An Agent is a system designed to execute specific tasks with some degree of autonomy. Unlike LLMs, which primarily respond to specific instructions, Agents are designed to perceive their environment, process information, make autonomous decisions and take proactive actions to achieve specific goals. In addition, they are able to dynamically adapt to unforeseen changes or challenges, continuously learning from their experiences.
The autonomy of Agents is based on three fundamental characteristics:
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Proactive Planning and Execution: Agents do not simply react to isolated instructions. They set clear objectives and plan how to achieve them, breaking down complex tasks into manageable steps, anticipating obstacles and adjusting their approach in real time.
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Advanced Reasoning and Continuous Learning: They use sophisticated Reasoning Strategies, such as Chain of Thought, to analyze situations, infer conclusions and decide on the most effective actions. They incorporate different types of memory (declarative, procedural and working) that allow them to learn from previous experiences, generalize knowledge, and continuously improve their performance.
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Integration with Tools and Data Sources: Agents integrate effectively with external Tools, APIs and various data sources, enabling them to access and process information from multiple systems and environments, thus extending their range of practical application.
Recognizing the transformative potential of Agents, Globant Enterprise AI introduces The Lab, an environment that simplifies their design, configuration, and management.
To define or update an Agent, you can use the Agents API or work directly in The Lab. If you choose The Lab, follow the steps described in How to create an Agent.
Since veraion 2025-04.