@lukcombinator · X

post to socials and check which post paid the rent

@wesselsHQ · X

@rafal_darlak · X

Released yesterday! I built a platform for my X account management, scheduling, analytics, AI assistant etc. I didn't like the apps that I tried so I wrote my own ;)

u/naxmax2019 · Reddit

Lessons from building a “paste a URL, get your brand” onboarding - our activation rate doubled when we deleted the signup wall Building an AI content tool (Sketch : turns one prompt into on-brand posts, carousels, video, etc.). Sharing one decision that changed everything, because I see SaaS founders get this wrong constantly: We let people generate before signing up. Old flow: signup → onboarding form → brand kit upload → first generation. Classic. Also classic drop-off at every step. N

sunpy · V2EX

快开学了,专门给老师们做了个在线排课工具 最近做了个小工具-Teacher Planner ，可以帮老师提高排课效率,节省时间. 目前支持: * 自动排课，保存前先标出时间冲突 * 某节课被占，点一下顺延，后面受影响的课自动跟着挪 * 日 / 周 / 月视图共用一份数据，能直接打印 * 课程标准可以挂到具体课时上，方便查漏 * 中英双语 技术栈是 Next.js + Drizzle ORM + PostgreSQL + Better Auth 地址： https://teacherplanner.ai 免费版能建一份完整计划，欢迎试用、欢迎拍砖～

@slaven_ra · X

- recently added subscribe to Youtube channel feature to receive auto-summaries via email on each new published video

@mesbahlab · X

@nrqa__ · X

the AI agent resource list I wish existed a year ago 1). for learning the fundamentals (videos) ↳ llm introduction - the crash course that actually explains how these models work before you touch a line of code ↳ llms from scratch - build one yourself so the black box stops feeling like magic ↳ agentic ai overview (stanford) - a proper academic breakdown of what makes an "agent" different from a chatbot ↳ building and evaluating agents - how to actually test whether your agent is doing its job or just faking it ↳ building effective agents - practical patterns for agents that hold up outside a demo ↳ building agents with mcp - how model context protocol changes the way agents connect to tools and data ↳ building an agent from scratch - no frameworks, no shortcuts, just the raw build ↳ philo agents - a full playlist for going deeper once the basics click 2). for cloning and remixing (repos) ↳ genai agents - a growing collection of agent examples you can clone and

@itzKashan2912 · 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

@helloukey · X

@SidathRashen · X