AI News
16,588 stories from 2775 sources · 1268 in the last 24 hours · refreshed hourly. Every story links to the original publisher.
Today's AI news from trusted publishers and official AI lab blogs, refreshed about every 30 minutes.
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- How to build evidence-grounded agent memory with OpenWiki and GraphsLangChain · toolsLangChain used OpenWiki, its open-source wiki compiler, and an evidence graph to build a persistent memory layer that preserves knowledge for agents to reuse across tasks. Learn how.
- How We Built Our Design AgentLangChain · toolsHow LangChain built Content Studio, an open-source design agent in Slack that makes on-brand videos, graphics and decks, and the harness that powers it.
- Context Engineering (Agent Memory) for AI Agents Starts with RetrievalLangChain · toolsAgents waste time and context on clumsy searches, oversized results and stale data. Learn the retrieval techniques LangChain s Deep Agents harness uses to get the right context in.
- LangSmith LLM Gateway: Runtime Controls for AgentsLangChain · toolsLangSmith LLM Gateway is in public beta: spend caps, rate limits, model fallbacks and PII redaction for production agents, without provider lock-in.
- How Numan Built an Eval-First AI Health Coach with LangGraph and LangSmithLangChain · toolsHow Numan built Nu, an AI health coach, on LangGraph and LangSmith with per-category evals, simulated conversations, and safety gates on a regulatory line.
- October 2026 LangChain Newsletter: Everything we shipped at Interrupt NYC & LondonLangChain · toolsWhat we shipped at Interrupt NYC and London: LangSmith AI Search, Engine v2, Trajectories, Custom Apps, Fine-Tuning, and Managed Deep Agents v0.9.
- Context Engineering with Deep Agents: How To Remember Without Keeping Everything In ContextLangChain · toolsLong-running agents degrade as context piles up. Learn how offloading, summarization, skills, subagents, and memory keep your agent s context window focused.
- The Most Common Questions About Agent Evals, AnsweredLangChain · toolsWhere to start with agent evals, offline vs online evals, evaluator types, LLM judges, benchmarks with Harbor, multi-turn evals, and keeping costs down.
- Open SWE: An Open-Source Framework for Internal Coding AgentsLangChain · toolsBuilt on Deep Agents and LangGraph, Open SWE provides the core architectural components for internal coding agents.
- Improving Deep Agents with harness engineeringLangChain · toolsHarness engineering improved LangChain s coding agent from Top 30 to Top 5 on Terminal Bench using self-verification, tracing, and context optimization.
- Context Management for Deep AgentsLangChain · toolsLearn how Deep Agents SDK manages context for long-running AI tasks through offloading, summarization, and filesystem abstraction to prevent context rot.
- Open Models have crossed a thresholdLangChain · toolsOpen models like GLM-5 and MiniMax M2.7 now match closed frontier models on core agent tasks — file operations, tool use, and instruction following — at a fraction of the cost and latency. Here s what our evals show and how to start using them in Deep Agents.
- Deep Agents Deploy: an open alternative to Claude Managed AgentsLangChain · toolsToday we’re launching Deep Agents deploy in beta. Deep Agents deploy is the fastest way to deploy a model agnostic, open source agent harness in a production ready way.
- How We Made Our Docs Test ThemselvesLangChain · toolsStale code samples are a docs problem nobody prioritizes. Here s how we used the Deep Agents CLI to automate migrating inline code into testable, CI-ready examples
- MCP in LangChain: Stateless Protocol, Elicitation, and More!LangChain · toolsMCP support now lives in langchain.mcp, built on FastMCP for the 2026-07-28 spec, with elicitation handled as a LangGraph interrupt and tool lists cached.
- How Orange Business Built Live Intelligence with LangChain and LangSmithLangChain · toolsLearn how Orange Business used LangChain and LangSmith to build Live Intelligence, a governed AI platform for agents, evals, observability, and production scale.
- Search agent traces by behavior with AI Search in LangSmithLangChain · toolsAI Search in LangSmith is a new way to query traces using natural language. Describe the behavior you re looking for, and LangSmith returns the traces where it happened.
- Building Long-Running Agents with ScaleDown and Deep AgentsLangChain · toolsUse ScaleDown s constrained decoding models with LangChain and Deep Agents to summarize history, compress tool results, and extract data faster and cheaper.
- How to build great out-of-the-box user experiences with Managed Deep AgentsLangChain · toolsManaged Deep Agents includes a new API for managing reactions for your distributed agents, and a system to dynamically assign emoji responses with your instrument of choice. Learn more.
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