# What We Can Learn From Visual Artists About Software Development

arXiv: https://arxiv.org/abs/2101.11218 · HTML: https://mlsanity.com/paper/2101.11218/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jan 2021.

## Built on by (most cited first, 4 of 4)

- [Spellburst: A Node-based Interface for Exploratory Creative Coding with Natural Language Prompts](https://mlsanity.com/paper/2308.03921/) (2023)
- [POET: Supporting Prompting Creativity and Personalization with Automated Expansion of Text-to-Image Generation](https://mlsanity.com/paper/2504.13392/) (2025)
- [Is AI Art Another Industrial Revolution in the Making?](https://mlsanity.com/paper/2301.05133/) (2023)
- [Computational Scaffolding of Composition, Value, and Color for Disciplined Drawing](https://mlsanity.com/paper/2509.17268/) (2025)

## Abstract (arXiv)

This paper explores software's role in visual art production by examining how artists use and develop software. We conducted interviews with professional artists who were collaborating with software developers, learning software development, and building and maintaining software. We found artists were motivated to learn software development for intellectual growth and access to technical communities. Artists valued efficient workflows through skilled manual execution and personal software development, but avoided high-level forms of software automation. Artists identified conflicts between their priorities and those of professional developers and computational art communities, which influenced how they used computational aesthetics in their work. These findings contribute to efforts in systems engineering research to integrate end-user programming and creativity support across software and physical media, suggesting opportunities for artists as collaborators. Artists' experiences writing software can guide technical implementations of domain-specific representations, and their experiences in interdisciplinary production can aid inclusive community building around computational tools.