AI Agent Frameworks

Agentic AI frameworks are transforming the development of intelligent systems by integrating Large Language Models (LLMs) with traditional programming languages to create autonomous agents capable of complex decision-making and task execution. These systems are built on foundational concepts such as skills, which are modular components enabling agents to perform specific actions or make decisions. Skill selection, a critical aspect of agentic AI, involves choosing the most appropriate skill for a given context through methods like generative and semantic skill selection. Additionally, orchestration, which coordinates multiple skills to accomplish complex tasks, plays a key role in ensuring agents can plan, execute, and adapt effectively to changing circumstances.

Multi-agent systems represent an advanced implementation of agentic AI, where multiple agents collaborate to achieve shared goals. These systems offer benefits like specialization, parallel processing, and robustness but also pose challenges in coordination and communication among agents. Another important aspect is user experience (UX) design, which ensures intuitive and reliable interactions between users and agents through modalities such as text, speech, or graphical interfaces. Effective UX design must address issues like context retention, transparency of agent capabilities, and building user trust.

Frameworks such as Microsoft’s Semantic Kernel, CrewAI, Dify, and n8n provide tools for developing agentic AI systems, ranging from low-code platforms to highly customizable solutions. As these systems evolve, developers must address ethical considerations such as bias, privacy, security, and societal impacts. By leveraging foundational concepts and addressing these challenges responsibly, agentic AI has the potential to augment human capabilities and solve complex problems across various domains.

Required Reading and Listening

Listen to the podcast:

(Click here for transcript)

Read the following:

  1. Summary Blog: Agentic AI Frameworks Overview

  2. Textbook: Michael Albada, Building Applications with AI Agents, Chapters 3, 4, 5, 7. 1st ed., Published by O’Reilly Media, Inc., ISBN-13 978-1098176495. This book is available in print and digital on O’Reilly Media. GSU Library Link

Additional suggested reading:

  1. Lekha Priya, Agentic RAG: The Next Frontier in Generative AI and Dynamic Intelligence

  2. Kerem Aydin, Which AI Agent framework should i use? (CrewAI, Langgraph, Majestic-one and pure code)

More resources can be found on the resource page Agentic AI Related Texts