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Lead Story
Deep Agents v0.7
Today we're shipping deep agents v0.7. This release simplifies the base harness, resulting in 65% fewer base input tokens at comparable performance.
LangChain Blog / 5:12 AM
Own Your Intelligence: The Key to Lasting AI Advantage
Learn why companies must own their agent systems, governance, context, and feedback loops to turn generic AI into lasting business advantage.
LangChain Blog / 5:12 AM
Full Text Search in SmithDB: Designing an Inverted Index for Object Storage
SmithDB supports full-text search and JSON filtering over agent traces with a median (P50) latency of 400 ms, even though the underlying data consists of large, deeply nested JSON documents stored in object storage.
LangChain Blog / 2:31 AM
How We Benchmark Deep Agents
We revamped how we benchmark Deep Agents. Here's the eval setup we run in Harbor across coding, conversation, and retrieval, and how we use it to ship changes.
LangChain Blog / 7:36 AM
How Schneider Electric Built Their LLMOps Foundations With LangSmith
Learn how Schneider Electric built enterprise LLMOps foundations with LangSmith to improve observability, evaluation, and deployment for AI products at scale.
LangChain Blog / 12:50 PM
3 Years of Graph Engineering with LangGraph
Graph engineering isn't a new idea. It's the latest name for a well established approach to building reliable agents. It's the same idea behind loop engineering and harness engineering: building putting model reasoning in the right places, with the right context, at each step. At LangChain, we've been helping people build agents with graphs for 3 years! Here's what we've learned.
LangChain Blog / 6:11 PM
Building Governed Agents: A Framework for Cost, Control, and Compliance
The gateway is the runtime control plane for enterprise AI, turning policy into enforceable decisions across every model call, tool call, and agent hop.
LangChain Blog / 6:36 PM
IssueBench - How We Evaluate Engine
Learn how LangChain built IssueBench, a synthetic benchmark for evaluating how well LangSmith Engine identifies, categorizes, and groups issues in agent traces.
LangChain Blog / 10:35 PM
Deep Agents Code on NVIDIA NemoClaw
Run Deep Agents Code on NVIDIA NemoClaw with deny-by-default networking, human approval, and audit logs for sensitive code modernization.
LangChain Blog / 10:35 PM
LangChain and NVIDIA Launch NemoClaw Deep Agents Blueprint
LangChain and NVIDIA launch the NemoClaw Deep Agents blueprint, combining Deep Agents Code, Nemotron 3 Ultra, and OpenShell for open, governed enterprise agents.
LangChain Blog / 10:35 PM
Your coding agent bill doubled. Here’s how to fix it.
Learn why coding agent bills spiral out of control — and how to trace, compare, and govern spend across Claude Code, Cursor, Copilot, and more in one place.
LangChain Blog / 1:27 AM
Benchmarking Agent Tool Use
Benchmark LLM tool use with 4 test environments. Compare GPT-4, Claude, and open-source models on function calling, planning, and reasoning tasks.
LangChain Blog / 1:27 AM
Extraction Benchmarking
Compare GPT-4, Claude, and open-source LLMs on structured data extraction from chat logs. Benchmark results, evaluation metrics, and dataset creation insights.
LangChain Blog / 6:59 PM
How we built SmithDB’s inverted index for full-text search
A technical deep dive into how LangChain built full-text search in SmithDB, from constructing and compacting inverted indexes to routing queries across local SSD and object storage.
LangChain Blog / 12:21 AM
How LangSmith and LangChain OSS Help You Meet EU AI Act Requirements
The EU AI Act compliance deadline is August 2, 2026. Learn what the EU AI Act requires, and how LangSmith and LangChain OSS products help you meet each requirement.
LangChain Blog / 7:00 PM
Testing Fine Tuned Open Source Models in LangSmith
Evaluate and compare fine-tuned open source LLMs using LangSmith. Test multiple models, automate evaluations, and choose the best performing AI.
LangChain Blog / 5:40 PM
On Agent Frameworks and Agent Observability
Learn why agent frameworks still matter in 2026 and how LangSmith provides observability for any framework, including LangChain, Claude SDK, and custom-built agents.
LangChain Blog / 5:40 PM
Build and deploy a RAG app with Pinecone Serverless
Build production-ready RAG apps with Pinecone Serverless, LangChain, and LangServe. Deploy scalable AI with usage-based pricing and observability.
LangChain Blog / 5:40 PM
Introducing End-to-End OpenTelemetry Support in LangSmith
LangSmith now provides end-to-end OpenTelemetry (OTel) support for applications built on LangChain and/or LangGraph.
LangChain Blog / 8:06 AM
How Box AI built enterprise content agents with Deep Agents
See how Box built Box Agent on Deep Agents to search, analyze, and synthesize enterprise content while preserving security, permissions, and model flexibility.
LangChain Blog / 2:31 AM
July 2026: LangChain Newsletter — NemoClaw Blueprint, OpenWiki Brains, and More
NemoClaw Deep Agents blueprint, LangSmith Sandboxes free trial, Fleet Slack integration, voice tracing, OpenWiki Brains, and RLMs in Deep Agents. See what's new at LangChain
LangChain Blog / 7:36 AM
Eval Engineering Skill: Build Evals From Repo Context and Traces
LangChain's Eval Engineering Skill inspects your agent's repo and traces, proposes evals through user interviews, and outputs runnable Harbor tasks.
LangChain Blog / 11:48 PM
How Apollo Uses Deep Agents and LangSmith for GTM AI
Apollo uses Deep Agents and LangSmith to power an AI Assistant that handles prospecting, enrichment, outreach, analytics, and MCP integrations.
LangChain Blog / 11:48 PM
Agents need their own computer. Here's how to give them one safely.
For most of computing history, a developer environment meant a physical machine, then a VM, then a container, with each one shared across the work happening on it, each one requiring deliberate setup and teardown. The idea of giving every agent its own isolated computer, booting in under a second and cleaning up when done wasn't practical at scale. Sandboxes give you a safer way to run upgraded workflows, providing you an isolated environment to run tasks that require iteration, verification, and access to the tools a person would normally use, all without requiring human supervision. Every human developer gets a laptop. Every agent can get a computer.
LangChain Blog / 4:02 PM
Trace voice agents in LangSmith
LangSmith now supports tracing for voice agents built with Pipecat, LiveKit, OpenAI Realtime, and Gemini Live. Capture audio, STT and TTS latency, interruptions, tool calls, and more in one trace.
LangChain Blog / 6:46 PM
New in Fleet: Deploy AI agents to Slack in one click
Build custom AI agents in Fleet without code, then deploy them to Slack in one click. Give agents custom identities, use them in channels and threads, and keep work moving where your team already collaborates.
LangChain Blog / 6:46 PM
OpenWiki 0.2 brings OKF to codebase documentation
OpenWiki 0.2 generates codebase wikis in the OKF format, helping developers organize repo docs with metadata, changelogs, and agent-friendly retrieval.
LangChain Blog / 3:40 AM
How to Debug Coding Agents with LangSmith Traces
Use LangSmith to trace coding agents across Claude Code, Codex, Cursor, Copilot, and more. Inspect tool calls, subagents, errors, costs, and retries.
Latest story in this edition: 5:00 PM
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