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This post describes Content Studio, an in-house design agent built on LangChain's Managed Deep Agents that generates on-brand videos, graphics, and slide decks from Slack prompts by writing the assets as code. The useful takeaways for AI readers are the process (four months of iterating on taste and design principles through visible failures) and the open-sourced harness, which lets other teams add their own brand tokens, fonts, and skills. Claims about output quality are self-reported, so the real test is how the approach holds up outside LangChain's own brand and workflow.
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.
The promo above was made by Content Studio, our design agent that can create videos, social graphics, recreated UI images, slide decks, and more from just a single prompt in Slack. Every asset the agent produces is written in code. Content Studio was built entirely in-house on Managed Deep Agents. It’s now one of the most widely used GTM agents within our company, but it didn’t start out that way. Early feedback was… not great. So how did we go from such low quality to this? We've spent four months teaching Content Studio our taste and design principles, mostly by watching it get things wrong in front of the whole company. This post walks through how our GTM Engineering team worked with our design team to build Content Studio from scratch: what good design means to us, how we taught the agent our taste, and the harness that lets it make anything from a still to a launch film. We've open-sourced our design agent. Fork the open-source repo, add your brand tokens, fonts and skills, and deploy it to your team's Slack with Managed Deep Agents.Watch the recording of GTM Engineering Live, where we go under the hood of the…
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