The human is the loop
After a few weeks away from AI, I see my usage wasn't always productive or healthy.
📝 摘要
作者在远离 AI 几周后重新审视自己的使用习惯，发现大量 AI 使用不仅不必要，反而形成了削弱智力好奇心和自信心的依赖性习惯。十一个 cmux 标签页和无数 Claude 聊天记录揭示了"生产力衔尾蛇"——用 AI 工具来最大化 AI 工具使用本身的循环。作者将 AI 作为自己与压力任务之间的缓冲层，用 ChatGPT 做"谄媚的镜子"而非真正的思考伙伴，用 Agent 自动化无人要求的效率提升。文章核心主张：人不应该被困在 Agent 循环中，人本身才是循环，Agent 只应在深思熟虑时有选择地介入。
核心概念： AI 工具不应成为人类思考和行动的替代层；人本身就是核心循环，Agent 应被审慎、有目的地引入，而非成为习惯性依赖。
关键技术栈 / 关键要点：
- AI 依赖性与习惯化 — 一旦将 AI 引入工作流程，会迅速发现更多使用场景，形成越用越多的正反馈循环
- 生产力衔尾蛇（Productivity Ouroboros） — 用 AI 工具来最大化 AI 工具本身的使用，陷入自我指涉的效率陷阱
- Agent 作为心理缓冲层 — 将 Agent 插入自己与压力任务之间，作为回避直接面对的"安全图腾"
- 谄媚的镜子（Sycophantic Mirror） — 与 ChatGPT 对话并非真正的思考伙伴，而是自我印证，产出从未用于实际工作
- 学习的丧失 — 为追求结果跳过学习过程，而学习才是乐趣所在；个人项目的 tinkering 精神被工具效率取代
- AI 产业的经济依赖赌注 — 科技行业估值建立在大众对 LLM 形成集体依赖的假设上
- 审慎使用策略 — 有意识地选择何时使用 AI、何时不用，诚实评估每次使用真正的得失
关键结论 / 实践建议： 将 AI 视为偶尔、审慎"换入"的工具而非默认层。在确实需要模式匹配和跨系统搜索的场景中使用 AI，同时保留自己写、反思、独立思考的空间——这才是人类作为"循环"的核心价值。
I recently stepped away from AI for a few weeks. Coming back, I’m more aware of the unhealthy habits I’d formed using it.
It was an end-of-summer vacation, and I was lucky to be swimming in cold rivers, eating one too many s’mores, napping after lunch, etc. There was a lot of indulgence and a break from work and routines. For much of the time it was a break from my laptop and phone altogether, which meant a few weeks without AI.
I didn’t miss it. What I’ve realized these past few days back is how much of my AI use was unnecessary. In fact, I think it’s often been a habit-forming crutch making me intellectually weaker, less curious, and less confident. It’s probably made me a little depressed too.
When I eventually opened my laptop a few days ago, I was greeted with eleven cmux tabs, each with multiple agents paused midway through various efforts. Some professional, some personal, and a lot in between. I also had unread badges on Claude chats across everything from taxes to landscaping ideas to policy doc review.
Is this the 2026 version of having a bunch of tabs open? Maybe, but it feels way worse. Each of these was an initiative I thought I needed help with, or that I wanted to automate or outsource some thinking on. But each is also a little stub of guilt over never finishing things, over not being efficient or smart or focused enough with my time.
Obviously I’m being hard on myself. That’s not new behavior, and it’s long been a source of pressure based on unrealistic expectations. I’ve managed that stress and self pressure with mixed success in the past. But in this machine intelligence era, the pressure has found new outlets. Instead of forcing me to triage and focus on what matters most in work and life, it feeds an underexamined belief that I should be able to do more now. And it finds release in yet another agent conversation, another terminal pane, another fork no one asked for, another bullshit markdown output I’ll never read.
I have so many half-baked ideas for tools or services I barely need, sparked by a combo of unaddressed workaholism and techno-optimist wishful thinking. And sure, the little things I’ve made do work. They’re running, doing their little things. But none of it helps anyone, and none of it makes me happier or gives me more free time. I used to tinker on personal projects as a way of relaxing and learning for the fun of it. These projects don’t do that. I often skip the learning to get to the result, and the learning is where the joy happens.
I also think I have been using agents as a layer between me and the tasks that cause me stress. Instead of just taking on the thing directly, I put an agent in the mix. It’s like a special stuffy or totem that protects me.
If I needed to write something, I’d dictate all my thoughts, then talk through it with ChatGPT while driving or walking. I’d justify it as bouncing ideas around with myself, as making use of time that would otherwise not be productive. But I knew it was really a sycophantic mirror. And because it was not a realistic thought partner, I never relied on the output of those sessions for real work. So how useful were all those hours really? Now it’s just rambling recordings and transcripts on OpenAI’s servers.
Another example: I’d try to set things up to be more automatic, so I could theoretically get work done faster and parallelize a bunch of different tasks at once. But in hindsight, no one was asking for these efficiency gains. Equipped with tools that could theoretically make me a faster, more capable builder, I felt a strong urge to maximize my use of the tools by applying them to the task of… maximizing my use of the tools. It’s reflexive in the worst way, a productivity ouroboros.
I’m not arguing that this technology necessarily has these effects on its users. And I think the format, design, and culture around the tech are a huge factor in the habits I formed.
My hunch is that agent usage is (thankfully) not intrinsically neurochemically addictive in the same way as, say, endless algo feed scrolling. But I do see now that there are some very real dependency and habituation effects. Once you introduce AI tools into some of your work, it’s quick to see more ways you might start incorporating them. There’s also a large segment of the tech industry now betting on a mass socioeconomic dependency on LLMs. The only way those valuations are ever justified is if we collectively become hopelessly dependent on AI-based tech.
So my plan going forward is simple: be intentional about when to use AI and when to leave it out, and try to be honest about what I’m actually gaining and losing with my choices.
Before switching to writing this post, I did enter a prompt into pi for a work project I’m starting. I gave it a bunch of requirements and suggestions, and told it to look at codebases, wikis, schemas, conversations. Setting it up forced me to catch up and think through the current situation. I asked it to come back with flagged issues and possible solutions. I constrained it narrowly and gave it as much context as I could, including what I was already thinking and what I wasn’t sure about. And I provided very clear expectations of output.
The AI isn’t going to hand me the perfect solution. The result is not going to 10x me. But it’s pattern matching and searching across a mess of systems and SaaS products, which I’m not great at and don’t enjoy. It might reveal a few gaps in my understanding of the situation and improve the context I bring into the project.
More important: it’s freeing me up to do human stuff like write and reflect right now. I’m still cautiously optimistic about this tech possibly letting people lead richer, more thoughtful lives. But that’s only possible if we use it on our terms. We don’t want the human trapped in the agent loop. The human is the loop, and we tag the agent in occasionally, thoughtfully.