When Code Becomes Abundant: Redefining Software Engineering Around Orchestration and Verification

2026-02-04

AI Summary

This work addresses the dual challenges posed by AI-driven reductions in coding costs and escalating hardware energy constraints that amplify the consequences of software failures, rendering traditional code-centric software engineering paradigms unsustainable. It proposes a paradigm shift toward emphasizing intent expression, architectural control, and systematic verification, underscoring the indispensable role of human judgment in automated development environments. The study systematically identifies, for the first time, the emerging risk of “accountability collapse” and advocates for a new human-judgment-centered paradigm that integrates software architecture design, formal verification, and human-AI collaboration mechanisms to restructure AI-assisted development workflows. This approach opens a novel direction for research, education, and industrial practice in software engineering—one that is intent-driven, verifiable, and highly reliable.

Technology Category

• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Application Domains: Software Engineering
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Economics, Online Markets and Human Computation: Research challenges in human and human-AI computation
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Software Engineering (SE) faces simultaneous pressure from AI automation (reducing code production costs) and hardware-energy constraints (amplifying failure costs). We position that SE must redefine itself around human discernment-intent articulation, architectural control, and verification-rather than code construction. This shift introduces accountability collapse as a central risk and requires fundamental changes to research priorities, educational curricula, and industrial practices. We argue that Software Engineering, as traditionally defined around code construction and process management, is no longer sufficient. Instead, the discipline must be redefined around intent articulation, architectural control, and systematic verification. This redefinition shifts Software Engineering from a production-oriented field to one centered on human judgment under automation, with profound implications for research, practice, and education.

Problem

• Software Engineering
• AI automation
• accountability collapse
• verification
• architectural control

Innovation

• intent articulation
• architectural control
• systematic verification
• accountability collapse
• software engineering redefinition