Vibe Coding Kills Open Source

TL;DR

This paper analyzes how vibe coding, an AI-driven approach to software development using open-source software, impacts the OSS ecosystem, productivity, and maintainer engagement, highlighting potential welfare trade-offs.

Contribution

It introduces a model of vibe coding's effects on OSS, showing how it influences productivity, user engagement, and the need for new maintainer compensation methods.

Findings

Vibe coding increases productivity but reduces user engagement with OSS.

Greater vibe coding adoption can decrease OSS quality and availability.

Maintaining OSS sustainability requires changes in maintainer payment models.

Abstract

Generative AI is changing how software is produced and used. In vibe coding, an AI agent builds software by selecting and assembling open-source software (OSS), often without users directly reading documentation, reporting bugs, or otherwise engaging with maintainers. We study the equilibrium effects of vibe coding on the OSS ecosystem. We develop a model with endogenous entry and heterogeneous project quality in which OSS is a scalable input into producing more software. Users choose whether to use OSS directly or through vibe coding. Vibe coding raises productivity by lowering the cost of using and building on existing code, but it also weakens the user engagement through which many maintainers earn returns. When OSS is monetized only through direct user engagement, greater adoption of vibe coding lowers entry and sharing, reduces the availability and quality of OSS, and reduces welfare despite higher productivity. Sustaining OSS at its current scale under widespread vibe coding requires major changes in how maintainers are paid.