Measuring AI-Readiness: A Three-Axis Maturity Model for Agent-Optimized Codebases
Lingua:
Inglese
Track "AI Technologies"
Orario: 10:45
- 11:30
Abstract
As AI coding agents become integral to software development workflows, a critical question emerges: why do these agents excel in some repositories while struggling in others? The answer lies not in the agents themselves, but in the codebases they navigate.
We introduce AI-Readiness: a measurable property of repositories that determines how efficiently AI agents can understand, navigate, and modify code. Unlike traditional code quality metrics designed for human comprehension, AI-readiness specifically addresses the unique constraints of LLM-based agents: context window, tokens, and the absence of human intuition.
