
Mirrors - Test AI Agents Against a Mirror of Production
用生产追踪镜像来测试AI代理,捕捉错误和性能回归。
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用生产追踪镜像来测试AI代理,捕捉错误和性能回归。
aisinghal

为AI代理提供UI理解,含截图、设计规范和审计。
u/albanianspy · Reddit
the boring internal tool became the product we didn’t start with a saas idea. we were just annoyed that every agent-built UI looked weirdly related. so we made an internal finish gate: real screen references, a design contract, browser checks, and a ban list for generic AI defaults. one developer kept asking why it wasn’t public. eventually we stopped having a good answer. now UIZZE has a few paid users. builder disclosure: it’s mine, $9/mo or $99 lifetime: https://uizze.com current

在网站上启用AI代理交互,并从仪表板跟踪它们的行为。
not_wowinter13 · HN
Make any website agent-ready in one script tag

用 Etch 追踪、回放和验证 AI 代理的决策。
u/Funky_Chicken_22 · Reddit
OSS to SaaS positioning problem: when the user persona and the buyer persona are completely disjoint Founder here. Sharing a positioning problem I think a lot of OSS-to-SaaS founders hit and don't talk about publicly. Context: I have been running an OSS project (world-model-mcp) with ~2,500 monthly PyPI installs. Two weeks ago I opened up the hosted companion, Etch, at etch.systems. Launched publicly on Product Hunt at 12:00 PDT yesterday. The positioning problem: OSS user persona: in

观看AI在任务中失去对撤销记忆的访问权限。
coleaalkire · HN
Pupul, portable and revocable memory you carry into any AI

检查你的 AI 应用的安全性、隐私和治理准备情况。
u/Budget_Lawfulness_33 · Reddit
I made a tool that bridges the gap between vibe coding and actually knowing what you shipped A lot of people are shipping things they don’t fully understand anymore. With the new flagship models such Claude/Codex and people spending hundreds on AI subscriptions to build faster, apps are being shipped quicker than ever. But when you’re constantly throwing prompts at AI, adding features, and moving fast, it’s easy to lose track of what actually made it into your codebase. So I built: https


监控AI成本,预测支出,为团队设置成本限制。
@eastbase_studio · X

AI Trading Replay 是一个帮助交易者分析交易和行为模式的仪表盘。
@Crypto77qi · X
最近一直在@dappOS_com上体验 @xBubble_ai 的 Coding,这两天我给自己做了一个 AI Trading Replay(AI 交易复盘助手)。 👉 做交易时间越久,我越觉得,真正拉开差距的,并不是找到更多交易机会,而是不断减少重复犯同样的错误。 现在币圈已经有很多成熟的交易工具,行情、链上数据、资金流向、技术指标几乎都能找到对应的平台。但这些工具更多是在告诉我们市场发生了什么,却很少帮助我们分析,为什么面对同样的市场,每个人最终的交易结果却完全不同。 有时候并不是没有机会,而是因为犹豫错过了;有时候方向看对了,却因为害怕提前离场;还有时候连续几次亏损之后,下一笔交易开始变得犹豫,最终又错过真正的行情。 这些问题,并不是增加一个指标或者再多看一份数据就能解决。 所以我没有继续做一个新的行情工具,而是直接用 xBubble Coding 做了一个 AI 交易复盘助手。 它不会预测市场,也不会告诉我什么时候买卖,而是把每天的市场变化、自己的交易记录和决策过程整理下来,通过 AI 自动分析哪些判断是正确的,哪些错误一直在重复发生,并生成每天、每周的交易复盘,让整个交易过程形成一套可以不断优化的闭环。 整个开发过程也比我想象中轻松很多。 没有写代码,没有配置服务器,也没有部署环境,只需要把自己的需求描述清楚,一个可以直接访问的网站很快就搭建完成了。从原来的一个想法,到真正变成可以使用的产品,中间几乎没有任何开发门槛。 我觉得,这也是 xBubble Coding 最有价值的地方。 它并不是让大家重复开发一个市面上已经存在的软件,而是让每个人都能把自己的经验、工作习惯和思考方式快速变成真正属于自己的工具。 未来真正有价值的,或许不是拥有越来越多标准化的软件,而是每个人都能根据自己的需求,打造一个最懂自己的 AI 工作伙伴。

由AI驱动的代码审查工具,在microVM中运行代码来捕获更多错误。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db

查看 ChatGPT、Gemini 和 Perplexity 如何推荐您的业务,获取即时 AI 可见性评分。
nikhilsiyer · HN
Show HN: A tool that checks how your business appears in AI search

CoBro 用 AI 扫描竞争对手和市场数据,90 秒内判断初创企业创意是否值得构建。
@Ebrahim_Rio · X
Most founders skip validation and pray. I automated the "worth building?" check. AI scans competitors, Reddit, and market data → Cook or Kill in 90 seconds. Killed? It surfaces the pivot the data actually backs.