Blogsby GlyphNov 12
How our GTM Agent builds consistent, high-quality sales artifacts
Learn how LangChain built GTM Agent on Deep Agents to build high-quality, custom sales artifacts trained on business context.
LangChain Blog the company blog of LangChain: latest posts and feed
LangChain · Company blog · 11 a week · 138 posts since Aug 16, 2026
Nov 10
How Workday Built an Enterprise-Scale AI Agent Platform with LangGraph and LangSmith
See how Workday used LangGraph and LangSmith to build an internal AI agent platform that cut prototype time from months to less than a day and compliance needs.
Nov 9
What Is Eval-Driven Development? How to Improve AI Agents
Eval-driven development helps you build AI agents against a consistent set of metrics. Define good behavior, write the eval first, then compare experiments.
Nov 9
LangSmith BYOC on AWS is generally available
LangSmith Bring Your Own Cloud is now generally available on AWS, giving Enterprise teams managed observability, evaluation, and deployment inside their own VPC.
Nov 9
Promptim: an experimental library for prompt optimization
Automate prompt engineering with Promptim's optimization library. Save time, improve AI performance, and switch models faster.
Nov 9
Iterating Towards LLM Reliability with Evaluation Driven Development
Dosu uses evaluation driven development and LangSmith to build reliable LLM products at scale, monitor production performance, and iterate with confidence.
Nov 9
How Stripe Built Kai on Deep Agents in 1 Week
Learn how Stripe built Kai, a company-wide AI agent on LangChain, LangGraph, and Deep Agents, reaching 5,000 users in roughly 4 weeks.
Nov 5
Agents Are Going Async
Async subagents let an agent stay responsive while background workers run long tasks. How the orchestrator, notifications and approvals work in Deep Agents.
Nov 4
LangSmith BYOC is now available on AWS, Azure, and Google Cloud
LangSmith BYOC now runs on AWS (GA), Azure and Google Cloud (Beta). Your traces, evals, and agent deployments stay in your cloud account while LangChain runs it.
Nov 3
Why human insight is a strategic advantage for building better agents
Explore 3 principles for effective human-in-the-loop workflows and how human-review is a strategic imperative for production-ready agents.
Nov 3
How We Optimized Browser Use for Deep Agents
We compared seven browser toolsets for Deep Agents, picked Stagehand from Browserbase, and tuned it with LangSmith traces and evals. Here's what we learned.
Nov 2
New context engineering challenges in late 2026
LangChain CEO Harrison Chase shares insights into the biggest harness engineering challenges with the emergence of proactive agents.
Nov 2
Managed Deep Agents: the fastest way to ship a production deep agent
Run deep agents in production with durable execution, sandboxes, tool access, and LangSmith observability, without building the runtime yourself. Now in private beta
Oct 29
Browser Use in Managed Deep Agents
Managed Deep Agents now runs a browser for your agent, with tools tuned for context-efficient browser use and a handoff so you can sign in yourself.
Oct 29
Managed Deep Agents v0.10: Browser Use and Async Subagents
Managed Deep Agents v0.10 adds browser use, so agents can work on sites with no API and hand you the window to sign in, and async subagents for background work.
Oct 28
How to build evidence-grounded agent memory with OpenWiki and Graphs
LangChain 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.
Oct 28
How to Build Proactive, Always-On Agents with the Schedules SDK in Managed Deep Agents
Most proactive agents run on a simple cron. Learn what scheduled runs unlock, from memory to smart triage, and how to add them to Managed Deep Agents.
Oct 27
How We Built Our Design Agent
How 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.
Oct 25
The five components of building a "company harness"
Learn how LangChain built internal agents across marketing, sales, and engineering, and how they have completely changed how those teams work.
Oct 23
Context Engineering (Agent Memory) for AI Agents Starts with Retrieval
Agents 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.
Oct 19
How Numan Built an Eval-First AI Health Coach with LangGraph and LangSmith
How Numan built Nu, an AI health coach, on LangGraph and LangSmith with per-category evals, simulated conversations, and safety gates on a regulatory line.
Oct 15
October 2026 LangChain Newsletter: Everything we shipped at Interrupt NYC & London
What we shipped at Interrupt NYC and London: LangSmith AI Search, Engine v2, Trajectories, Custom Apps, Fine-Tuning, and Managed Deep Agents v0.9.
Oct 15
The Most Common Questions About Agent Evals, Answered
Where to start with agent evals, offline vs online evals, evaluator types, LLM judges, benchmarks with Harbor, multi-turn evals, and keeping costs down.
Oct 14
Context Engineering with Deep Agents: How To Remember Without Keeping Everything In Context
Long-running agents degrade as context piles up. Learn how offloading, summarization, skills, subagents, and memory keep your agent's context window focused.
Oct 13
Search agent traces by behavior with AI Search in LangSmith
AI 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.
About this blog
LangChain's own blog on langchain.com, found by the daily check.
Posts per week, last 26 weeks
11 a week over the last six months (or since the feed's oldest post)
Posts by month
Writes about
AI and agents (102), Product and company (12), Developer tools (10) in the last six months.
LangChain
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History
Listed on Blogs Sep 28, 2026. No changes to its feed, status or cadence since.