The golden age of Vibe Coding: Open source is quietly dying.

Author: Yi Tao

Over the past year, Vibe Coding has almost completely rewritten the way programming is done.

You no longer need to manually "write" code line by line. Just tell Cursor, Claude, or Copilot: what feature I want, what technology stack to use, and ideally, "it should feel like a certain product," and let AI do the rest.

Many people who couldn't write code before were able to "create things" for the first time. From a personal perspective, this was almost the golden age of software development.

However, there's a crucial, often overlooked premise: AI doesn't create code out of thin air; rather, it invokes and integrates existing human wisdom. When you say, "Make me a website," AI is actually silently referencing the logic and structure accumulated from countless open-source projects on GitHub.

Vibe Coding's core capabilities are built upon the learning and reorganization of these open-source codebases.

Recently, a research team from Central European University and the Kiel Institute for the World Economy published a paper titled "Vibe Coding Kills Open Source" (https://arxiv.org/pdf/2601.15494v1), revealing the hidden crisis behind the Vibe Coding boom.

The paper points out a truth:

Vibe Coding may be fundamentally undermining the open-source ecosystem that underpins the entire software world.

Since August 2022, the proportion of Python developers in the United States using AI programming has begun to rise significantly.

01 The "Invisible Infrastructure" of the Digital World

To understand what this paper is worried about, we must first clarify one thing: what is open source software and where does it fit into our lives?

Many people may not have a real understanding of open source software, but in reality, almost all the digital products people use every day are built with open source software at their core.

When you wake up in the morning and pick up your Android phone, the underlying Linux operating system is open source software.

When you open WeChat and browse your chat history, the database that stores every piece of information for you is SQLite, which is open-source software.

When you browse Douyin or Bilibili during your lunch break, FFmpeg, which is also open-source software, is responsible for video decoding and playback in the background.

Open source software is like the sewers of the digital age. You use it every day without even realizing it .

You only realize its importance when it malfunctions.

The Log4j vulnerability in 2021 is a prime example. Log4j is the most widely used logging framework in the Java ecosystem, used to record events and information during application runtime.

Most ordinary users have never even heard of it, but it runs in the background on billions of devices worldwide, from Apple and Google's cloud servers to government systems around the world.

In late 2021, a vulnerability known as "Log4Shell" was discovered. This vulnerability allowed hackers to remotely control servers around the world as if they were operating their own computers. The entire internet infrastructure was instantly exposed, forcing global security teams to work overtime to fix it. Its widespread impact and the difficulty of fixing it made it one of the most serious security crises in internet history.

This is the essence of open source—it is not a product of any particular company, but a "public good." Because it lacks commercial attributes, the maintainers who write the code often cannot directly charge for the project.

Their rewards are indirect: gaining fame through projects and landing jobs at big companies; earning income by providing consulting services; or relying on community donations.

This model has been operating for decades, relying on "direct interaction." Users read documentation, submit questions, and like/recommend software when using it. This attention flows back to the maintainers, transforming into motivation for continuous maintenance.

And this is precisely the connection that Vibe Coding is severing .

02 How did AI gradually "starve" open source?

Before Vibe Coding, the development model was like this: you would download an open-source package, read the documentation, encounter a bug, submit an issue on GitHub, and if you found it useful, you would give it a star to show your support.

The maintainers thus gain attention, which translates into revenue, creating a closed loop .

With the advent of Vibe Coding, you only need to tell the AI what functionality you want, and the AI will automatically select and combine open-source code in the background to generate a "usable implementation".

The code runs, but you don't know which libraries it uses, let alone look at their documentation or community.

The paper calls this change a " mediation " effect—the attention and feedback that were originally passed directly from the user to the maintainer are intercepted by the AI as an intermediary layer.

What will happen if this mechanism continues?

The authors of the paper constructed an economic model simulating the open-source ecosystem. They likened developers to entrepreneurs deciding whether to "enter the market" at different quality levels, investing in development costs first, and then deciding whether to open-source and share based on market feedback. Users, on the other hand, have to choose from countless software packages and decide whether to "use them directly" or through an "AI intermediary."

The model ran and revealed two opposing forces.

The first benefit is efficiency improvement. AI makes software easier to use and reduces the cost of developing new tools. This should theoretically incentivize more developers to enter the market, increasing supply.

The second scenario is a shift in demand. When users turn to AI intermediaries, maintainers lose the revenue from direct interaction, which reduces the returns for developers.

However, in the longer term, when the second force (demand shift) is stronger than the first (efficiency improvement), the entire system will tend to shrink.

This manifests as a higher barrier to entry for developers, with only the highest quality projects worth sharing, leading to the disappearance of medium-quality projects and ultimately a decline in both the number and average quality of software packages on the market . While individual users may enjoy the convenience of AI in the short term, the long-term benefits actually decrease because there are fewer high-quality tools available.

Simply put, the ecosystem has fallen into a vicious cycle. And once the foundation of the open-source ecosystem weakens, the capabilities of AI will also deteriorate.

This is a point repeatedly emphasized in the paper: Vibe Coding improves productivity in the short term, but in the long term, it may actually reduce the overall level of the system .

This trend is not a purely theoretical assumption, but is happening in real life.

For example, Stack Overflow's public Q&A traffic has declined significantly since the rise of generative AI. Many questions that would have been discussed in public communities have been moved to private AI conversations.

After ChatGPT was launched, the number of questions on Stack Overflow began to decrease significantly.

For example, projects like Tailwind CSS have seen a continuous increase in downloads, but document access and commercial revenue have declined.

The project is being used extensively, but it is becoming increasingly difficult to translate into meaningful returns for maintainers.

03 When will the Spotify of the Coding world appear?

Despite the problems with Vibe Coding, the productivity gains it brings are real, and no one can go back to a world where AI Coding doesn't exist.

The more fundamental problem is that when AI becomes the new intermediary, the old incentive structure is no longer applicable.

In the current structure, AI platforms derive immense value from the open-source ecosystem without incurring any corresponding costs in maintaining that ecosystem. Users pay for AI, AI provides convenience, but the open-source projects and maintainers that are invoked often receive nothing in return.

The authors of the paper proposed the following idea:

Restructure the way benefits are distributed .

Just like in the music industry, where streaming platforms like Spotify share revenue with musicians based on play volume, AI platforms can track which open-source projects they've called and return a portion of their revenue to the maintainers proportionally .

Besides platform revenue sharing, foundation grants, corporate sponsorships, and government funding for digital infrastructure are also important means of compensating for revenue loss for maintainers.

This requires the industry to shift its mindset from viewing open-source software as a "free resource" to viewing it as "public infrastructure that requires long-term investment and maintenance."

Open source software will not disappear; it is deeply embedded in the digital world and cannot be easily replaced.

But the era of open source, which relied on scattered attention, reputation building, and idealism, may have reached its limit.

Vibe Coding offers more than just a faster development experience; it's also a stress test of how public technologies can be continuously sustained.