№2, 2025
PROSPECTS OF ARTIFICIAL SOFTWARE ENGINEERING
The merging of AI and software engineering marks a defining moment: intelligent systems now move beyond simple code completion or test automation to become active partners in each phase of development. We term this “Artificial Software Engineering,” a collaborative framework where human ingenuity and machine intelligence co–author software—from early prototypes and code generation to debugging and architectural design (Menzies et al., 2019). By looking at platforms like Devin AI and GitHub Copilot, we see clear benefits—faster iterations, deeper error detection—but also face new challenges around trust, ownership, legal responsibility, and maintaining AI‐influenced code over time. Rather than treating automation as an end goal, we argue that this emerging discipline demands fresh thinking about ethics, team dynamics, and design practices. Ultimately, the most successful software will blend human insight with algorithmic strength to drive responsible innovation (pp.69-74).
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