@buildwithmaya · X

Hi Rashka I am building

@baptistedulac · X

time tracking for freelancers and agencies

@MourynCher16712 · X

data analysis app. Check out

@okiela_io · X

Sales up but profit unclear? I help ecommerce sellers find hidden profit leaks by SKU. Send me 1 order export → 3 leaks:

@heydevottam · X

I'm building EVE — an inventory intelligence platform that helps D2C brands detect stockout risks, dead stock, and profit leakage before they become costly.

@uday_devops · X

@itz_sayan_03 · X

Ever wondered how cinematic scroll-driven websites are built? 👀 Meet SectionFlow—an open-source React library with 60+ ready-to-use section transitions, a one-command CLI, reusable sections, and optimized performance. 🚀

@himanshu_b20 · 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

@Moha__niang · X

@patologico · X