Vibe Coding's Hidden Cost: How AI Assembly Threatens Open Source Sustainability

The paper "Vibe Coding Kills Open Source" by Miklós Koren, Gábor Békés, Julian Hinz, and Aaron Lohmann presents a formal economic analysis of a phenomenon that's rapidly reshaping software development. The authors define "vibe coding" as a process where AI agents build software by automatically selecting and assembling open-source components, often without developers directly reading documentation, reporting bugs, or engaging with maintainers. This represents a fundamental shift from traditional open-source usage patterns.

The Economic Model

The researchers develop an equilibrium model that captures several key dynamics:

1. Endogenous Entry and Quality Heterogeneity

Open-source projects vary significantly in quality, and new projects enter the ecosystem based on expected returns. Maintainers invest time and effort with the understanding that user engagement—through bug reports, feature requests, documentation improvements, and sometimes direct financial support—provides compensation, either monetary or in-kind.

2. OSS as a Scalable Input

Unlike traditional inputs, open-source software has near-zero marginal cost of replication but requires upstream investment in maintenance. The model treats OSS as a production factor that enables creation of more software, but with a critical dependency: maintainers need signals of value to continue investing.

3. User Choice: Direct vs. AI-Mediated Consumption

Developers choose between:

• Direct usage: Reading docs, understanding APIs, contributing back through engagement
• Vibe coding: AI handles selection and integration, developer stays at a higher abstraction level

The Core Mechanism

The paper identifies a positive feedback loop with negative consequences:

Productivity Gains: Vibe coding lowers the cost of using existing code. Developers can build more, faster, by letting AI handle the complexity of component selection and integration.

Engagement Erosion: When AI intermediates the relationship between users and maintainers, the natural feedback loops break down:

• Bug reports don't reach maintainers (AI workarounds instead)
• Documentation gaps aren't identified (AI infers intent)
• Feature requests bypass maintainers (AI implements alternatives)
• Financial support decreases (users feel no direct relationship)

Ecosystem Degradation: With weakened engagement signals and reduced direct compensation, fewer new projects enter the ecosystem. Existing maintainers reduce investment or exit. The overall quality and availability of OSS declines.

The Welfare Paradox

Here's the critical insight: despite higher productivity in software production, overall welfare can decrease. The model shows that the productivity gains from vibe coding are outweighed by:

1. Reduced OSS availability in the long run
2. Lower quality of remaining projects
3. Loss of spillover benefits from engaged communities (innovation, security fixes, ecosystem knowledge)

The paper quantifies this trade-off: when OSS monetization depends entirely on direct user engagement, widespread vibe coding adoption leads to suboptimal entry and sharing, reducing total welfare.

Why This Matters

This research challenges the optimistic view that AI tooling will simply accelerate software development without negative externalities. The authors argue that the current OSS sustainability model—reliant on volunteer labor supplemented by indirect compensation—cannot survive widespread vibe coding adoption.

The paper suggests that sustaining OSS at its current scale requires "major changes in how maintainers are paid." This could include:

• Direct AI tooling fees that flow back to OSS projects
• New compensation mechanisms that don't depend on user engagement
• Platform-level interventions that maintain feedback loops

Broader Implications

The vibe coding phenomenon extends beyond individual developer productivity. It represents a structural change in how software value is created and captured. If AI intermediaries become the primary interface to OSS, the traditional social contract of open source—"I share my work, you engage with me"—breaks down.

This creates a classic tragedy of the commons scenario: individual developers benefit from using AI to assemble software efficiently, but the collective action of widespread adoption degrades the shared resource (OSS ecosystem) that makes the efficiency possible.

The paper's economic modeling provides a framework for understanding why this isn't just a cultural shift but a fundamental threat to the production model that underpins modern software development.

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Paper Details

• Title: Vibe Coding Kills Open Source
• Authors: Miklós Koren, Gábor Békés, Julian Hinz, Aaron Lohmann
• arXiv: 2601.15494
• Category: General Economics (econ.GN)
• Submitted: January 21, 2026