PROMPT RECORD · 公开作品详情
"我想开发一款和 https://t.co/ICXDLwNfxh 一样的应用。"然后我就让 agent 去搭建，我开始接受它给出的所有建议。前…
公开 AI 图像创作记录，包含原图、提示词、使用模型、作者、标签与来源。
- 使用模型
- None
- 创作者
- @vitosmolenski
- 发布时间
- Sun Jul 19 20:52:47 +0000 2026
- 图片数量
- 1 张
完整提示词
源提示词按原始换行与标点完整保留"I want to build an app just like https://t.co/ICXDLwNfxh." Then I let the agent build, and I just started accepting its suggestions. I accepted everything up to my $100. Then I got curious. How far would this actually go? So I kept accepting. Past $200 I got a little more selective, only greenlighting what looked genuinely useful. I finally stopped at $300. Next prompt: "Add Clerk auth so many users can have their own time tracking." This was the part that impressed me most. The app had been built single-user, so the agent had real architectural work to do, rearranging everything around multiple users each owning their own isolated data set. It took its time and did it properly. Last prompt: "Create comprehensive docs for the app." It produced full in-app, searchable documentation that's honestly better than what most funded teams ship. $439 total. That's it. With what amounted to minimum effort on my part, I ended up with an enterprise-grade product. The numbers: 3 apps from one shared, type-safe API contract (web, native mobile, API server) 25 API endpoints 276 automated tests (194 API + 82 mobile), all green 35+ features shipped and merged 195 commits, 70,000+ lines of code, in 6 days ~97% of all commits landed in a single 24-hour sprint What actually got built: Google sign-in, cross-device server-side timers, focus sessions, daily goals with gentle nudges, weekly reports, photo uploads, full account management, and searchable in-app docs. It even executed a complete rebrand mid-flight (TimePulse → TimeBench) touching 200+ references without breaking a single test. The wildest part to watch: parallel AI task agents working in isolated environments, shipping and merging features simultaneously, while a main agent coordinated, reviewed, and kept everything green. I always wanted an app like this for myself. So I built it. Meet TimeBench 👇 https://t.co/WUcshDrxTE This is what happens when you reinvest $100 and trust the agents. @Replit @Franciscocrz @MannyBernabe @raymmar
提示词译文
译文与源提示词分开显示，不替代原文"我想开发一款和 https://t.co/ICXDLwNfxh 一样的应用。"然后我就让 agent 去搭建，我开始接受它给出的所有建议。前期我一路点击接受，一直花到 100 美元。后来我开始好奇：它到底能走多远？所以我继续接受。过了 200 美元之后我变得更挑剔一些，只放行那些看起来确实有用的东西。最后我在 300 美元这里停了下来。 下一条提示词是："加入 Clerk 鉴权，让多个用户都能拥有自己的时间追踪。"这一步是最让我印象深刻的部分。应用最初是为单用户构建的，所以 agent 真正做了架构层面的工作，把整个系统重新组织，让每个用户都拥有各自独立隔离的数据。它不急不躁，把这件事做得很到位。 最后一条提示词是："为这个应用编写完整的文档。"它产出了一套完整的应用内、可搜索的文档，说真的比大多数拿到融资的团队交付的文档还要好。 总共 439 美元。就这样。我这边基本只是最小的投入，最后得到了一个企业级的产品。 具体数字： 3 个应用，共享同一套类型安全的 API 契约（Web、原生移动端、API 服务端） 25 个 API 端点 276 个自动化测试（API 194 个 + 移动端 82 个），全部通过 35+ 个功能完成并合并 195 次提交，70,000+ 行代码，历时 6 天 约 97% 的提交集中在一次 24 小时的冲刺中完成 实际交付的内容：Google 登录、跨设备服务端计时器、专注会话、带温和提醒的每日目标、每周报告、图片上传、完整的账户管理，以及可搜索的应用内文档。它甚至在过程中完成了一次完整的品牌重塑（TimePulse → TimeBench），涉及 200+ 处引用，却没有让任何一个测试挂掉。 最让人看得过瘾的部分是：并行的 AI 任务 agent 在隔离环境中同时工作和合并功能，而主 agent 在一旁协调、把关，并保证所有测试持续绿灯。 我一直想给自己做一款这样的应用。所以我就做了它。认识一下 TimeBench 👇 https://t.co/WUcshDrxTE 这就是当你把 100 美元再投入进去、并且信任这些 agent 时会发生的事。@Replit @Franciscocrz @MannyBernabe @raymmar