@SpalaAi · X

chenglong-hn · HN

Data visualizations are the bridge between user and data. But building AI agents that can generate visualizations reliably can be very tricky: - simple chart specs can be reliable, but generated charts are often of low quality due to reliance on system defaults; - complex chart specs with explicit details can produce good-looking charts, but they are verbose and agents can struggle with reliability We figured out it is a limitation on the language issue (not just AI capability thing) -- current visualization languages are a bit too low-level for AI agents, requiring them to explicitly make visual decisions that are supposed to be handled by a good compiler. Flint is a visualization intermediate language to address this issue, allow AI agents to solve this last-mile human-agent interaction problem. It provides a simple semantic-type based specification, and contains a layout optimization engine that can produce good-looking charts (filled with derived low-level details) from simple

@shiftibis · X

Indie project 📝 ReBox: visual boards where color = group and branches = a file tree — both at once. Share links open without login (anyone with the link can edit). A Claude connector builds boards for you. English UI just shipped. #buildinpublic

tahazsh · HN

Hi! I’m Taha. In many agentic products that support workflows (including one I worked on), I noticed they either don’t support node-based editors, or use React Flow and go through the difficult work of integrating it into their product to run it and work with their existing logic. So I thought about creating a tool that could help with this by closing the gap between the editor and the runtime. That’s why I created Wayflow. The basic architecture is simple: you just need to create a graph (which is a JSON object) that the runtime knows how to run. The runtime doesn’t care where that graph is coming from, it just needs the right schema. And with the help of the editor, you can create the graph, and then export it or directly save it on your backend in your database. And then when you want to execute it, you just hand it to the runtime. The runtime can either stream the execution (which is useful for the editor), or give you the final result. How you execute the graph is up to you: t

@iamdeepak89 · X

@AbhilashVeettil · X

@simranrambles

@pixelcave_john · X

Hey Germán! I recently launched and a major update to Tailkit!

@GuidedBase · X

@sivasankar___s · X

I’m currently deep in building Rudra, a visual orchestrator for Next.js designed for full engineering control. ​Zero vendor lock-in—you own the code. ​ Website: App Build with Rudra

@Akinzoooo · X

@kitbasedev · X

We just launched, check us out at