Pre-AI Baseline: Developer IDE Satisfaction and Tool Autonomy in 2022
This paper establishes a pre-AI baseline of developer IDE satisfaction and tool autonomy, crucial for future longitudinal research on the impact of AI on software development productivity and satisfaction.
This study analyzed satisfaction data from 1,155 software developers in July 2022, finding a high IDE satisfaction ecosystem (Mean = 8.14) dominated by Visual Studio Code (79% usage). It identified that autonomy in tool choice is the strongest predictor of IDE satisfaction (beta = 0.51) and that cloud IDE adoption was negligible (4.3%).
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.