@SkinsSquad · X

No funding necessary but a great productivity tool for myself to connect GCal, Slack, and Granola for organizing my To-dos in one spot.

@jiimaho · X

Made a few changes to so now people can add more dates, delete a day and delete a person! Built with #claude

@SwipeSights · X

u/Next_Bluejay265 · Reddit

I built a free college schedule maker — type or speak your week and it draws the timetable Built this because every semester I was redrawing my week in Notes / Excel. College Schedule Maker — free weekly class timetable in the browser. • Drag & drop courses on a week grid • Print / PNG / share link (no account) • “Type your week”: paste lines like “BIO 201 MWF 9-9:50am” and it builds the grid • Optional voice: say a line, it lands in the text box (Chrome/Safari) Parsing runs on yo

@zsh89821970 · X

做了一个新小项目 🛠️ Sent2X — AI 驱动的 X/Twitter 定时发帖工具。用 AI 生成一批帖子，一键导入，定时自动发布。不用每天蹲在 X 上。 👉

@GorewadaGroup · X

@AmeerHaio · X

your content everywhere!

@asaio87 · X

not looking to sell but its nice to get it out there

u/Hot_Spend_2860 · Reddit

Two of us built a group-scheduling tool over two months - the stack, what took longest, and the mistake that cost us our analytics Upfront so nobody wastes their time: free product, $0 revenue, no company formed. This isn't a revenue flex. I'm posting the build because the two things that went wrong were more interesting than the things that went right. here’s the link! What it is: Meetly, a group scheduling poll. The people you invite never make an account, calendars auto-import so nob

@AI_Agencyguy · X

@harryjwang · X

I've used many of the major conference systems. Plenty still have docs as an unsearchable static site — or worse, as PDFs that stopped tracking the product three versions ago. Somehow, still true in 2026. We took an AI-first path with instead. Our docs are generated from the codebase itself. A custom Claude Code skill writes each page and retakes the screenshots whenever a feature changes — so the docs don't drift from the product. Every page still gets reviewed by a human before it ships. Now you can talk to them, too. We just shipped "Ask AI" over our docs: This feature also turned out to be a nice teaching case for agentic RAG vs. classic RAG: • Classic RAG: chunk → embed → vector DB → retrieve once, by fixed rules • Agentic RAG: hand the model a search tool and let it drive — write a query, read the results, rewrite, retry At more than 100 pages, still no vector database needed. And every answer cites the exact page it came from. #Age

@JoydeepNath007 · X