In 2024, AI agents gained significant attention on social media and industry platforms, with companies like Anthropic and OpenAI making strides in developing agents that mimic human interactions by accessing computers via keyboard and mouse. Despite the hype, the practical implementation of AI agents remains limited, as these systems face numerous challenges, such as reliability, cost, transparency, and complexity. The gap between the potential of AI agents and their current capabilities is highlighted by the lack of genuine agency in commercial products and the hurdles in deploying them in production environments. The development of Compound AI Systems, which integrate language models into larger frameworks like Retrieval-Augmented Generation (RAG), exemplifies the ongoing evolution in this field. While existing AI agents operate more as tool-based systems or routers rather than autonomous entities, advancements such as the ReAct framework are paving the way for future iterations that promise to be more capable and impactful.