Sprint 107 was built around the main release: the Icecat Studio AI Assistant. Alongside it, the new Story Builder reached our dev environment, the MCP Server got more capable. Several smaller improvements, including a simpler aggregation architecture, round out the sprint.
Imagine an editor you can simply talk to, on any page of Studio. Give it a product link or a file, and it returns a finished story. Then keep chatting to refine it. Now it’s in Studio and you can find it sitting next to your profile.
Finding and creating assets
Creating stories
Working on the story afterwards
Publishing and help
Safe by design
Verified on real contentWe checked about 100 stories from websites, JSON, XML and HTML files, images, chat text and several languages. Almost all were created on the first attempt. On the same pages, the stories are fuller, and the text is taken verbatim.
The native Story Builder is now deployed on our dev environment and is being actively tested.
We started adding an SVG import tool to the MCP Server, so connected AI agents can upload SVG files. This is the first step in a set of MCP additions planned for the next sprint.
The concept for the first page after login was discussed and reworked this sprint actively. The goal is a page that informs everyone who enters the platform. Data and structure come first, and design follows.
Aggregation was previously handled by a separate microservice that tracked events and made selections. We simplified this and removed the service and now aggregated stories live in an entity. The collection stays separate, but we process it on assets and entities separately.
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