The Perfection Paradox: From Architect to Curator in AI-Assisted API Design

TL;DR

This paper investigates the use of AI in API design, revealing that AI can produce highly usable specifications faster, but may lead experts to perceive AI-generated work as unnervingly perfect, highlighting a paradox in AI-assisted design.

Contribution

It introduces the 'Perfection Paradox' in AI-assisted API design and proposes shifting human roles from drafting to curating AI-generated patterns.

Findings

AI outperforms humans in usability metrics and reduces authoring time by 87%

Experts often mistake AI work for human, with 19% accuracy in identification

AI-generated designs are perceived as unsettlingly perfect, indicating a paradox

Abstract

Enterprise API design is often bottlenecked by the tension between rapid feature delivery and the rigorous maintenance of usability standards. We present an industrial case study evaluating an AI-assisted design workflow trained on API Improvement Proposals (AIPs). Through a controlled study with 16 industry experts, we compared AI-generated API specifications against human-authored ones. While quantitative results indicated AI superiority in 10 of 11 usability dimensions and an 87% reduction in authoring time, qualitative analysis revealed a paradox: experts frequently misidentified AI work as human (19% accuracy) yet described the designs as unsettlingly "perfect." We characterize this as a "Perfection Paradox" -- where hyper-consistency signals a lack of pragmatic human judgment. We discuss the implications of this perfection paradox, proposing a shift in the human designer's role from the "drafter" of specifications to the "curator" of AI-generated patterns.