@Stemack · X

I vibe coded a sports capital tracker…would love your thoughts.

@tonylab_net · X

Just launched Yoink a fast way to grab & reuse content from the web Demo: Built to solve the constant copy/paste chaos when researching or building Lightweight. Minimal. Still early would love feedback #buildinpublic #indiehacker #webdev #productdesign #startups #nocode #AItools

@cleanmycsv_app · X

hi alisha, just shipped to fix corrupted utf-8, missing zeros and bad formatting before importing to crms. building in public now 🚀 let’s connect!

@bharattpawarr · X

Just launched Built with Astro + Cloudflare features: YouTube Subtitle Downloader YouTube Thumbnail Downloader 🔗 #BuildInPublic #AstroJS #JavaScript #Cloudflare

@MEJ50749 · X

用 @dappOS_com coding 做了一个美股信号网站： 它和普通美股行情网站最大的区别是：普通网站更多是“给你看行情”，而这个网站更像一个“辅助交易工作台”。 大多数美股网站会把价格、涨跌幅、新闻、财报、K 线分散展示出来，信息很多，但用户还要自己判断： 哪只股票值得看？ 现在是什么信号？ 这个信号强不强？ 有没有触发提醒？ 后续要不要复盘？ 我这个站的核心思路不是堆信息，而是把交易前的观察流程做成工具： 1. 市场总览不是单纯看涨跌 首页会把美股标的放进观察池里，比如 AAPL、NVDA、MSFT、GOOGL、AMZN、META、TSLA 等，不只是显示价格，还会结合涨跌幅、成交量、市值、PE/PB、行业、52 周区间等信息，让我先快速判断哪些票值得继续看。 2. 最重要的是信号扫描器 这个功能是普通行情站很少直接做成工作流的地方。 网站里有“智能信号扫描器”，可以扫描技术形态，并把信号归类成突破、反转、动量、超卖、超买、金叉、死叉、背离等类型。 比如： NVDA 出现强势突破、量能放大、均线多头排列； AAPL 出现 MACD 金叉、RSI 超卖反弹、布林带下轨支撑； MSFT 出现 MACD 背离，需要注意短期回调； TSLA 出现均线死叉，提示中期下行压力。 这就不是简单告诉我“今天涨了多少”，而是帮我回答一个更交易化的问题： 这只股票现在为什么值得关注，关注点在哪里？ 3. 个股详情页更像交易前检查清单 普通网站的个股页往往是行情 + 新闻 + 财务数据。 我这个站的个股详情页更偏“交易前判断”：价格、评级、52 周区间、K 线/成交量、基本面、技术信号、资讯都放在一起。 它的价值是把“发现信号”之后的下一步接住。 扫描器告诉我哪只票有异动，详情页帮我进一步看这个信号有没有质量。 4. 提醒中心是我最喜欢的功能 这个站不是看完就结束，而是有 Alerts Center。 里面可以看到全部提醒、已触发提醒、等待中提醒，还能新建价格/信号提醒。 比如： NVDA 突破 900 美元触发提醒； AAPL 出现 MACD 金叉提醒； TSLA 等待成交量异常触发； META 跌破支撑提醒止损风险； AMZN 突破近期高点提醒动能增强。 这和普通美股网站最大的差异就在这里： 它不只是信息展示，而是把“观察 →

barretlee · GitHub

agent-pulse Evidence-backed AI industry intelligence — trends, source updates, daily data refreshes, and weekly decision briefs.

__mp · HN

I built my own weather prediction / visualization app: https://wx.rsp.li (on-device temperature lapsing, on device interpolation modes, user-selectable aggregations, etc…). One of these days I should do a writeup. I also asked Claude to build a photo gallery for me https://places.pascalspoerri.ch (HDR, map support, similar images)

u/dooddyman · Reddit

I launched 2 SaaS. First failed brutally. Second hit $5k MRR in 3 months. What worked and didn't. tldr: My first AI SaaS failed because I built blindly, outsourced marketing, and had no clear ICP. My second product hit $5k/mo in 3 months because I built an audience first, obsessed over SEO and distribution, and targeted a specific niche. I launched my first AI SaaS last year, kept it alive for about a year now. It's making less than $50 mrr and i'm thinking of closing it. Here's what went

u/maybeImakemoney · Reddit

I built the thing. Now I am not sure the base use case is one people will pay for. Founder here. This started as a side learning project to see whether an LLM could answer questions about Excel data, back when they could not do it well. I built the first version on n8n, with workflows that ingested files, generated metadata with an LLM, and answered questions against the converted data plus that metadata. Then I started using it for my own analysis and report generation, saw that the time sav

@im_pradee_p · X

Backend as a service

u/Secret_Appeal6271 · Reddit

Agents are more capable, and susceptible to exploits, than ever. We're working to stop this from hurting users. AI agents are starting to get real access like GitHub tokens, cloud credentials, customer data, deploy permissions. Not coincidentally, the rate of major cybersecurity incidents is rising rapidly. See for yourself: https://epoch.ai/data/cve?view=graph https://genai.owasp.org/resource/state-of-agentic-ai-security-and-governance/ My friend and I, both AI researchers, are working o

@ebrahim_dev3 · X

An interactive, high-contrast weather radar application. The system provides real-time atmospheric visual layers over high-resolution satellite imagery with distinct airflow, thermal contours, and storm tracks.