zhiheng_huang · HN

Sharper – an AI office agent grounded in your knowledge, with citations

@WorkFarOfficial · X

@Shekar77hima · X

run deepresearch, coding agents for free.

Turbo Learn — 从文档、图片、拼音文件生成笔记的 AI 学习工具网站

QWQ AI Assistant — 免费提供经过深思熟虑且富有详细推理的答案的 AI 助手，不需要登录

@fedeponte1 · X

my first saas. i think i built something people actually want and completely failed at the business side. would genuinely love help. openpaper ( writes full, cited research papers from a prompt. research, outline, writing, real citations, export. the honest numbers: - ~2,300 signups - ~1,500 generated a full paper. people actually use it. - ~5 have ever paid. ~$45/mo. activation is great, revenue is basically zero. i've been staring at this for weeks. the paywall is on export (pay ~$12 to download the pdf). but the full cited paper is right there on screen, free, you can read it and copy-paste it. so i'm charging for the gift wrap after handing over the gift. almost nobody even reaches checkout. 76% generate exactly one paper and leave. one-and-done, so subscriptions make no sense. the audience is mostly students and researchers on personal gmail, all over the world, almost none on university or company emails. traffic is x and github. so i genuinely can't tell

CareerAce — AI 模拟视频面试与求职辅导工具，根据简历与实时回答进行对话提问，并在面试后提供评估报告 — 支持 Web、iOS、Android

u/Sea_Way6729 · Reddit

We started working on MoClaw 6 months ago as a side project, and managed to turn it into our main and only business! About half a year ago, a group of friends and I started working on a tool in our free time. We wanted a safer and more streamlined version of OpenClaw because there were many, many stories about AI going rogue, and ultimately decided to make one ourselves. On top of that, the costs of running autonomous, independent agents were quite high if you wanted to do it the proper, safe

@taherchhabra · X

These exact 4 things ... in

david082321 · V2EX

我做了一个 Kimi K3 的工作台，把成本、部署、评测和使用场景整理到一起 最近看大家聊 Kimi K3 、Claude 、GPT 在 coding 和长上下文任务里的差异，发现很多信息散在不同地方：API 成本、上下文窗口、本地部署、硬件需求、评测表现、适合的使用场景，都要来回翻。 所以我整理了一个偏“导航仪”的 Kimi K3 站点： https://kimi3.org/?utm_source=v2ex&utm_medium=post&utm_campaign=kimi3_org&utm_content=create_topic 它不是单纯的介绍页，更像一个给开发者用的参考工作台。你可以快速看 Kimi K3 适合做什么、部署前要准备什么、和其他模型相比大概强在哪里，以及 API 成本怎么估算。 如果你最近也在比较 Kimi K3 、Claude 、GPT 或 GLM 这类模型，欢迎看看，也欢迎提建议。

@AjayGB4 · X

tekbog · HN

Research Rooms for Agents