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

TL;DR

This paper introduces a process-oriented explainability framework to monitor and understand agentic decisions in autonomous coding agents, addressing the systemic drift called agentic entropy that traditional methods overlook.

Contribution

It proposes a novel framework with three pillars that exposes agentic decision processes over time, tool calls, and architectural boundaries, enhancing oversight in software development.

Findings

Framework provides intent-level telemetry for agentic decisions.

Improves structural visibility for lay users engaged in vibe coding.

Offers richer contextual grounding for professional developers without extra overhead.

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.