单人软件
Software for One

原始链接: https://www.ajwaxman.com/writing/software-for-one

受罗宾·斯隆(Robin Sloan)2020年关于“个人软件”的文章启发,作者探讨了人工智能辅助编程的兴起如何将软件开发转变为一种如同“家常烹饪”般的体验。 以往,构建自定义应用程序需要深厚的技术专长和大量时间。如今,AI 智能体使得快速创建高度个性化的工具成为可能——例如个性化健身追踪器、婴儿睡眠监测器和专业教育应用,只需几天甚至几个晚上即可完成。通过聚合来自不同来源的个人数据并利用大语言模型提供情境感知洞察,这些应用解决了主流商业软件所忽视的利基问题。 由于开发成本和技术门槛的降低,软件现在可以是短期的;如果某个工具只需要使用几个月,那么投入精力去开发也是值得的。作者认为,“个人计算”终于变得真正个性化了,并正朝着这样一个未来迈进:人们将不再依赖通用的、基于广告的商业产品,而是习惯于通过简单的自然语言指令构建自己的软件。随着这些工具变得触手可及,个性化软件很可能会取代通用应用成为消费者的标配,从而实现人们长期以来对于直观、灵活且自主的数字环境的愿景。

Hacker News 的讨论聚焦于“个人软件”这一日益增长的趋势——即个人为满足特定需求而构建的定制化应用程序,而大语言模型(LLM)的出现加速了这一进程。 支持者认为,人工智能辅助编程让用户能够快速开发利基工具(如追踪器、遥控器或管理器)。这些工具因无需考虑商业扩展性或广泛的可维护性,往往优于应用商店中的通用产品。这种“随心编码”(vibe coding)的方式,让用户能以低廉的成本快速解决各类个人问题,涵盖从爱好整理到专业的家庭管理等方方面面。 然而,讨论也指出了其中的显著阻力: * **平台守门人:** 用户对苹果和谷歌的封闭生态系统表示不满,这些生态系统设置了高昂的开发者费用和沙盒限制,为运行私有、本地构建的软件制造了障碍。 * **依赖性与主权:** 批评者指出,依赖人工智能订阅和服务托管会带来持续的成本及安全风险。 * **复杂性:** 尽管简单的工具易于构建,但一些开发者认为,稳健、高质量的软件仍然需要专业的工程严谨性。 归根结底,参与者将这一转变视为迈向个人计算主权的一步;在这一趋势下,软件正逐渐被视为一种即用即弃、量身定制的实用工具,而非僵化的成品。
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原文

In 2020, Robin Sloan wrote about BoopSnoop, a messaging app he built for his family. Four people downloaded it. He considered this a resounding success. His point was simple: an app can be a home-cooked meal. You don't need scale. You don't need users. You cook for the people you love.

The app took him a week to build, half of it lost to code-signing purgatory. He wrote: "In a better world, I would have built this in a day, using some kind of modern, flexible HyperCard for iOS."

The time is now

Six years later, the essay resurfaced on X when Thariq wrote that "personal software was a bit early in 2020 but in 2026, it really can be as personal as a home cooked meal, or a handwritten letter."

Lee Robinson wrote about the same shift. AI has made "personal computing" actually personal. He and his wife built a baby tracker because they didn't need "user profiles, badges, subscription tiers, or any other extra features."

My smoothie knows my mileage

I spent the past six months building way too much personalized software:

  • A sleep app that runs our sleep consultant's plan
  • A fitness app that sizes my smoothie to that morning's run
  • A marathon plan built from my races, not my age
  • A "Duolingo for jazz" that quizzes me on chord voicings from my piano lessons
  • A medical records tool that flagged gaps before a specialist visit

Our sleep consultant's plan arrived as a PDF full of conditional logic: wake windows, nap caps, what to do when a nap fails. Turning it into an app took a week of evenings. Now my wife, our nanny, and I share one live schedule that re-plans itself when a nap runs short.

My fitness app is built around my goals and connects data sources in a way no single app can. It knows my weekly run schedule, courtesy of the marathon app below, so it adjusts my daily calorie targets based on that morning's run distance and intensity. It tells me how many extra carbs and protein to eat before and after long runs, and reminds me to carb load the night before. It knows my smoothie recipe, eight ingredients I weigh out every morning, and sizes each portion to that day's training.

The fitness app in action

My running app skips the plan templates and derives everything from my Strava history and race results, including heart rate zones computed from races I ran instead of a formula involving my age.

