@victorvravatar · X

rrr_oh_man · HN

Alyph, a manual transmission for LLM context

@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.

u/safi1409 · Reddit

Instead of asking "what should I learn next?", I built a tool that diagnoses your actual gaps and tells you One pattern I keep seeing here (and had myself): you're learning a field - say backend development or ML - and at some point you don't know what you don't know. You've done tutorials, watched videos, maybe built some projects. But you can't tell if you actually have real understanding or just surface-level familiarity. I built a free tool called Cascade AI that tries to solve this.

@vela_cx · X

u/Background-Bed-8866 · Reddit

I built an AI back office that handles startup operations while I focus on shipping I build an AI back office for founders because I was tired of juggling 15 different SaaS tools for blogging, SEO, docs, analytics, customer support, and launches. Today I finally launched on Product Hunt. Happy to answer anything about the architecture, pricing, or why I chose specialized agents instead of one general assistant. try it out: Astrodesk submitted by /u/Background-Bed-8866 to r

yaoleifly · GitHub

ai-stock-pool AI industry-chain stock pool with US/A-share mapping, active discovery, policy pressure, and one-click deployment.

u/Still_Pirate1653 · Reddit

Built Aivora with a friend — describe a problem, get an AI tool + how to use it Hey — my friend came up with the idea, and I built it: Aivora. You type a problem in normal language (like “add subtitles to my YouTube videos”), and it recommends AI tools for that. For the top pick it also gives a short guide on how to actually use it — not just a link dump. There’s a curated set of real tools, plus a daily tip and some problem-specific pages. Link: https://tryaivora.vercel.

@0xdeusyu · X

想知道代理是不是真的把每个 AI 站都送到同一个出口？ 答案：并不是。 我做了一个 AI 分流测试： 它会探测 ChatGPT、Sora、OpenAI、Claude、Grok、Anthropic、Perplexity 等 AI 服务，通过读取各站点的 Cloudflare Edge Trace 信息，获取实际访问情况： 出口 IP Cloudflare 边缘节点（colo） HTTP / TLS / WARP 状态 访问延迟 然后根据落地位置进行归组。 这次测试结果： 6 个服务（覆盖 7 个域名）走美国出口。 唯一例外是 Sora，落在东京节点。 也就是说，同一个代理配置下，不同 AI 服务并不一定经过同一个出口。看起来“都能访问”，实际线路、节点和落地点可能完全不同。 整个测试工具纯前端实现，零后端。