@pillarlabai · X

@aka_gaurang · X

There are bounties for creators to grow

@AppMailpilot · X

if you are doing bulk outreach by emails - lets warmup your emails for lifetime (for only early users) - each time now you don't have to worry about your mails if they are landing in spam go and break servers of

royashbrook · HN

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

@Evelyn_tree1 · X

I built a dashboard that just shows me where global money is flowing. Free public data, rebuilds itself twice a day. Every indicator answers exactly one question. Is money loose or tight? Flowing where? Buying what? Risk-on or risk-off? Crowded? If it doesn’t answer one of these, it doesn’t get a slot on the board. Reading got the same treatment: a hard cap of 45 min/day → 5 RSS feeds + 5 newsletters, each rate-limited (Damodaran: about one post a month). I’d rather miss a few things than let the feed become an anxiety machine. I don’t write code. Claude Code wrote every script — fetch, build, publish, twice a day on cron. I set the rules and keep the judgment; the machine does the running. Personal research notes, not investment advice.

@Aryan_2190 · X

Hyper Personalized Outreach for B2B

@cobraisystem · X

Manual retention can’t keep up with your acquisition - sees the slip, forecasts the churn, and triggers the save that keeps your growth compounding.

@mailthentic · X

@heydevottam · X

I'm building EVE — an inventory intelligence platform that helps D2C brands detect stockout risks, dead stock, and profit leakage before they become costly.

u/person-person12 · Reddit

The honest reality: Building more SaaS features can do more harm than good Nine months ago, my SaaS was called WealthLearn . At the time we had built Market Research, Backtesting, AI Tools, TradingView Indicators, Portfolio Analysis, Broker Connections, Automation, Education, and even a separate Futures Application for MacOS/Windows. The problem was that every time I explained the company, I had to list all of those things. Our team understood how everything connected b

felixdoerp · HN

Hi HN, The one thing AI reliably does is generate noise. Half the tools I see launch are just machines for producing more noise across more channels. And people are starting to see this in the form of emails in their inboxes as spam filters are struggling. There used to be a useful signal in email: the effort a sender put into customizing a message was a rough proxy for how relevant it actually was. AI killed that. Now it's customized slop with the appearance of effort with none of the cost. It is painful that the open internet / open channels have been abused like this. Captchainbox applies the idea of proof-of-work to email. If a sender is willing to do a bit of work to reach you, the message is more likely to be worth your time and the sender more likely to be real. The work is a traditional captcha. You can also set a pay-to-deliver amount if you want more friction. The proceeds of the delivery payment after transaction costs go to the Internet Archive and the EFF. The tool curr

@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