@Fresno_Famous · X

Replit built website getting organic traffic…. #replit #ai #vibecoding #bigyellowmemorial #thebigyellowmemorial

u/Funky_Chicken_22 · Reddit

OSS to SaaS positioning problem: when the user persona and the buyer persona are completely disjoint Founder here. Sharing a positioning problem I think a lot of OSS-to-SaaS founders hit and don't talk about publicly. Context: I have been running an OSS project (world-model-mcp) with ~2,500 monthly PyPI installs. Two weeks ago I opened up the hosted companion, Etch, at etch.systems. Launched publicly on Product Hunt at 12:00 PDT yesterday. The positioning problem: OSS user persona: in

@zuess05 · X

Shipped some banger updates to

Deep Nostalgia AI — 借助人工智能照片动画，将家庭照片转变为引人入胜的动画视频，为珍贵的回忆注入活力的网站

@KWSKAN · X

Check out what I just built with Lovable! #HongKong #MarkSix #Lottery #WinnerWinnerSteakDinner #HKJC

u/ComfortableCheap1669 · Reddit

I built a way to see the decisions behind an AI-assisted project, not just the final repo I kept running into a weird problem with projects I built using AI. Once the project is finished, GitHub shows the result pretty well. But almost none of the process survives. The first approach that didn’t work. The bug that changed the architecture. The point where I realized I was solving the wrong problem. The AI suggestion I ignored. Why v2 looks different from v1. You

u/Rcoo232 · Reddit

I built a council of 5 historical figures that debates your hardest life decision (based on Karpathy's LLM Council) A few weeks ago, I came across Karpathy's "LLM Council" concept. You ask multiple Agents the same question independently, have them anonymously peer-review each other, then synthesise a final answer. The peer-review round is the genius part; models get surprisingly honest when critiquing anonymised responses. I turned it into a consumer product where the council members are hi

u/G1a9b9r9y · Reddit

I built a tool that shows if you would've panic-sold during a real market crash Weekend project: a test where you relive a stock's worst historical crash day by day, and decide whether to sell or hold at each point. At the end it shows how much return you'd have left on the table by panic-selling vs holding. Posted it on an Italian finance sub first — got genuinely useful feedback (turns out showing the ticker upfront made it too easy to guess the outcome), so I just shipped a v2 where the

theill · HN

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

@GrindOxfor6559 · X

u/ICARUS_2X · Reddit

Spent 7 months building a FOSS platform for natural-language chess analytics (No LLM) Hey guys, I've released CHONSE2, an open-source game review platform that offers unlimited analysis and move explanations without using hallucination-prone LLMs, running entirely in your browser. chonse2.com But Lichess is free, so why use this? Some have asked. It expands on Lichess's feature set a few different ways: Full analysis (accuracy/elo estimations/eval graphs, etc) requir