HomeResearch LibraryThe Landscape of Emerging AI Agent Frameworks
surveyChapter 1arXiv · 2024

The Landscape of Emerging AI Agent Frameworks

Shengran Hu (Oxford), Cong Lu (Oxford)

Abstract

We survey the rapidly evolving landscape of AI agent frameworks, analyzing their architectural choices, capabilities, and limitations. We identify key trends and open challenges in agent framework design.

Eigenvector Insight — Zone III / PASF-PADE AnalysisNot part of the original paper
Eigenvector Research — Marco van Hurne
How this paper contributes to solving the Zone III problem (PASF-PADE)

This survey provides the most current map of the agent framework landscape. For enterprise architects selecting a Zone III framework, this is the essential reference for understanding the trade-offs between different approaches.

Why AI is not sufficient for Zone III without this

Zone III refers to high-complexity, high-risk, long-running agentic workflows — the class of enterprise AI deployments where a single failure can cascade across hundreds of steps. Standard AI models, trained to predict the next token, are not inherently designed for durable, governed, multi-step execution. This paper addresses one or more of the structural gaps that make Zone III deployments unsafe without explicit architectural intervention.

Key Contributions

  • →Comprehensive agent framework survey
  • →Architectural taxonomy
  • →Capability comparison matrix

Topics

agent frameworkssurveyarchitectureframework comparison