The world of Artificial Intelligence continues to evolve, as revealed in the enlightening course ‘Learn to build effective Agentic AI systems with Andrew Ng,’ published on October 7, 2025, by DeepLearning.AI. Andrew Ng introduces ‘Agentic AI,’ a fresh paradigm emphasizing systems that perform multi-step, autonomous workflows. This signifies a pivotal shift from traditional AI systems, which often respond only to direct prompts, suggesting a more dynamic future for AI interactions. Spotlights shine on the crafting of agentic workflows using essential Python techniques without reliance on frameworks, empowering learners to understand each component intimately. Ng deftly bridges theoretical insights with practical applications, offering a structured approach to building AI systems that reflect, plan, and utilize tools effectively. The promise of becoming proficient in such systems, marked as an in-demand skill, hints at new vistas for innovation. However, one must consider the critique around the term ‘Agentic AI’ risking becoming another buzzword, which might dilute its conceptual depth. This concern is offset by the course’s focus on rigorous error analysis and system evaluation, equipping participants with advanced analytical methods. Although the course leans heavily on theoretical teachings, Andrew Ng’s dedication to practical, mindful application ensures participants can integrate these learnings into any desired framework. This is an exciting development in AI education, showcasing both the potential splendor and the practical challenges of embracing Agentic AI in modern tech landscapes.