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@langchain

Design Agent Uses Editable HTML, Data Specs and Animation Timelines

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@langchain

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27 October 2026 19h39

Our design agent doesn’t burn tokens starting over. It never hands back a flat image or a generated clip.

Slides are HTML. Charts are data specs. Films are animation timelines. “Move the parrot left” is a one-value change, not a regenerate-from-scratch.

🍿 Want to go deeper? We… https://t.co/aJpDLGUGf1 pic.twitter.com/nkAz9VTTXF
— LangChain (@LangChain) 27 octobre 2026

Our design agent doesn’t burn tokens starting over. It never hands back a flat image or a generated clip. Slides are HTML. Charts are data specs. Films are animation timelines. “Move the parrot left” is a one-value change, not a regenerate-from-scratch. 🍿 Want to go deeper? We

→ View original post on X — @langchain

27 October 2026
Open Source Design Agent Supports Slides, GIFs and Images

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@langchain

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27 October 2026 18h15

deepdive into how we built our design agent (along with oss code) i use this at least a few times a week for slides, gifs, images, etc

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27 October 2026
Managed Deep Agents Support Deploying Content Studio Within Organizations

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@langchain

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27 October 2026 18h06

bet ya didn't know… Content Studio is a managed deepagent!!! want your own content studio deployed in your organization? git clone
mda deploy boom

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27 October 2026
LangChain Opens Content Studio Agent Used for Thousands of Branded Assets

By

@langchain

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27 October 2026 18h05

We just open sourced our internal design brain 🧠

Meet Content Studio – the agent behind 3,000+ assets at @LangChain

Create on-brand product launch videos, slide decks, ad creatives, social media assets, ui mockups and more

Storyboard and collaborate on a shared canvas in… pic.twitter.com/VDnxWb2b5p
— amal (@amal_irgashev) 27 octobre 2026

We just open sourced our internal design brain 🧠 Meet Content Studio – the agent behind 3,000+ assets at @LangChain Create on-brand product launch videos, slide decks, ad creatives, social media assets, ui mockups and more Storyboard and collaborate on a shared canvas in

→ View original post on X — @langchain

27 October 2026
Open Source Content Studio Builds Branded Assets Through a Slack Agent

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@langchain

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27 October 2026 17h52

How we built Content Studio, an open-source design agent in Slack that makes on-brand videos, graphics and decks, and the harness that powers it.

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27 October 2026
Box Architecture Lets Parent Agents Handle Simple Requests Without Planning

By

@langchain

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27 October 2026 17h07

"If the question was very simple, or the search was very simple, the parent node can just do it. It doesn’t even need to come up with a plan” -Shubhro Roy, AI Engineering Leader at @Box

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27 October 2026
Box Deep Agent Uses Parent Child Architecture for Complex Requests

By

@langchain

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27 October 2026 17h07

.
@Box
’s Deep Agent architecture for Box Agent uses a parent/child model. Simple request? The parent handles it directly. No planning needed. Complex request? It spawns child agents to distribute the work, keeping the invocation surface uniform throughout.

→ View original post on X — @langchain

27 October 2026
Agent Improvement Session Examines Detecting Mistakes and Writing Evaluations

By

@langchain

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27 October 2026 17h06

What does it take to get to an agent that catches its own mistake and writes the eval and the fix?

Catch @hwchase17's Interrupt London session on building agents that improve over time: https://t.co/0l2gxKtdxd pic.twitter.com/J6xe9At0fX
— LangChain (@LangChain) 27 octobre 2026

What does it take to get to an agent that catches its own mistake and writes the eval and the fix? Catch @hwchase17
's Interrupt London session on building agents that improve over time: https://
youtu.be/xy_7SzwsIjM

→ View original post on X — @langchain

27 October 2026
LLM Judge Workshop Covers Trajectory Scoring and Deterministic Matching

By

@langchain

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27 October 2026 14h02

Can you trust an LLM judge? Join @divyasan0 Oct 28th for a virtual workshop on:
✅ How to score a trajectory with the trajectory match evaluator
✅ How to tune matching so evals fail on real behavior changes, not argument formatting
✅ When to use deterministic matching vs.

→ View original post on X — @langchain

27 October 2026
Tutorial Explains LangGraph in One Minute

By

@langchain

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26 October 2026 20h00

LangGraph explained in 1 minute. pic.twitter.com/cVH7jtGrUH
— LangChain (@LangChain) 26 octobre 2026

LangGraph explained in 1 minute.

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26 October 2026

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