@SpalaAi · X

u/bob__io · Reddit

What we learned from trying to turn vibe-coded prototypes into production SaaS applications Founder here. While developing MCPBackend, we noticed a major difference between generating a convincing application demo and building a maintainable SaaS product. AI coding tools are increasingly capable of generating interfaces, routes and even initial application logic. But a production application still needs: a reliable data model authentication and authorization backend validation

u/tokmako · Reddit

I am developing an alternative work environment to Claude Design. When I first tried Claude Design, I really liked the idea. But after generating a design, I kept wanting a more direct way to continue working on it not as a separate design representation, but as a live, working interface. That’s what I’m building with VisualWizard. The canvas contains real, interactive prototypes. You can select elements directly, move or resize them, change styles, and keep interactions and

@SanikaSurse · X

u/12qwww · Reddit

I built a live benchmark to see which AI actually writes the best frontend code Hey everyone! I built OpenVibeEval because I was tired of "vibe-checking" AI-generated frontend code. I wanted to know which model actually produces the most accessible and clean React/Tailwind output. What I built: •A leaderboard of 24 models (Claude, GPT, DeepSeek, etc.) ranked by axe-core accessibility scores. •A Harness Comparator to show how different system prompts change the same model's output. •

@NikChr1414 · X

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

visuali · HN

Like Claude Code for Images

u/yousefemz · Reddit

18 months ago we weren't sure it was possible. Today we launched it. We kept asking ourselves one question for a year and a half: can an AI actually design a scalable backend from a description of how it should behave, not demo-ware, something that holds up in production? We didn't know. Some weeks it felt like the answer was no, or that we'd end up with code that looks right and falls apart the second real traffic hits it. We just launched it. You describe how your backend should behave,

@butmatthew17 · X

just check it out completely for free

samcymbaluk · HN

Axiom toolkit – Make your ideas precise enough to be proven wrong

@pixelcave_john · X

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