Common Use Cases and Applications
Building upon our previous examination of risks and challenges in LLM-based agent systems, from adversarial attacks to ethical concerns, we now turn our attention to their practical applications. This chapter explores how agentic systems are transforming various domains by combining LLMs with goal-directed behavior and autonomous decision-making capabilities. We’ll see how these agents can understand context, formulate plans, and take action to achieve specific objectives while maintaining meaningful interactions with humans.
As we explore these applications, we will focus on how agents leverage LLMs not just as language processors but also as core reasoning engines that enable sophisticated planning and execution across different domains. This represents a fundamental shift from traditional AI systems, as these agents can now adapt their behavior, learn from interactions, and operate with increasing levels of autonomy while maintaining alignment...
