Developer Tools1 month ago
Spala — Visual Backend Logic for AI-Built Apps
Visualize and deploy AI-generated backend code as a verifiable logic layer you can understand and own.
@SpalaAi · X
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Visualize and deploy AI-generated backend code as a verifiable logic layer you can understand and own.
@SpalaAi · X
Backend-as-a-service with MCP server, REST APIs, and row-level security for AI apps.
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
Design working prototypes visually with a coding agent in real-time.
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
Build and preview AI apps with real backends and model choice.
@SanikaSurse · X
Visual node-based programming environment for creating GPIO logic and MQTT workflows on ESP32 devices.
@NodeESP · X
- Project for sale
Free frontend developer tools for CSS generation, image compression, and more.
@iamdeepak89 · X
Form backend for static sites and AI launches that captures submissions and routes them to your tools.
@AbhilashVeettil · X
Turn natural language descriptions into production-ready backend APIs and services.
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,
Debug and monitor AI agents with real-time visualization and performance analytics.
@simranrambles
Build production-ready AI agents using a visual canvas interface.
@salmanzafar949 · X
A curated library of reusable UI components built with Framer.
@buildlylibrary · X
Benchmark AI models by having them animate a 3D banana plant's full lifecycle.
fran-mora · HN
I gave 5 AI coding agents one prompt: grow a banana plant through its whole life in three.js: sprout, leaves, flower, fruit, rot, then pups that restart the loop. It's deceptively simple and yet very hard to get right from procedural code: you have to write working three.js and understand how the plant is actually built; how it hangs, ages and decays. Get the biology wrong and the code renders something weird. These are agents, not bare models (Claude Code and Codex for now). They can use tools, including playwright to check their work and improve it.