@brankopetric00 · X

I've got two 😀: - automate your X presence - helps you break into DevOps

fenilsuchak · HN

OpenBenchmarks – Helping agents discover and pick the right SaaS APIs

u/DetlefRichter · Reddit

Made a prototype: EU AI Act Self-Assessment Tool. Worth turning into a product? Made a prototype over the weekend. Short questionnaire that classifies your AI system under the EU AI Act into one of five tiers (Prohibited, High-Risk Annex I, High-Risk Annex III, Limited-Risk, Minimal-Risk), with a plain-language explanation of your compliance deadline and next steps. The trigger: I keep seeing founders with AI features who have no idea whether they even fall under the Act, and legal advice i

@Patryk597153122 · X

Stwórz profesjonalne CV i sprawdź, czy przejdzie przez systemy ATS 👇 Zwiększ swoje szanse na znalezienie pracy

PaperCheck — 论文提交前自查工具，提供 Turnitin 查重 + AI 写作检测报告，帮助学生在正式提交前发现问题

@VaraadDurgaay · X

Solving the prb of observability in ai agents

eldar_hsnv · HN

Show HN: AI Notebook for Data Science – Kind of Like Cursor but for Jupyter

@SpalaAi · X

u/alexkendig · Reddit

I got tired of paying monthly for X tools, so I built a BYOK/Local browser extension instead Hey everyone, I use X/Twitter to share product updates, find customers, and build an audience. The problem is that most X tools eventually become another expensive subscription. TweetHunter, Typefully style tools, schedulers, AI assistants, outreach tools, it adds up quickly, often $30–$90/month. So I built Tweetback, a browser extension workspace for X that uses your own AI key in

@aidyor33641 · X

is crypto platform.  All in one place: *multichain token scanner *OCR-screenshoot to scan *crypto related news feeds *smart contract bug scanner-for devs to clean airdrops of their respective tokens before Cex/Dex contact info: [email protected]

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

fran-mora · HN

I gave 5 AI coding agents one prompt: grow a banana plant through its whole life in three.js: sprout, leaves, flower, fruit, rot, then pups that restart the loop. It's deceptively simple and yet very hard to get right from procedural code: you have to write working three.js and understand how the plant is actually built; how it hangs, ages and decays. Get the biology wrong and the code renders something weird. These are agents, not bare models (Claude Code and Codex for now). They can use tools, including playwright to check their work and improve it.