Vibe Coding: Threatening the Open Source Ecosystem

Vibe Coding’s prosperity may be built on the ruins of the open source ecosystem.

In the past year, Vibe Coding has fundamentally rewritten how programming is done.

You no longer need to write code line by line. Just tell Cursor, Claude, or Copilot what functionality you want, what tech stack to use, and ideally, how it should feel like a certain product, and let AI handle the rest.

Many people who previously couldn’t code now have the ability to “create something” for the first time. From a personal perspective, this is almost the golden age of software development.

However, there is an overlooked premise: AI does not create code out of thin air; it calls upon and stitches together existing human knowledge. When you say “help me make a website,” AI is quietly referencing the logic and structure accumulated from countless open source projects on GitHub.

The core capability of Vibe Coding is built on learning and reorganizing these open source code libraries.

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,” revealing the hidden crisis behind Vibe Coding’s prosperity.

The paper points out a truth:

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

The Invisible Infrastructure of the Digital World

To understand the concerns raised in this paper, we first need to clarify what open source software is and its role in our lives.

Many people may not feel the presence of open source software, but in reality, almost all digital products we use daily are built on a foundation of open source software.

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 to check your chat history, the SQLite database that stores every message is open source software;

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

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

Only when it fails do you suddenly recognize its importance.

The Log4j vulnerability in 2021 is a typical 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 its name, but from Apple and Google’s cloud servers to government systems worldwide, billions of devices run it in the background.

At the end of 2021, a vulnerability called “Log4Shell” erupted. This vulnerability allowed hackers to remotely control servers around the world as if they were operating their own computers. The entire internet infrastructure was suddenly exposed, and global security teams were forced to make emergency repairs over the weekend. Its widespread impact and the difficulty of fixing it made it one of the most severe security crises in internet history.

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

Their rewards are indirect: gaining fame through the project leads to jobs at major companies; earning income through consulting services; or relying on community donations.

This model has operated for decades, relying on “direct interaction.” Users read documentation, submit issues, and give stars while using the software. This attention flows back to the maintainers, converting into motivation for ongoing maintenance.

However, this connection is precisely what Vibe Coding is severing.

How AI is Gradually “Starving” Open Source

Before Vibe Coding emerged, the development model was as follows: you download an open source package, read the documentation; if you encounter a bug, you submit an issue on GitHub; if you find it useful, you give it a star to show support.

Maintainers gain attention, which translates into income, forming a closed loop.

After Vibe Coding appeared, you only need to tell AI what functionality you want, and AI automatically selects and combines open source code in the background to generate a “working implementation.”

The code runs, but you have no idea which libraries were specifically used, nor do you check their documentation or community.

The paper refers to this change as a “mediation effect”—the attention and feedback that were originally directly transmitted from users to maintainers are entirely intercepted by AI as an intermediary.

What happens if this mechanism continues?

The authors of the paper constructed an economic model simulating the open source ecosystem. They compared developers to entrepreneurs deciding whether to “enter the market” at different quality levels, initially investing costs in development and then deciding whether to open-source based on market feedback. Users must choose among countless software packages and decide whether to “use directly” or through the “AI intermediary.”

The model revealed two opposing forces.

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

The second is demand transfer. When users turn to AI intermediaries, maintainers lose the income from direct interactions, which lowers developers’ returns.

However, in the long term, when the second force (demand transfer) outweighs the first (efficiency improvement), the entire system will shrink.

This is manifested by an increased barrier to entry for developers, where only the highest quality projects are worth sharing, while medium-quality projects disappear, ultimately leading to a decline in both the number and average quality of software packages in the market. Although individual users enjoy the convenience of AI in the short term, long-term benefits decrease as the availability of high-quality tools diminishes.

In simple terms, the ecosystem falls into a vicious cycle. Once the foundation of the open source ecosystem thins, the capabilities of AI will also deteriorate.

This is a point the paper emphasizes repeatedly: Vibe Coding increases productivity in the short term, but in the long run, it may lower the overall level of the system.

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

For example, the traffic of public Q&A on Stack Overflow has significantly declined after the popularity of generative AI. Many questions that would have been discussed in public communities have shifted to private AI conversations.

After the launch of ChatGPT, the number of questions on Stack Overflow began to decline significantly.

Similarly, projects like Tailwind CSS see a continuous increase in downloads, but documentation access and commercial revenue have decreased.

Projects are widely used but increasingly struggle to translate into meaningful returns for maintainers.

When Will the Spotify of Coding Appear?

Despite the issues posed by Vibe Coding, the productivity gains it brings are real, and no one can return to a world without AI coding.

The more fundamental question is that when AI becomes the new intermediary, the old incentive structures are no longer applicable.

Under the current structure, AI platforms gain immense value from the open source ecosystem but do not need to pay a corresponding cost to maintain that ecosystem. Users pay AI, AI provides convenience, but the open source projects and maintainers being called upon often receive nothing in return.

The authors of the paper propose a vision:

Reconstruct the profit distribution model.

Just as streaming platforms like Spotify share revenue with musicians based on play counts, AI platforms could track which open source projects they called upon and proportionally return a portion of the income to the maintainers.

In addition to platform revenue sharing, funding through foundations, corporate sponsorships, and government support for digital infrastructure are also crucial means to compensate for the loss of income for maintainers.

This requires a shift in industry perception, from viewing open source software as “free resources” to recognizing 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.

However, the era of open source that relied on scattered attention, reputation accumulation, and idealism may have reached its limits.

Vibe Coding brings not only a faster development experience but also a pressure test regarding how “public technology can be sustainably supported.”