LangChain JS
@LangChain_JS
Ship great agents fast with our open source JS frameworks – LangChain, LangGraph, and Deep Agents. Maintained by @LangChain.
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You deploy, we provision! 🤝
Starting today, a @LangChain's Managed Deep Agent deploy provisions your Slack app for you 🤯
No manifest. No OAuth redirects. No bot tokens to copy around.
One command, and your agent says 👋 in Slack.
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An agent is 3️⃣ layers.
👉 Business logic you write.
👉 A harness that runs the loop.
👉 Infrastructure that survives production.
@hwchase17 breaks the whole stack in one video.
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Managed Deep Agents is just getting started 🚀
@hwchase17 just published a set for banger videos that get you up to speed how shipping production agents today looks like.
The AI engineer's job: what it knows, what it can call, and where people reach it. 🤔🗣️🤝
The rest is Managed Deep Agents.
In Managed Deep Agents skills load in two steps, which is why a lean SKILL.md works.
The prompt keeps the name and description. The body opens when the task matches.
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Mention the agent in Slack. It runs. It replies in the thread.
Managed Deep Agents treats Slack as a channel file: channels/slack.py. Mentions, DMs, and follow-ups start a run as the caller and post the answer back. No bot server to stand up either.
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You don't stand up an agent. You upload a folder.
Claude Code is a harness for your laptop. Managed Deep Agents is a harness for production.
Want Slack? Add a file. Want a daily run? Add a file. Want memory? Add a file.
LangSmith runs the harness.
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We’re launching Managed Deep Agents today 🎉👀
@LangChain
The goal posts for building agents have moved.
Giving an agent tools, deploying it somewhere, and putting a UI in front of it isn’t the hard part anymore.
The next challenge is everything around the agent: identity, memory, credentials, permissions, and securely connecting it to the services your users already use.
This beta release is just the beginning and our foundation what is about to come next 🚀
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this blog covers 6 common workflow patterns we see with dynamic subagents (fanout and synthesize, adversarial verification, etc)
if you'd prefer to learn w/ a video, check out this excellent guide from @colifran_ with examples and trace walk throughs!
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code reviews can be beautiful ❤️ thanks @shadcn!
Plugged the new @shadcn chat components into @LangChain_JS Deep Agents and one-shotted a full code review agent.
One reviewer per file, local sandbox, streaming live. Wild how fast this was 😍
🧑💻 full demo:
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Alex recently joined the @LangChain_OSS team, and he published his first article on how Deep Agents uses prompt caching to cut API costs.
Give it a read, and give @its_ao a follow!
give Alex (@its_ao) a warm welcome to the LangChain OSS team! first article is already a banger 🔥
Use GLM 5.2 today in Deep Agents Code!
One LangChain model object gives you access the whole @OpenRouter catalog for Deep Agents.
Route by throughput, latency, or price. Filter providers. Enforce ZDR/no data collection. Select fallback models.
When OpenRouter adds a provider or model, just pass the new slug.
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