Jack of All Trades, Master of All?

Generative AI has become central to my academic and professional practice, significantly enhancing productivity in research, writing, coding, design, and medical learning. I use it to support literature reviews, refine language, create visual and presentation materials, analyse information, and streamline coding tasks, enabling both efficiency and higher-quality outcomes. Early niche services were quickly outperformed as general models evolved to cover a broad range of specialised functions, allowing them to act as versatile assistants across domains. My use of these systems falls broadly into three categories: reinforcing existing knowledge, acquiring new information with critical evaluation, and producing direct outputs such as text, code, or designs. As an early adopter, I have experienced firsthand how these tools can dramatically accelerate workflows while also raising the standard of work to a level that would often be unattainable without them. Far from being merely generalists, modern generative AI systems demonstrate mastery across diverse tasks, embodying the notion of a “Jack of All Trades, Master of All.”