使用AI有两种方式:一种是疯狂构建大量项目,但大多被废弃,沦为AI垃圾;
另一种是借助AI更快迈出第一步,回归真正的问题。
许多创业创始人沉迷用Claude、ChatGPT和各类AI智能体持续数月构建产品,却从未与真实用户交流。
AI并未让创业成功变得更容易,只是加速了部分环节。
真正困难的事情--承担人生风险、公开署名、面对当面拒绝、在无人相信时坚持--AI无法改变。
AI最大的危险是让人在自我构建的泡沫中误以为自己在做有用的事。
在AI时代,唯一的差异在于不断追逐真相,用现实反复敲打自己。
使用AI有两种方式:一种是疯狂构建大量项目,但大多被废弃,沦为AI垃圾;另一种是借助AI更快迈出第一步,回归真正的问题。许多创业创始人沉迷用Claude、ChatGPT和各类A...
使用AI有两种方式:一种是疯狂构建大量项目,但大多被废弃,沦为AI垃圾;
另一种是借助AI更快迈出第一步,回归真正的问题。 许多创业创始人沉迷用Claude、ChatGPT和各类AI智能体持续数月构建产品,却从未与真实用户交流。 AI并未让创业成功变得更容易,只是加速了部分环节。 真正困难的事情--承担人生风险、公开署名、面对当面拒绝、在无人相信时坚持--AI无法改变。 AI最大的危险是让人在自我构建的泡沫中误以为自己在做有用的事。 在AI时代,唯一的差异在于不断追逐真相,用现实反复敲打自己。
使用AI有两种方式:一种是疯狂构建大量项目,但大多被废弃,沦为AI垃圾;
另一种是借助AI更快迈出第一步,回归真正的问题。
许多创业创始人沉迷用Claude、ChatGPT和各类AI智能体持续数月构建产品,却从未与真实用户交流。
AI并未让创业成功变得更容易,只是加速了部分环节。
真正困难的事情--承担人生风险、公开署名、面对当面拒绝、在无人相信时坚持--AI无法改变。
AI最大的危险是让人在自我构建的泡沫中误以为自己在做有用的事。
在AI时代,唯一的差异在于不断追逐真相,用现实反复敲打自己。
Who can punch themselves in the face with reality the most? This is who will win in the age of AI.
I think there are two ways to use AI. You can just go off the deep end and start building a crazy amount of things. While it can be fun with your dozens of Claude and ChatGPT and agents and all that, most of it will be abandoned and not get used by anyone in the long term. And this is where you start getting things like AI slop and psychosis and all the things that people are starting to hate about AI generated anything.
And the other way is to take a step back and decide that okay, in the previous world, I would have had to spend all this time just to take the first step. Now with AI, I can take that first step much faster and actually get back to the real problem.
I have seen way too many startup founders delude themselves into building more and more for months without a single conversation with a real user. The builders and the technical people really struggle with this. If all you know is how to build, and you just use AI as an excuse to keep building more and more and more, you are just procrastinating and avoiding reality. And the thing is that you were probably procrastinating before AI as well. And now it has just become much more obvious when you do it with AI.
What is already easy for everyone will not create any lasting value for you. I don’t think building a successful startup has gotten any easier with AI. It’s just that certain parts of it have gotten faster. I don’t think speed of coding or having the right landing page copy or the right deck or presentation was ever the bottleneck in getting your startup off the ground, anyways.
There are so many failed startups and founders who spend so much time building something that didn’t work out. You will almost always hear that even before the AI era, they built way too much and they built too many irrelevant things. Instead of really being honest with themselves about whether what they are doing is actually working or not.
And the things that make a startup work, that make anything work, have always been hard and continue to be hard today.
Did AI make any of these easier? I don’t think so.
I know you want to use AI as an escape. It is so tempting. You get to sit in your bubble and imagine everything and see it come to life and your agent buddy will keep cheering you on while you get nothing done with your life. And I think that’s the biggest danger of AI. You convince yourself that you are doing something useful when you are not.
Don’t lose sight of what is real. Figure out why you were put on this earth. What do you need to do with your life? What kind of impact do you want to create? What are the projects that need you the most? What are you naturally good at? What can you do that other people will want?
I think in the AI era, the only delta left will be in relentlessly chasing the truth. And the only way to get it is to punch yourself in the face with reality again and again.
Adi | Built with Timbre:https://timbrehq.com
Aioga 编辑摘要:使用AI有两种方式:一种是疯狂构建大量项目,但大多被废弃,沦为AI垃圾; Aioga 将其归入「技巧观点」方向,重点关注它对真实使用和行业竞争的影响。
背景分析:实践类内容的价值在于是否能被复现、是否有明确边界,以及它能否转化为稳定的开发或工作流方法。
Aioga 判断:这条动态更适合作为行业观察信号,当前信息足以建立线索,但不足以推导长期结论。
影响分析:对相关团队而言,短期应先核对来源、可用范围和实际成本,再判断是否值得接入或跟进。 后续观察:继续观察示例是否可复现、工具版本变化、社区反馈和实际成本。
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抓取通道: 摘要聚合 · 原始域名: adi.bio
来源: Hacker News 热门(buzzing.cc 中文翻译)
原文链接: 打开原始来源
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Content record: source-page · Updated: 2026-07-14T16:07:18.060Z

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