Grey Literature Review Proposes Unified Definition and Engineering Blueprint for AI-Native Applications
A recent grey literature review synthesizes 106 sources to define AI-native applications, highlighting two core pillars: the central role of AI as the system's intelligence paradigm and their inherently probabilistic, non-deterministic nature. The review identifies key quality attributes—reliability, usability, performance efficiency, and AI-specific observability—and describes an emerging technology stack including LLM orchestration frameworks, vector databases, and AI-native observability platforms. This work offers a structured synthesis of current conceptual and practical perspectives on AI-native software engineering.
Why it matters: This review provides the first comprehensive engineering definition and architectural blueprint for AI-native applications, addressing a gap in systematic guidance for practitioners.
Full story at: arXiv Software Engineering ↗