English

Beyond the 'Diff': Addressing Agentic Entropy in Agentic Software Development

Software Engineering 2026-05-05 v2 Artificial Intelligence

Abstract

As autonomous coding agents become deeply embedded in software development workflows, their high operational velocity introduces a critical oversight challenge: the accumulating divergence between agentic actions and architectural intent. We term this process agentic entropy: a systemic drift that traditional code diff-based and HCXAI methods fail to capture, as they address local outputs rather than global agentic behaviour. To close this gap, we propose a process-oriented explainability framework that exposes how agentic decisions unfold across time, tool calls, and architectural boundaries. Built around three pillars (conformity seeding, reasoning monitoring, and a causal graph interface) our approach provides intent-level telemetry that complements, rather than replaces, existing review practices. We demonstrate its relevance across two user profiles: lay users engaged in vibe coding, who gain structural visibility otherwise masked by functional success; and professional developers, who gain richer contextual grounding for code review without increased overhead. By treating cognitive drift as a first-class concern alongside code quality, our framework supports the minimum level of human comprehension required for agentic oversight to remain substantive.

Keywords

Cite

@article{arxiv.2604.16323,
  title  = {Beyond the 'Diff': Addressing Agentic Entropy in Agentic Software Development},
  author = {Matteo Casserini and Alessandro Facchini and Andrea Ferrario},
  journal= {arXiv preprint arXiv:2604.16323},
  year   = {2026}
}

Comments

Camera-ready version of the position paper accepted to the Human-Centered Explainable AI (HCXAI) Workshop at CHI 2026

R2 v1 2026-07-01T12:14:49.224Z