
Claro | Teamwork Whiteboard
创建共享白板,进行素描、头脑风暴、分配任务和协作。
@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?
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创建共享白板,进行素描、头脑风暴、分配任务和协作。
@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?

创建用颜色分组和分支结构的视觉看板,支持无需登录分享。
@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

用 TeachAny 创建个性化课程、工作表和测验,节省教学规划时间。
TeachAny — 使用 TeachAny AI 工具,简化您的教学 - [更多功能](https://www.teachany.com/tools)

强调性能和响应式设计的免费网络工具集合。
@rutvikraval5 · X
🚀 Just launched The Pegboard — a clean, responsive web experience focused on performance and usability. 🔗 Would love your feedback 🙌 #Flutter #FlutterWeb #BuildInPublic

为AI代理构建数据库、看板和笔记进行协作。
@emir_ogz · X
Just shipped - AI-native workspace for solo devs Agent reads/writes your project notes automaticly

通过交互式可视化学习数据结构和算法,准备技术面试。
@aarsh_30 · X

上传手写考试答卷,获得即时AI评分和详细反馈。
Xaminix
AI Powered Answer Evaluation for CA/CS/CMA

在智能代理笔记本中构建、运行和评估机器学习工作流。
eldar_hsnv · HN
Show HN: AI Notebook for Data Science – Kind of Like Cursor but for Jupyter

用间隔重复法复习 LeetCode 题目,提升记忆和解题能力。
@JoydeepNath007 · X

管理学术会议:提交和审阅论文、处理日程安排和注册。
@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

为 Arduino、ESP32 和 Raspberry Pi 等平台设计电路、模拟和共享项目的开源注册表。
@locatornation · X

使用模板、电子签名和分析功能创建商业提案
@propelio_app · X
Hey man, Building Propelio, proposals for freelancers Let’s connect!