@saysSerenaaa · X

Unshift lets you build web sites + web apps from a production-ready foundation instead of starting from scratch.

@thread_snoop · X

Give you claude/codex free access to search through reddit :)

u/bob__io · Reddit

What we learned from trying to turn vibe-coded prototypes into production SaaS applications Founder here. While developing MCPBackend, we noticed a major difference between generating a convincing application demo and building a maintainable SaaS product. AI coding tools are increasingly capable of generating interfaces, routes and even initial application logic. But a production application still needs: a reliable data model authentication and authorization backend validation

@ohdearkk · X

@Robhay3s · X

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

@gonelf · X

So many things - dead simple way to share projects within your team - dead simple base - no backend forms - ez directory submissions - a Lego event

g418572664 · V2EX

做了一个文档解析与记忆工具，专门辅助给传统行业做 AI 落地的老哥 现在 AI+的工作还挺常见的，就像大佬们说的，“所有行业的产品可能都会用 AI 重新做一遍”。最常见的就是各种 agent ，说要用 AI 赋能传统行业啥的，代替人类专家去处理海量的复杂资料、进行深度分析并做出决策。 举个例子，金融行业的“智能审计与尽调 Agent”。 过去，银行或投资机构想要给一家企业贷款或投资，需要人类审计师去读几十份、每份几百页的招股书和财务报表。现在虽然有了 AI ，但把文件一股脑全丢给它是不现实的，且不说烧 token 的问题，这些文档里有无数的跨行、跨列单元格表格，普通工具一拉，表格数据全串行了。如果 AI 把“第一季度利润”和“第二季度支出”的信息碎在一块，那得出的财务分析就完蛋了。 所以，现在要真想开发出一个能干活，还确保正确率的 agent ，就需要一个专业的、AI-native 的解析工具，把复杂的表结构和章节层级完整还原出来。我做的工具 Knowhere 就是干这个的： https://knowhereto.ai/?utm_source=v2ex 它能把复

@ServerForAgent · X