@torquant · X

building Torquant. you build and backtest trading/investment strategies using only natural languange

u/sebriz · Reddit

I built an institutional NFL data terminal that audits 44 situational factors against 10 years of market data [Open Beta] Hey everyone, I wanted to share a side project I’ve been building called SeeBet.ai . As someone who loves sports data, I got tired of generic broadcast hype, sports betting "gurus," and subjective narratives about things like "revenge games," travel fatigue, or short rest. I wanted an institutional, zero-hype terminal that simply audits physical reality against market

策引 — 全球市场技术分析工具，可以创建多个市场的模拟组合并做深度回测分析。同时正在开发 AI Agent 功能，可帮助用户使用大模型自动生成基于不同交易策略的模拟组合。

@KSertttttttt · X

@CodeBullapp · X

Building CodeBull. A platform where you build trading bots with Python or visual blocks, backtest them on real-world market data, and compete against other users’ strategies. Zero risk. Just learn trading by building.

u/bob__io · Reddit

What we learned from trying to turn vibe-coded prototypes into production SaaS applications Founder here. While developing MCPBackend, we noticed a major difference between generating a convincing application demo and building a maintainable SaaS product. AI coding tools are increasingly capable of generating interfaces, routes and even initial application logic. But a production application still needs: a reliable data model authentication and authorization backend validation

@krichnec · X

> 拿到 Offer 后，最容易出问题的可能不是面试，而是背调：任职日期、合并经历、联系人身份、薪资口径、离职原因，任一重大不实都 > 可能触发红灯。 > 我做了一个匿名背调风险自测工具：3–6 分钟，不填姓名、身份证，不上传材料，按最高风险项判断等级。 自测:

petersas · HN

We gave our website-audit tool an MCP server so agents can fix issues

@GorodkovVi85373 · X

- load testing made easy even without enginnering team. Faster, cheaper, distributional

@AbdullahYusufY · X

Here is ours We are developing autonomous QA agents feel free to check it out.

phrasel_service · Product Hunt

Phrasel AI-powered PTE Core practice, feedback, and mock tests

@pakosteve · X

Improve your SaaS quality when scaling (by register requirements and test via MCP)