The running app in action

Sloan's sovereignty point holds up too. "There will be no sudden redesign, no flood of ads, no pivot to chase a userbase inscrutable to us." My wife's favorite feature in the sleep app will be there as long as she wants it.

My stack

I'm been using the same stack for a couple years now and continue to love it. It lets me build fast and gives me full control over implementation details.

There are plenty of other great ways to do this, including less technical tools like Claude Artifacts, Replit, and Lovable that can get you a working app without touching a terminal.

Cost

The whole thing costs me about $160/mo: $100 for Claude Code Max, $10 in Anthropic API usage, $20 for Vercel, and $30 for Neon.

That's probably more than I'd pay for subscriptions to all these apps combined. But the bulk of the cost is my Claude subscription, which I'd keep regardless. Most of the Neon and API costs come from my slightly larger projects, nycjazz.guide and Claude Code Daily, not the personal apps. Before I upgraded from Claude Pro to Max it was under $100/mo.

Most of these services have generous free tiers, so if you're running one or two apps you could likely keep it to a $20/mo agentic coding subscription and ~$5-10/mo in model API usage.

Learnings

  1. The cost to build dropped off a cliff. The sleep app took a week of evenings. The fitness app took a weekend. The jazz quiz took a single evening after the kids went to bed. A year or two ago I wouldn't have considered building any of these: too slow to build, even harder to maintain. Imagination is now the limiting factor.

  2. Maintenance is surprisingly easy. At least so far. Sloan's essay has a running gag in its yearly updates: "I have added one (1) feature, at my mother's request." In 2020 that made sense, because each change cost him a fight with Xcode. I've found fixing bugs, adding new features and dependency bumps to be easier than ever. 9/10 times a feedback screenshot shared with Claude gets the job done.

  3. Aggregate data, add an LLM. The cost drop doesn't just mean more apps, it means apps can be far more personal. Most of mine follow the same shape: pull data from multiple sources, combine it in one place, and use an LLM to generate insights from the full picture. My fitness app combines nutrition, sleep, weight, and training data that lives in four separate apps, then uses that context to make recommendations none of them could alone. I think this pattern will spread to professional tools too.

  4. Ephemeral is fine. We used the sleep app for about four months. Our son sleeps through the night now, so we retired it. If the app had taken me months to build, that might sting. Because it took a week, I'm just glad it worked when we needed it.

  5. AI floods big markets and unlocks small ones. Yes, AI produces endless derivative apps. But the same tools also let me build apps for my household that no company would bother making. Beyond my household, I built nycjazz.guide for NYC jazz fans and claudecodedaily.com for Claude Code developers, audiences too small for a business but worth serving.

  6. Good APIs matter more than ever. I switched from Cronometer to FatSecret because FatSecret had a better API. My fitness app pulls from Strava, Oura, Withings, and FatSecret, and the quality of each integration depends on how well the API is designed. As more people build personal software, users will expect their apps to have APIs and MCPs worth connecting to.

  7. Building is the point, not just the result. These apps solve real problems for me and the people I care about: how well our son sleeps, my health, my running. That part is rewarding. But I also spend my evenings after the kids are asleep building these instead of watching Netflix or scrolling X. It's my preferred source of entertainment now.

  8. It's not just fun. It's addictive. Agentic coding has slot machine mechanics. You're one prompt away from the next feature or unlock, so you keep pulling. The irony isn't lost on me: I've ruined more than a few nights of sleep building apps to improve my health.

Looking ahead

My approach is still too technical for most people. You need to be comfortable with a terminal, a database, and deployment pipelines. But I don't think that lasts. Sam Altman posted recently about sending ChatGPT a single message from his phone: plan a trip for nine friends, build a site to coordinate, draft the invite email. It worked. The prompt was one paragraph long.

If that's where the tools are heading, building personal software won't require a developer's stack for much longer. I kept building these apps because no app in the App Store knows my smoothie recipe, my race history, or my sleep consultant's rules. I think that frustration is common. Once the barrier drops far enough, a lot of people will build their own.

And once you use an app that actually knows your context, the generic version feels broken. I wouldn't be surprised if truly personalized becomes the new baseline consumer expectation.

Sloan wished for "some kind of modern, flexible HyperCard for iOS." He got something stranger: you describe what you want in plain English, and an agent builds it. His better world has arrived.

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