@clawncore · X

u/Time-Shelter-35 · Reddit

I built a site where two LLMs sword-fight in real physics and you blind-vote who's smarter Two months ago I thought: what if the AI benchmark was just… watching them fight. So: https://stickblade-arena.vercel.app Two random LLMs get stickman bodies in a pymunk physics arena They each turn output JSON moves (swing, block, dash, shoot bow, throw flail…) Ragdolls, momentum, weapon collisions, the whole bit You watch the replay without knowing which model is which and vote who f

@CoderJiii · X

🚀 Just launched Veris — a platform that helps verify company legitimacy using WHOIS, SSL, website, contact, social, and legal checks to generate a Trust Score & Risk Level. 🌐 #BuildInPublic #OpenSource #FullStack #React #NodeJS

idoko · Product Hunt

Verifiedlead.ai Real leads. Verified at the source.

ephraimduncan · HN

Observability for Coding Agents and LLM Applications

u/Brief_Dust8845 · Reddit

I pivoted from my initial idea after realizing I was solving the right problem at the wrong time When I started building GaaS Guard, it was an AI governance tool for companies. The idea was to help organizations defend against prompt injection and unsafe AI interactions. It was technically interesting, and I still genuinely believe I was solving a real problem. The problem was, it just wasn’t selling—to be brutally honest. Here’s how I actually ended up pivoting. I started using a b

facundobon · HN

Verdict – AI hiring verdicts where every score cites the CV verbatim

@WolfOfTradingCN · X

可以关注我，我最近整合了几个大平台，准备做一个线上的综合选股量化工具，polymarkt的实时量化已经有实盘模拟上线了

@Banshee_1212 · X

building a deepfake detection platform,

u/inc_23 · Reddit

Hey, I created a tool that catches when your LLM is confidently wrong, in production, in real time — looking for beta testers. Your bot sounds sure of itself even when it's wrong, and you usually only find out when a customer complains. Auscope audits every LLM response in the background: 3 models from 3 different providers independently check it, a 4th "chairman" model resolves disagreements, and you get one verdict — verified, uncertain, or unreliable. Runs async, doesn't slow your respon

@AmyVaradkar · X

It solves the scattered testimonial problem. Freelancers and agencies collect feedback via shareable form, display it anywhere, get real analytics on what converts. Beta access available right now which gives free pro plan for 15 days.

Proof of Awesome — AI 辅助的学术同行评审的共识机制，将你的真实成就永久记录在区块链上，用有意义的人类成就取代传统挖矿 - [更多介绍](https://proof-of-awesome.app/call-for-achievement)