@claroboard · X

I built a whiteboard. The hardest part wasn't the coding. The hardest part was getting the first users. Want to give it a try?

@shiftibis · X

Indie project 📝 ReBox: visual boards where color = group and branches = a file tree — both at once. Share links open without login (anyone with the link can edit). A Claude connector builds boards for you. English UI just shipped. #buildinpublic

@rutvikraval5 · X

🚀 Just launched The Pegboard — a clean, responsive web experience focused on performance and usability. 🔗 Would love your feedback 🙌 #Flutter #FlutterWeb #BuildInPublic

@emir_ogz · X

Just shipped - AI-native workspace for solo devs Agent reads/writes your project notes automaticly

@locatornation · X

@rishabh21g · X

The whiteboard that just lets you draw

TeachAny — 使用 TeachAny AI 工具，简化您的教学 - [更多功能](https://www.teachany.com/tools)

@clawncore · X

u/pablostanley · Reddit

Built Hilos, a team chat where AI coding agents are members of the channel Hi, I'm Pabs, and I built this thing I'm calling Hilos (means "threads" in spanish) I work with coding agents every day (Claude Code, Codex, Cursor) and the workflow started to feel a bit isolating... tons of tabs in a terminal, and my team in a chat somewhere else, and I'm the messenger in the middle, copy-pasting context both ways from things I build and feedback I get. The llm doesn't know what the

@AmaaN_AshiF · X

I Built this for 2 weeks with Claude code It’s now a working beta Product A chat first workspace for teams whose work gets scattered across chats, files, feedback and project tools. Free to try right now.

@posteyai · 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