Vibecoding and Digital Entrepreneurship

TL;DR

This paper investigates how GenAI-enabled coding automation, called vibecoding, influences digital entrepreneurial entry and performance, highlighting its role in complementing technical expertise rather than replacing it.

Contribution

It provides empirical evidence that vibecoding increases venture entry and performance mainly when it enhances existing engineering capabilities, especially among STEM-educated founders.

Findings

Vibecoding increases first-time venture launches and shortens time to launch.

Economic viability of ventures rises only when vibecoding complements, not fully automates, product development.

Performance gains are concentrated among ventures with engineering-intensive teams and STEM backgrounds.

Abstract

As generative artificial intelligence (GenAI) automates coding tasks and expands access to technical resources, this paper examines how GenAI-enabled coding automation, colloquially known as "vibecoding," affects digital entrepreneurial entry and venture performance. We exploit ex-ante variation in ventures' exposure to vibecoding based on the product characteristics of their initial launches and estimate difference-in-differences models around the diffusion of GenAI coding tools. Vibecoding increases first-time launches and shortens time to launch, but economically viable entry rises only where vibecoding augments, rather than fully automates, product development. In these partially exposed product segments, viable entry increases by 11%, driven entirely by ventures founded by individuals with STEM education or work experience, especially those whose most recent employment was outside middle management. Among ventures launched before GenAI became widely accessible, performance gains similarly concentrate among partially exposed ventures with engineering-intensive initial teams. Together, these results suggest that GenAI-enabled coding automation does not eliminate the value of technical expertise. Instead, vibecoding creates the greatest value when it complements internal engineering capabilities, allowing ventures to delegate lower-level coding tasks to GenAI while shifting human effort toward higher-level problem solving and dynamic adaptation.