  This article explores the dynamic influence of computational entities based
on multi-agent systems theory (SMA) combined with large language models (LLM),
which are characterized by their ability to simulate complex human
interactions, as a possibility to revolutionize human user interaction from the
use of specialized artificial agents to support everything from operational
organizational processes to strategic decision making based on applied
knowledge and human orchestration. Previous investigations reveal that there
are limitations, particularly in the autonomous approach of artificial agents,
especially when dealing with new challenges and pragmatic tasks such as
inducing logical reasoning and problem solving. It is also considered that
traditional techniques, such as the stimulation of chains of thoughts, require
explicit human guidance. In our approach we employ agents developed from large
language models (LLM), each with distinct prototyping that considers behavioral
elements, driven by strategies that stimulate the generation of knowledge based
on the use case proposed in the scenario (role-play) business, using a
discussion approach between agents (guided conversation). We demonstrate the
potential of developing agents useful for organizational strategies, based on
multi-agent system theories (SMA) and innovative uses based on large language
models (LLM based), offering a differentiated and adaptable experiment to
different applications, complexities, domains, and capabilities from LLM.
