Building Effective Large Language Model Agents

Authors

Sydney Holder, Southern Methodist UniversityFollow
Shreyash Taywade, AT&TFollow

Abstract

The advancement of large language models (LLMs) has significantly expanded the influence of artificial intelligence across various sectors. This paper explores building LLM agents to power applications and examines what is necessary to build an efficient and helpful AI assistant. The research investigates the core components necessary to create specialized agents, facilitate collaboration in problem-solving, and improve human task performance. The development and application of tools designed to augment the capabilities of LLM agents are also explored. The paper addresses the potential risks of the unknowns, such as hallucinations, which can compromise the success of agent-based solutions within LLM applications. The potential application areas for LLM agents and the broader implications of these findings on AI research and application development are discussed.

Recommended Citation

Holder, Sydney and Taywade, Shreyash (2024) "Building Effective Large Language Model Agents," SMU Data Science Review: Vol. 8: No. 1, Article 6.
Available at: https://scholar.smu.edu/datasciencereview/vol8/iss1/6

Creative Commons License

This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License