把你的时间和金钱给 Django,而不是你的代币。
Give Django your time and money, not your tokens

原始链接: https://www.better-simple.com/django/2026/03/16/give-django-your-time-and-money/

作者认为不应将LLM作为贡献Django代码的主要工具,尽管它们在其他地方很有用。虽然LLM可以加速开发,但Django的长期稳定性和高质量标准需要贡献者深入理解——而LLM可能会掩盖这一点。 仅仅提交未经真正理解的LLM生成的代码,会阻碍Django社区的协作精神,并让审查者面对“理解的假象”而士气低落。 相反,LLM应该*补充*学习,帮助理解和润色沟通,并公开其使用情况。核心信息是,为Django贡献是关于成长和社区,真正的价值在于开发者的理解,而不仅仅是贡献者名单上的一个名字。作者建议向Django软件基金会捐款,而不是将资金用于缺乏真正理解的LLM辅助贡献。

这个Hacker News讨论围绕着开源项目,特别是Django,在人工智能生成代码日益普及的时代所面临的挑战。一篇文章指出,一个项目鼓励捐款,而不是接受可能质量较低的人工智能贡献。 评论者们讨论了一种日益增长的趋势,即项目实施更严格的贡献指南——披露人工智能的使用情况、要求对拉取请求进行工作量证明,甚至限制直接提交问题——以保护维护者的时间和精力。 一位经验丰富的Django开发者分享了他们尽管经验丰富,却难以为框架做出贡献的困难,并表示人工智能工具*可能*有助于新贡献者。然而,他们同情那些被潜在劣质提交淹没的维护者。总体情绪是,开源维护者面临的负担越来越重,财务支持可能比代码贡献更有价值,尤其是在当前形势下。 多个链接指向相关的讨论以及Debian对此问题的深思熟虑的方法。
相关文章

原文

Spending your tokens to support Django by having an LLM work on tickets is not helpful. You and the community are better off donating that money to the Django Software Foundation instead.

We’re in a new era where people don’t have to type out all of their code. I used an LLM to build a good part of the new functionality in the djangonaut.space site. I know I wouldn’t have shipped that much in that amount of time without using an LLM.

But Django is different. The level of quality is much, much higher. This is because it has a much larger user base, it changes slowly, and the community expects it to be in use 20 years from now. It’s partly why it’s such an honor to have your name among the list of contributors.

This isn’t about whether you use an LLM, it’s about whether you still understand what’s being contributed. What I see now is people who are using LLMs to generate the code and write the PR description and handle the feedback from the PR review. It’s to the extent where I can’t tell if there’d be a difference if the reviewer had just used the LLM themselves. And that is a big problem.

If you do not understand the ticket, if you do not understand the solution, or if you do not understand the feedback on your PR, then your use of LLM is hurting Django as a whole.

Django contributors want to help others, they want to cultivate community, and they want to help you become a regular contributor. Before LLMs, this was easier to sense because you were limited to communicating what you understood. With LLMs, it’s much easier to communicate a sense of understanding to the reviewer, but the reviewer doesn’t know if you actually understood it.

In this way, an LLM is a facade of yourself. It helps you project understanding, contemplation, and growth, but it removes the transparency and vulnerability of being a human.

For a reviewer, it’s demoralizing to communicate with a facade of a human.

This is because contributing to open source, especially Django, is a communal endeavor. Removing your humanity from that experience makes that endeavor more difficult. If you use an LLM to contribute to Django, it needs to be as a complementary tool, not as your vehicle.

Use an LLM to develop your comprehension. Then communicate the best you can in your own words, then use an LLM to tweak that language. If you’re struggling to convey your ideas with someone, use an LLM more aggressively and mention that you used it. This makes it easier for others to see where your understanding is and where there are disconnects.

There needs to be understanding when contributing to Django. There’s no way around it. Django has been around for 20 years and expects to be around for another 20. Any code being added to a project with that outlook on longevity must be well understood.

There is no shortcut to understanding. If you want to contribute to Django, you will have to spend time reading, experimenting, and learning. Contributing to Django will help you grow as a developer.

While it is nice to be listed as a contributor to Django, the growth you earn from it is incredibly more valuable.

So please, stop using an LLM to the extent it hides you and your understanding. We want to know you, and we want to collaborate with you.

联系我们 contact @ memedata.com