@uchechukwuevan · X

@blackkaide · X

OMNEX: AI that reviews your trades like a coach with no ego to protect — it just tells you where you bleed and how to stop.

Topfi · HN

Like everyone on HN, I love nothing more than to (re)read my own comments. Getting my intuition that I am among the smartest, most humble, highest quality commenters on here confirmed by an LLM so capable that the US government had to temporarily export restrict it [0] seemed only natural. Having had my perfection confirmed, I decided to share this joy with you as I had a few percent usage left before a reset. I took a few prompts, then did a review of the output which resulted in Selbstbild, a BYOK (Anthropic / OpenRouter) web app that gives you a summary and assessment of your public comments by one of our machine Gods, including Fable 5 (provided your can afford that luxury at API pricing). In all seriousness, I have, for a long time, used my own comments on social media (including HN) as part of a personal needle-in-haystack test, simply because I do know my somewhat peculiar style and what I tend to write, but also because I can sometimes write in a slightly confusing manner, ma

@jielove233 · X

最近看到 @dappOS_com 一个作品挺有意思 一个主流币交易共振信号Agent，通过 dappOS Coding 快速完成 链接： 这个案例的价值，不在于又做了一个行情页面，而是在于它展示了一种新的 AI Agent 构建方式 过去开发一个交易辅助工具，需要先处理数据接口，再搭建前端交互，编写指标逻辑，最后不断测试优化。 对于很多有交易想法的人来说，真正困难的不是没有策略，而是从想法到产品之间隔着一整套开发流程 dappOS Coding 改变的，就是这个过程 通过自然语言描述需求，就可以快速生成对应功能模块 像这个交易共振信号案例，本质上就是把市场数据、技术指标和信号逻辑结合起来，形成一个面向交易场景的辅助工具 它并不是替用户直接交易，也不是承诺预测市场 更重要的价值在于 帮助交易者降低信息处理成本 在 Crypto 市场里，行情 24 小时运行，大量数据、新闻、价格变化不断涌入 普通用户很难持续人工筛选有效信息 AI Agent 可以承担其中一部分重复工作： 监控市场变化 整理关键数据 输出信号参考 辅助交易决策 这也是为什么最近 AI + Crypto 的结合越来越受到关注 OKX 推出 AI 与交易生态结合 @BNBCHAIN 也在推动更多项目加入 BNB Agent Studio，鼓励开发者围绕交易、情感陪伴等方向构建 AI Agent 整个行业正在从AI 能聊天进入AI 能完成任务的阶段 而 dappOS Coding 展现出来的方向，是降低 Agent 创建门槛 以前一个想法可能停留在笔记里，需要开发团队才能实现 现在，更多开发者、交易者甚至普通用户，都有机会快速验证自己的想法 未来 Crypto 的竞争，不只是资产和协议之间的竞争，也会是 AI Agent 生态和应用数量的竞争 谁能让更多人低成本创造工具，谁就更有机会成为下一阶段基础设施的一部分 这个交易信号案例只是一个开始 AI Agent 正在逐渐成为连接用户、数据和链上应用的新入口

@jitendraballa · X

@johncalvo · X

Built an entire YouTube research platform with @AnthropicAI Claude Code. a YouTube research tool that treats entire channels as a searchable transcript database rather than individual videos. Any YouTube channel. Every word. Fully searchable. Track how topics trend, peak, and evolve across hundreds of videos. Researching what someone said on YouTube means watching hours of footage and hoping you find it. ChannelScout extracts full transcripts from any channel, makes every word instantly searchable, and tracks how topics trend over time, without watching a single video manually. Paste a YouTube channel or playlist URL and it transcribes and indexes every transcript. Follow multiple channels and they all land in one private library. New videos on followed channels are auto-transcribed and added to your library the day they publish. Beyond YouTube it accepts any yt-dlp-supported URL including Vimeo, TED, and SoundCloud, and you can upload local files directly

@kitbasedev · X

We just launched, check us out at

royashbrook · HN

Show HN: Mtok.market – a non-custodial spot market for AI inference tokens