生产力2 weeks ago
Online Appointment Scheduling for Individuals & Businesses | Onbookr
用 Onbookr 管理预约、同步日历、自动发送提醒。
@helloukey · X
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30 projects
用 Onbookr 管理预约、同步日历、自动发送提醒。
@helloukey · X
与本地旅行者和向导连接，参加社区聚会及预订真实体验。
@nopecode369 · X
This completely resonates. I actually poured my entire heart and passion into building for this exact reason. It’s designed as a dedicated home where real travelers, local guides, photographers, and trip planners can finally connect organically
在LinkedIn上追踪采购信号,自动预订演示会议的AI代理。
@nickventuri · X
building to book high intent demos on autopilot founders just show up to meetings
分析会议记录以检测范围蔓延风险并生成警报。
@theshaunak_twit · X
ScopeShield ( A platform designed to kill scope creep for agencies and teams before it eats their margins. Built so you don’t forget scopes and stop doing unbilled work.
创建付费活动，管理报名、生成二维码票券并进行手机签到。
@HossainArif85 · X
Building — a platform for paid events where organizers manage registrations, approve payment proofs, send QR tickets, and check attendees with any phone browser. Happy to connect with fellow builders!
统一日历管理所有房源在Booking.com和Airbnb上的预订
@hazansalami · X
Built with Claude you no go believe 😪
为会议前的参与者生成有来源的研究简报。
@dhanushkenkiri · X
Building If you ever wanted to know about someone online this is your go to place. Also, let's connect!
从 Telegram 群聊中提取任务和截止日期，并发送个人提醒。
@SagarSR349400 · X
Working on Sieve, a distributed AI system that autonomously monitors Telegram group chats, extracts tasks and deadlines using Google Gemini, and sends intelligent private reminders.
一个链接完成从推介到付款的交易全流程：预订会议、签署合同、收款。
@abhinav__dubey · X
Heyy Yooo! Building one link that helps SMBs go from first pitch to fully paid process, no juggling four tools to get there.
创建活动、销售门票、管理参与者并通过 AI 分析活动数据。
@abhishekbariyaa · 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
