
WeekendMax — max your 3-day weekends. Zero PTO required.
从你的城市发现3天周末旅行,按旅行时间和预算排序。
cakerace · HN
WeekendMax – Every 3-day-weekend trip from your city
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从你的城市发现3天周末旅行,按旅行时间和预算排序。
cakerace · HN
WeekendMax – Every 3-day-weekend trip from your city

与本地旅行者和向导连接,参加社区聚会及预订真实体验。
@nopecode369 · X
This completely resonates. I actually poured my entire heart and passion into building for this exact reason. It’s designed as a dedicated home where real travelers, local guides, photographers, and trip planners can finally connect organically

举办和发现活动,支持门票、嘉宾管理和现场签到。
@_ariesblaze · X
1. SEO & Websites Audits. 2. Invoice mgt. 3. Event and Ticket Mgt

保存并浏览你想尝试的餐厅,帮助你决定去哪里用餐。
@danielendara · X
Sure! let's connect! My latest creation is

浏览附近餐厅的每日鸡翅特价、啤酒优惠和欢乐时光。
@WingBeerSpecial · X
- Discover daily specials at restaurants near you. Currently limited to Ontario Canada. Let us know if you like to concept and want to see coverage in your area next!

由大脚怪导游的BC 3D之旅,探索30座历史城镇和6条山脉。
halshin_dev · HN
An interactive game of British Columbia

按标签浏览和分享链接,由社区点赞和评论排序。
rakibtg · HN
Hey HN, the maker here. I built Prijm.com because I wanted something like a cross between Reddit and the simplicity of Hacker News, where you can follow tags like #OpenAI or #AI [1] the way you'd follow a subreddit, but ranking is based on favorites/comments rather than a hidden algorithm Right now it has a very small user base and a few posts, so it's small and early. One thing I'm actually proud of is the threaded, markdown commenting system. I put a lot of work into it. Unfortunetly, there is

内置chat功能的to-do list app,用于任务组织和团队问责。
@ammar_nassri · X
I'm building a conversation-first accountability app. Let's connect

搜索餐厅,发现当地人真正吃饭的地方,避免旅游陷阱。
kingchesco · HN
I know $90 for a dining app sounds absurd. And it’s not even an app; it's a wrapper for an LLM. But it is how it is built that makes it so expensive. I had to make a whole API just to call it (which because its own SAAS). All just to bypass dumb google reviews. Google Maps and reviews send people to places optimized for tourists and good copywriters. To find actual local hole-in-the-walls algorithmically, I had to first build that api (called BWENDI), a "spatial gravity" engine using 100GB+ of tweaked OSM, GeoNames, and other proprietary data. Instead of aggregating reviews, it mathematically calculates foot-traffic, throughput, transaction stats, and economic criticality among other factors. Bwendi is A Python/Node ETL pipeline feeding an LMDB-backed context API. It uses a proprietary 1MB binary grid served via Cloudflare Workers for millisecond edge reads with near-zero overhead, hosted in Switzerland. This was done of course to get the purest location context around every street
