Good Vibrations? A Qualitative Study of Co-Creation, Communication, Flow, and Trust in Vibe Coding (2509.12491v1)

Abstract: Vibe coding, a term coined by Andrej Karpathy in February 2025, has quickly become a compelling and controversial natural language programming paradigm in AI-assisted software development. Centered on iterative co-design with an AI assistant, vibe coding emphasizes flow and experimentation over strict upfront specification. While initial studies have begun to explore this paradigm, most focus on analyzing code artifacts or proposing theories with limited empirical backing. There remains a need for a grounded understanding of vibe coding as it is perceived and experienced by developers. We present the first systematic qualitative investigation of vibe coding perceptions and practice. Drawing on over 190,000 words from semi-structured interviews, Reddit threads, and LinkedIn posts, we characterize what vibe coding is, why and how developers use it, where it breaks down, and which emerging practices aim to support it. We propose a qualitatively grounded theory of vibe coding centered on conversational interaction with AI, co-creation, and developer flow and joy. We find that AI trust regulates movement along a continuum from delegation to co-creation and supports the developer experience by sustaining flow. We surface recurring pain points and risks in areas including specification, reliability, debugging, latency, code review burden, and collaboration. We also present best practices that have been discovered and shared to mitigate these challenges. We conclude with implications for the future of AI dev tools and directions for researchers investigating vibe coding.

• The paper's main contribution is a qualitative exploration of vibe coding's benefits and challenges, highlighting co-creation, flow, and trust in AI-assisted development.
• It uses extensive qualitative data from interviews, social media discussions, and professional posts to triangulate developer experiences with AI interactions.
• The study suggests best practices such as context management and proactive testing to mitigate risks like debugging issues and technical debt.

Qualitative Study of Vibe Coding: Co-Creation, Communication, Flow, and Trust

Introduction to Vibe Coding

Vibe coding, a programming paradigm introduced by Andrej Karpathy in 2025, emphasizes an AI-assisted software development process centered around iterative co-design, flow, and experimentation. This approach relies on conversational interaction with AI, promoting co-creation and developer engagement over traditional methods of upfront specification and code artifact analysis. Despite its increasing popularity, there's a need for empirical research to understand developers' perceptions and experiences with vibe coding.

Methodological Approach

This paper presents a systematic qualitative investigation based on over 190,000 words of collected data from various sources, including interviews, discussions on social media platforms like Reddit, and professional posts on LinkedIn. The paper aims to ground the concept of vibe coding in real-world developer experiences and concerns.

The research combines flexible qualitative methodologies, triangulating insights from different data sources to reduce bias and validate findings. The primary research questions focus on defining what vibe coding is, understanding how and why developers engage with it, identifying its challenges, and exploring emerging best practices.

Framework for Understanding Vibe Coding

Figure 1: Overview of the conceptual framework for vibe coding, highlighting interaction, co-creation, flow, and trust.

Conversational Interaction and Co-Creation

Vibe coding leverages natural language interfaces for software development, enabling programmers to specify tasks and goals through conversational dialogues with AI. This approach minimizes traditional code writing and reading, aiming for a seamless co-creation process with AI participation in critical decision-making. The paradigm is supported by the notion of AI functioning as a creative partner, enhancing brainstorming and learning through dynamic interaction.

Developer Flow and Joy

A significant attribute of vibe coding is fostering a flow state—an intrinsic sense of capacity and engagement while coding. Developers report experiencing heightened productivity and creativity, attributing these to AI's assistance in managing low-level coding concerns. The research indicates that flow and joy are paramount in this paradigm, driven by the sense of continuous progress and feedback loops intrinsic to this style of development.

Pain Points in Vibe Coding

Despite its potential, vibe coding presents several challenges. Developers encounter issues such as specifying intent accurately, managing AI's conversational memory, and the risk of unreliable, low-quality code output. Additionally, co-creation experiences can be disrupted by debugging burdens or challenges in maintaining the AI's solution quality.

Figure 2: Pain points and challenges identified in vibe coding, including issues with conversational memory and task delegation.

Trust and Risk in Vibe Coding

Trust in AI emerges as a key mediating factor in the vibe coding experience. Developers' willingness to delegate decision-making to AI can lead to increased flow but also elevates risks such as introducing technical debt or security vulnerabilities. This trust must be carefully managed to ensure that the benefits of vibe coding are not undermined by the potential pitfalls of unchecked AI reliance.

Emerging Best Practices

The paper identifies best practices that are evolving to mitigate these challenges. Techniques such as context management, proactive version control, and integrating robust testing frameworks are recommended to enhance reliability and maintain flow. Best practices also emphasize maintaining a balance between task complexity and clarity of communication to the AI.

Conclusion

This investigation reveals that vibe coding represents a shift towards an experience-driven software development approach, balancing traditional coding foundations with creative AI interaction. As a burgeoning paradigm, it poses unique opportunities and challenges for developers aiming to harness its potential, underscoring the need for ongoing research and tool evolution to support this dynamically co-creative environment. Future work should continue to explore the nuanced balance between automation and human oversight inherent in vibe coding, ensuring its sustainable integration into broader software engineering practices.