@gavinelliott · X

Finding that some people cared about but not enough to make it viable, maybe

u/Early-Cobbler-917 · Reddit

I need some honest feedback, please. I’ve been developing this website ( https://Cybergrid.dev ) for a while now. Even though I started out super enthusiastic because I thought the idea was great, I have to admit that my motivation has been fading a bit lately. I’ve shared the project across a few communities looking for suggestions on how to improve it, as many people pointed out that it looks like the result of "vibe coding." While it’s true that I’ve relied heavily on AI tools to move fa

u/Shifan224 · Reddit

I built an open-source AI image studio that runs one prompt across 13 models at once (BYOK, no backend) I kept guessing which image model to use for a prompt, so I built a tool that stops the guessing. Gridloom runs one prompt across several models and seeds at the same time and gives you a contact sheet. You look at the grid and pick the keeper. What it does: comparison grid (models by seeds in one run), a cost meter that estimates the run before you spend anything, a local searchable libr

@OprosOlamiflex · X

Check out what I just built with Lovable!

u/FMLatex · Reddit

Rustgrid - From mission to merge What if tickets became work orders for AI coding agents—connect a repo, assign the task, and get a pull request back. Looking for a few early testers: https://rustgrid.com Happy to bump for free any serious early adopter in exchange of feedback submitted by /u/FMLatex to r/SideProject [link] [comments]

@Jummsie · X

@_coderwolf · X

u/GuillaumeBrdet · Reddit

Fun weekend project built on Lovable Here's a fun little weekend project I built using Lovable. It's inspired by the one million dollar homapage 😊 You can check it out: onemillionpixels.co Let me know what you think. It's far from perfect, but I was able to get the vibe I was aiming for. submitted by /u/GuillaumeBrdet to r/SaaS [link] [comments]

@ffteema · X

softwarewrighte · HN

Open source ML programming language playground

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