@jordanunegbu · X

Develop apps and websites with natural language?

@OrchAppDev · X

- build the most complex iOS apps in one shot!

@zstmfhy · X

前段时间在推特上分享了阿里秒悟（Meoo），当时只是尝鲜，现在真用上了。 给女儿做了一个「专属绘本生成器」：选角色、输故事、AI 自动生成带插画的互动绘本。全程没写一行代码，从想法到上线，大概就一杯咖啡的时间。体验地址放评论区了 👉 官方地址： 用了一段时间，秒悟几个特点很明显： ✅ 说话就能做产品 不用写代码，直接用自然语言描述需求，AI 自动理解并生成完整应用。我这种非技术出身的人也能独立完成。 ✅ 全栈生成，一键部署 不只是生成个前端页面，而是前端 + 后端 + 数据库一次性搞定，生成完直接点部署就能拿到可访问的链接。阿里云的基础设施全内置，不用自己配服务器、买域名。 ✅ 蜂群模式，速度真的快 简单应用基本 1 分钟内出活。复杂一点的需求，多 Agent 并行处理，也比传统开发快很多。 ✅ 四大模型聚合，自动调度 集成了 Qwen、Kimi、GLM、MiniMax，系统会根据任务类型自动匹配最优模型，不是单一模型硬撑。 ✅ 可视化圈选修改 生成后不满意？直接圈选页面元素，用自然语言告诉它怎么改，AI 实时调整底层代码，所见即所得。 ✅ 技能市场 + 团队协作 可以加载别人封装好的 Skill 快速扩展功能，也支持多人实时协作编辑，适合小团队快速迭代。 ✅ 小程序也打通了 6 月份上线了微信小程序生成功能，从创建到审核发布全链路覆盖，对想做微信生态的朋友很友好。 现在还在免费体验阶段，注册送积分，每天登录还送。想快速验证想法、做个人项目或者内部工具，可以试一下。

u/aitoptools · Reddit

built adult discovery platform - what do you guys think? i'm very knowledgable in AI and i built an AI adult discovery platform, wanted to see what you think? pornprompt.ai - enjoy it! appreciate the feedback! submitted by /u/aitoptools to r/SideProject [link] [comments]

littlepp · HN

Speech Generation – Free text-to-speech in 18 languages

u/jm_ka · Reddit

SmartDocs - open-source docs framework with AI chat; just add your API key. SmartDocs is an open-source Markdown documentation with built-in AI chat. The pitch: write docs in Markdown, add your API key to .env, and every page gets a grounded AI assistant. Self-hosted, your data, your control. Tech: Next.js + Markdoc + Tailwind. No vector DB — uses graph-backed retrieval (keyword scoring + link traversal) inspired by Karpathy's LLM Wiki pattern. Live demo (no key needed): https://www.ge

@wyfcoder · X

最近做了一个 AI 修图网站：Picuro Photo Editor。 不用复杂参数，上传图片后，直接说出你想修成的样子，比如“更清晰”“电影质感”“日系清新”“蓝天白云”，AI 就会帮你生成效果。 目前还在早期版本，欢迎试用，也欢迎提建议 🙌

@rubs_murga · X

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

symuz · HN

LLM-enabled large data analysis

u/yousefemz · Reddit

18 months ago we weren't sure it was possible. Today we launched it. We kept asking ourselves one question for a year and a half: can an AI actually design a scalable backend from a description of how it should behave, not demo-ware, something that holds up in production? We didn't know. Some weeks it felt like the answer was no, or that we'd end up with code that looks right and falls apart the second real traffic hits it. We just launched it. You describe how your backend should behave,