@troyaunderwood · X

@dailytaskproai · X

@DonatasJab · X

Not long ago finished my first SaaS product - social media scheduling tool. Tomorrow will launch on Product Hunt. I hope it goes well.

bhagyeshsp · HN

First things first: On the landing page, click on the "demo" link below the Hero section to try it without jumping any hoops ** I'm a long-time Basecamp user and satisfied with its overall functionality. Of course, there are many things that can be improved but that is not the point of this post. *Background* Basecamp lets users create "Projects". These projects are isolated workspaces that contain: members, todos, chat, files, message board, and calendar, etc. My issue was with the scattered calendars. Because I (and every other Basecamp user) creates a dedicated project for different scope of work, even if it is for the same client. For example, at any given time, I may have 4 projects for client-X and 3 projects for client-Y. *My pain point* I have experienced that most clients (especially the decision-makers) do not use Basecamp as often as we--the agency folks use it. They just use it when some reviews or comments are required or some file access. The clients organize their

@Akisin1 · X

Listen Like You Live

@AmeerHaio · X

your content everywhere!

@Rustam280592 · X

Day Etch is your second memory. Day Etch - your experience as intellectual capital for future generations. We are creating not just a diary, but a repository of life.

English Daily — AI 每日英语学习平台

mjkl7896 · HN

Velprium - Time Workspace

@JespernissenSEO · X

@seb_klopfer · 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