Christian Bromann
@bromann
Running on agentic reasoning and espresso. Building with @LangChain ๐ฆ๐.
888 Following 3.3K Followers
Starting today, @LangChainโs Managed Deep Agents can bake your agentโs environment at deploy time. ๐งโ๐ป
No clone. No install. No repeated setup.
Drop in or a Dockerfile. Bake once. Every new thread starts ready. ๐
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Starting today, a @LangChain's Managed Deep Agent deploy provisions your Slack app for you ๐คฏ
No manifest. No OAuth redirects. No bot tokens to copy around.
One command, and your agent says ๐ in Slack.
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An agent is 3๏ธโฃ layers.
๐ Business logic you write.
๐ A harness that runs the loop.
๐ Infrastructure that survives production.
@hwchase17 breaks the whole stack in one video.
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Managed Deep Agents is just getting started ๐
@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. ๐ค๐ฃ๏ธ๐ค
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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Weโre launching Managed Deep Agents today ๐๐
@LangChain
The goal posts for building agents have moved.
Giving an agent tools, deploying it somewhere, and putting a UI in front of it isnโt 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 ๐
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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 ๐
๐งโ๐ป full demo:
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