@MiloPaigeTech · X

Learning how to code so just making a simple work hours tracker for me and my colleagues.

Loerei · HN

I found that describing where a broken UI is and taking screenshots for AI agents really sucks. I’m too lazy to explain an indescribable visual bug or capture a millisecond-long flash. I also don’t want to remember which file defines an element, whether it's right in the .tsx or a problem with the Parent Styles in .css. And even if you can point out the exact file, your agent still has to dig through thousands of lines of code to know what on earth you're yapping about. In a 7700-file monorepo like Cal.com, simply giving the right file in the prompt for your agent saves about 68.9% of execution time and 94.2% of the tokens your agent needs to digest. HoverSource gives all the needed information and further pushes it to -88.5% time and -94.5% tokens, basically skipping the entire digging session and jumping straight to reasoning and executing. The save is linear to how big your codebase is. I want to save tokens, but don’t want to spend my time and energy digging manually, and a junio

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

@ivygrzy · X

My git history as music. This is Unicorn: a desktop app I built w/ @AnthropicAI's Claude Code. It lives beside the terminal and documents my builds. Every experiment logs itself. Every commit plays a note. The story: The preview:

@pending_d3v · X

Just shipped SouqTrack. A tool that tracks live crypto prices, built from scratch while learning JavaScript. Add coins, prices update every 30s, your list saves even after refresh. 🔗 #buildinpublic #javascript #webdev

nymph09 · V2EX

做了一个打工人黄历，用来玄学上班的传统魔法 做了一个面向产品、开发、测试、项目和运营同学的职场黄历，根据日期和岗位生成当天的运势、宜忌事项、贵人/冲煞、吉星和值日信息。 ## 项目链接 - 在线预览：[https://noir-hedgehog.github.io/pm-calendar/]( https://noir-hedgehog.github.io/pm-calendar/) - GitHub 仓库：[https://github.com/noir-hedgehog/pm-calendar]( https://github.com/noir-hedgehog/pm-calendar) ## 比如今天的 

@thinking_555 · X

🚀 我做了一个超有意思的网站！ 「S」—— 一个极简、纯粹、能让你安静思考的地方。 没有广告、没有推送、没有干扰，只有干净的内容和思考空间。 感兴趣的朋友欢迎来坐坐 👉 #极简 #思考 #个人网站 #极简搜索

@integ_web · X

~*OpenEd* _Edtech is broken, we are fixing it._

@liamghennigan · X

timeblind · V2EX

那天的月亮 | 月相观测网站 最近做了一个 side project：Lunaria 。 选日期、时间，在 3D 线框地球仪上点一个地点，就能看到那一刻、那个位置真实可见的月亮 —— 不是随便一张月相图，而是带月相、明暗交界、天平动和本地观测倾斜角的 3D 渲染。 技术栈：React + Three.js + astronomy-engine ，时区用 tz-lookup 处理，光照按站心天文计算。 几个我觉得有意思的点： 北半球盈月右亮、亏月左亮，和肉眼看到的一致 「本地观测角度」默认开启，按你在该地实际仰望时的倾斜呈现 可以生成分享卡片，内置「你出生那天的月亮」「我们相遇那夜的月亮」这类文案 在线体验： https://kokoro-ele.github.io/Lunaria/ 源码： https://github.com/kokoro-ele/Lunaria 欢迎来玩🌛

laurentiurad · HN

I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!

@XoDaGod · X

Cognitive Intelligence Labs — Engineering Sovereign Multi‑Agent AI and Next‑Generation Cognitive Systems.