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| Main Authors: | , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.00202 |
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| _version_ | 1866909658005897216 |
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| author | Kam, Matthew Miller, Cody Wang, Miaoxin Tidwell, Abey Lee, Irene A. Malyn-Smith, Joyce Perez, Beatriz Tiwari, Vikram Kenitzer, Joshua Macvean, Andrew Barrar, Erin |
| author_facet | Kam, Matthew Miller, Cody Wang, Miaoxin Tidwell, Abey Lee, Irene A. Malyn-Smith, Joyce Perez, Beatriz Tiwari, Vikram Kenitzer, Joshua Macvean, Andrew Barrar, Erin |
| contents | Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & knowledge to be a successful AI-enhanced developer are organized into four domains (using Generative AI effectively, core software engineering, adjacent engineering, and adjacent non-engineering) deployed at critical junctures throughout a 6-step task workflow. In order to "future proof" developers for this age of AI, on-the-job learning initiatives and computer science degree programs will need to target both "soft" skills and the technical skills & knowledge in all four domains to reskill, upskill and safeguard against deskilling. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_00202 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | What do professional software developers need to know to succeed in an age of Artificial Intelligence? Kam, Matthew Miller, Cody Wang, Miaoxin Tidwell, Abey Lee, Irene A. Malyn-Smith, Joyce Perez, Beatriz Tiwari, Vikram Kenitzer, Joshua Macvean, Andrew Barrar, Erin Artificial Intelligence Generative AI is showing early evidence of productivity gains for software developers, but concerns persist regarding workforce disruption and deskilling. We describe our research with 21 developers at the cutting edge of using AI, summarizing 12 of their work goals we uncovered, together with 75 associated tasks and the skills & knowledge for each, illustrating how developers use AI at work. From all of these, we distilled our findings in the form of 5 insights. We found that the skills & knowledge to be a successful AI-enhanced developer are organized into four domains (using Generative AI effectively, core software engineering, adjacent engineering, and adjacent non-engineering) deployed at critical junctures throughout a 6-step task workflow. In order to "future proof" developers for this age of AI, on-the-job learning initiatives and computer science degree programs will need to target both "soft" skills and the technical skills & knowledge in all four domains to reskill, upskill and safeguard against deskilling. |
| title | What do professional software developers need to know to succeed in an age of Artificial Intelligence? |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2506.00202 |