I started in technology at the age of 13. At an early age, I won a scholarship to study in Japan where I obtained my degree in Electronic Engineering and a Specialization in Robotics.

Years later, I achieved a master’s in software technologies in Spain and a Specialization in Digital Marketing in Canada, which I complemented with studies in Automation in Brazil.

I integrated into my training internships at NTT, Mazda, Kyocera, and Toshiba companies.

I managed Banking and Telecommunications Projects for 10 years, leading multidisciplinary and multicultural IT teams.

My teaching work allowed me to train professionals for more than 15 years, and as an International Consultant, I have collaborated with important companies in Mexico, Colombia, Ecuador, Costa Rica, El Salvador, and Peru. I currently contribute technology articles to the meer magazine, which is published in 3 languages.

I am an International Speaker and proud founder of the Technology Company FuturaSoft.

Four years ago, I accepted the fascinating challenge of teaching a Big Data course. The thematic proposal was intimidating, as it presented an approach devoid of "ready-to-use" tools and, instead, proposed a highly technical approach (Kumar et al., 2022).

This required meticulous and mechanical practice that consisted of mastering the Linux operating system, configuring virtual machines, and installing more than half a dozen tools through command line, as well as configuring an endless list of system files (.sh, .ini, etc.). These specialized practices demand considerable time and expertise from the instructor (Wang & Chen, 2023).

Back then, AI assistants like ChatGPT or Claude didn't exist. Class preparation without these tools became an arduous and often torturous process of achieving the ideal pedagogical strategy. Here, aspects such as class script, narrative resources, demonstrative arguments, effective design of examples, and the development of questionnaires, glossaries, case studies, group dynamics, among others, became relevant.

I soon discovered that I needed four hours of preparation for each hour of class taught. The sessions would last four hours, so I had to sit down to workdays in advance. Much of this time was spent installing, configuring, and deploying the tools that would be the subject of study. However, given the technical complexity, problems and unforeseen issues constantly arose that seemed endless, feeding an upward spiral of frustration and stress.

In those moments, I would immerse myself in a frantic Google search, trying to find answers to questions that seemed to have no solution. After hours of navigating countless pages and hundreds of desperate and furious clicks against the mouse, I would reach some page where another user, probably as desperate as I was, described the same problem; to which a generous soul would provide a solution, thus ending the mystery. This became a habitual routine in my teaching work.

Class preparation in that "pre-AI era" demanded considerable effort, time, and resources. Fortunately, the arrival of AI has radically transformed the academic scenario (Zawacki-Richter et al., 2019). Questions no longer have to be resolved with a tenacious and urgent search in internet browsers. Today we can tell AI what ails us and in a matter of seconds we will have a proposed solution based on vast knowledge that unfolds amid solid arguments explained didactically and illustrated with examples that elevate

comprehension and understanding to levels only matched by long hours of traditional research and study. These responses transcend mere resolution of the problem posed, additionally opening a range of pedagogical possibilities (Mollick & Mollick, 2023); ranging from deep analysis of case studies to the implementation of functional prototypes that transform abstract concepts into tangible experiences for students.

While AI assistants have made our pedagogical work more effective and efficient, AI has gone even further in optimizing teaching. An outstanding example is Gamma, a platform that has revolutionized presentation creation. This innovative tool frees us from the tedious task of designing slides from scratch, automatically generating presentations with captivating designs. Gamma not only produces high-quality images, whether created by AI or selected from a vast library but also generates personalized content according to the instructor's specifications. After an exhaustive analysis of the materials produced by this tool, I can affirm that the precision and quality of the generated content are truly impressive, significantly elevating the standard of our educational resources and transforming our way of preparing material for the classroom.

Another notable tool is Napkin, which creates diagrams and infographics from text. Gone are the days when we had to resort to Microsoft Word's SmartArt functionality to generate diagrams. Napkin detects and extracts key points from the content and transforms them into high-quality, professional-style visual resources. All this without the need to curate or modify the content.

I cannot fail to mention Notebooklm, a platform that I consider one of the most surprising innovations of recent years. This tool not only summarizes content from various sources (PDF, URL, YouTube) into structured chapters, but also generates quizzes, glossaries, essays, timelines, indexes, study guides, frequently asked questions, and even podcasts, all with a single click. The quality and veracity of the content it produces are exceptional, taking the automation of teaching work to an unprecedented level.

The integration of AI in the educational process has marked a before and after (Anderson & Smith, 2024). What was once a rough road has become a fast track to pedagogical efficiency and excellence. This revolution has not only lightened the workload but has expanded the possibilities of creating richer and more personalized learning experiences.

However, it is crucial to remember that AI is a powerful tool, but not a substitute for the educator (Holmes and Richardson, 2024). Our role as teachers evolves towards that of curators and facilitators, leveraging these technologies to enhance our ability to inspire and guide students on their learning journey (Zhang et al., 2023).

The AI era in education has begun, opening a world of possibilities for redefining how we teach and learn. The future of education is exciting, and we are barely at the threshold of its transformative potential.

References:

• Kumar, S., Patel, R., & Johnson, M. (2022). Teaching big data: Challenges and opportunities. Computer Science Education, 32(1), 45-63.
• Wang, Y., & Chen, X. (2023). Technical challenges in modern computer science education. Journal of Computing in Higher Education, 35(2), 289-310.
• Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 16(1), 1-41.
• Mollick, E., & Mollick, L. (2023). ChatGPT and the future of education. Harvard Business Review Digital Articles, 1-8.
• Anderson, K., & Smith, J. (2024). AI-powered educational tools: A comprehensive review. Journal of Educational Technology, 45(2), 78-92.
• Holmes, W., & Richardson, M. (2024). The evolving role of educators in the AI era. Educational Research Review, 31, 100411.
• Zhang, L., Liu, D., & Brown, A. (2023). AI as educational facilitator: Transforming teaching practices. Teaching in Higher Education, 28(4), 412-428.