few-shot examples in LangSmith, you can Index examples in your datasets in one click and dynamically select the most relevant few-shot examples based on user input. This lets you rapidly iterate and improve LLM app performance.
UX for Agents, Part 2: Ambient This is our second post focused on UX for agents. We discuss ambient background agents, which can handle multiple tasks at the same time, and how they can be used in your workflow.
LangGraph Studio: The first agent IDE LangGraph Studio provides a specialized agent IDE for visualizing, interacting with, and debugging complex agentic applications. See how to use it on your desktop today.
Dataset schemas for fast and iterative data curation in LangSmith Define and flexibly manage dataset schemas in LangSmith. Validate examples against a defined schema, and update the schema easily in the LangSmith UI.
UX for Agents, Part 1: Chat At Sequoia’s AI Ascent conference in March, I talked about three limitations for agents: planning, UX, and memory. Check out that talk here. In
Few-shot prompting to improve tool-calling performance We ran a few experiments, which show how few-shot prompting can significantly enhance model accuracy - especially for complex tasks. Read on for how we did it (and the results).
How Athena Intelligence optimized research reports with LangSmith, LangChain, and LangGraph See how an AI-powered employee for enterprise analytics used the LangSmith playground and debugging features to quickly identify LLM issues and to generate complex research reports.
Planning for Agents The fourth installment in our "In the Loop Series," in which we talk about what planning means for an agent and how to improve it.
Improving core tool interfaces and docs in LangChain See our latest improvements to our core tool interfaces that make it turn any code into a tool, handle diverse inputs, enrich tool outputs, and handle tool errors effectively.
