@FourLeaf_AI · X

@gududubey · X

@matthew_meadows · X

Introducing Earth's daily zeitgeist, on a map. Trending, corroborated stories that scope to your view. S&P 500 & Today in History. Drop pins, subscribe to locations & follow users. Chat with Marco! Every place has a story...

u/Radiant_Freedom9451 · Reddit

Building a resume-tailoring micro-SaaS taught me that more features can weaken the product I’m the founder of ApplyBoost, a small SaaS for tailoring resumes to individual job descriptions. While building it, I made the classic mistake of thinking that every related feature would increase the product’s value. I added: AI resume tailoring ATS scanning Keyword matching Bullet rewriting Resume templates Application tracking Follow-up guidance Interview preparation Techni

Aural — 开源 AI 面试平台，支持语音、聊天和视频面试，提供自适应追问、结构化评分、面试练习与自托管 - [查看仓库](https://github.com/1146345502/aural-oss)

u/OriginalPosition1 · Reddit

CrowdWis - Ask first, then get routed to relevant people Disclosure: I’m the founder of CrowdWis. Most online communities make you choose a group before you know who is best suited to answer. I built CrowdWis around the opposite flow: write the question first, then the platform routes it to people based on their expertise, interests, and context. Replies stay private, and AI synthesizes the different perspectives into one result. The beta is live here: https://crowdwis.app/?utm_source=re

@Akisin1 · X

Listen Like You Live

@askjames_co · X

u/Puzzleheaded-Log-27 · Reddit

Building a multi-model AI deliberation tool taught me something about trust LLM Counsel isn't another wrapper around one model - it sends your question to a panel of frontier LLMs, has them peer-review each other anonymously, and an impartial "chairman" model returns one synthesized answer. Free to start, pay-as-you-go after, credits don't expire. What I've learned so far: people trust a synthesized answer a lot more once they can see that the models actually disagreed and how that disagree