Paper
Pre-AI Baseline: Developer IDE Satisfaction and Tool Autonomy in 2022
Authors
Nikola Balić
Abstract
To quantify the impact of AI on software development, the community requires a robust pre-AI baseline. This study analyzes valid satisfaction data from 1,155 software developers collected in July 2022, immediately preceding the mainstream adoption of generative AI tools. We report a high-satisfaction ecosystem (Mean = 8.14 [95% CI 8.01-8.25]), dominated by Visual Studio Code (79% usage). Multivariable regression confirms that autonomy in tool choice is the strongest predictor of IDE satisfaction (beta = 0.51), significantly outweighing demographic or role-based factors. Conversely, cloud IDE adoption was negligible (4.3% regular usage), with 40.1% citing network dependency as the primary barrier, a constraint that remains relevant for modern cloud-reliant AI agents. Additionally, we identify an "experimenter" segment (29.9%) characterized by high tool churn but no significant satisfaction difference (t = 0.43, p = 0.67), and demonstrate significant variation in IDE retention rates (VS Code: 68.5%, traditional IDEs: 3.9-25%), suggesting underlying dissatisfaction despite high overall satisfaction. By providing a quantitative snapshot of developer sentiment and workflows on the eve of the AI revolution, this study establishes a verifiable baseline for longitudinal research into the productivity-satisfaction misalignment observed in the post-AI era.
Metadata
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Raw Data (Debug)
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"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2603.06050v1</id>\n <title>Pre-AI Baseline: Developer IDE Satisfaction and Tool Autonomy in 2022</title>\n <updated>2026-03-06T09:01:53Z</updated>\n <link href='https://arxiv.org/abs/2603.06050v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2603.06050v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>To quantify the impact of AI on software development, the community requires a robust pre-AI baseline. This study analyzes valid satisfaction data from 1,155 software developers collected in July 2022, immediately preceding the mainstream adoption of generative AI tools. We report a high-satisfaction ecosystem (Mean = 8.14 [95% CI 8.01-8.25]), dominated by Visual Studio Code (79% usage). Multivariable regression confirms that autonomy in tool choice is the strongest predictor of IDE satisfaction (beta = 0.51), significantly outweighing demographic or role-based factors. Conversely, cloud IDE adoption was negligible (4.3% regular usage), with 40.1% citing network dependency as the primary barrier, a constraint that remains relevant for modern cloud-reliant AI agents. Additionally, we identify an \"experimenter\" segment (29.9%) characterized by high tool churn but no significant satisfaction difference (t = 0.43, p = 0.67), and demonstrate significant variation in IDE retention rates (VS Code: 68.5%, traditional IDEs: 3.9-25%), suggesting underlying dissatisfaction despite high overall satisfaction. By providing a quantitative snapshot of developer sentiment and workflows on the eve of the AI revolution, this study establishes a verifiable baseline for longitudinal research into the productivity-satisfaction misalignment observed in the post-AI era.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='cs.SE'/>\n <published>2026-03-06T09:01:53Z</published>\n <arxiv:comment>21 pages, 5 figures. Preprint version submitted to PeerJ Computer Science; supplementary material included in the source bundle</arxiv:comment>\n <arxiv:primary_category term='cs.SE'/>\n <author>\n <name>Nikola Balić</name>\n </author>\n </entry>"
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