@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.

@aryansoni1108 · X

Hi all, can you give me some feedback on my SaaS and the landing page -

@QuantBuddyAI · X

And just getting started!!

软著 Pro — AI 软著生成器，帮助用户生成软件著作权申请文档

@KhaledMMatar · X

rohanrecommends · Product Hunt

Fuzzy AI We warm your prospects before reaching out

SafeWrite AI — 结合 AI Humanizer 与 AI 检测功能的写作工具，帮助用户生成更自然、难以被检测为 AI 的内容。支持训练私有化的 Humanizer，模拟个人文风并确保隐私不泄露。同时整合 GPTZero、Turnitin 等检测器，一键获取多平台检测结果。通过“改写-检测-再改写”的自动流程，有效提升内容通过率，适用于学生、自由写手及内容创作者。

@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

@SeHozaifa · X

@taherchhabra · X

These exact 4 things ... in