Since early 2023, the discourse around generative AI tools like ChatGPT has been dominated by concerns over potential job displacement, yet recent declines in usage suggest a more complex landscape. Venture Capitalist Chamath Palihapitiya attributes this downturn to the inherent hype cycle of new technologies, a pattern familiar from past innovations like XML and Ruby on Rails. Despite a temporary dip in engagement, sparked perhaps by seasonal changes in student usage or a lack of compelling applications, the proliferation of new AI tools such as Google’s Bard and Claude.ai suggests a growing range of options rather than diminished interest. The broader narrative reflects a historical pattern where new technologies initially overpromise and underdeliver but eventually contribute to substantial productivity gains, as seen in the evolution of software engineering. The potential of generative AI is not in reducing the need for programmers but in expanding what can be achieved, although the exact impact remains uncertain. As the tech landscape continues to evolve, the emphasis is on embracing these tools for learning and exploration, positioning oneself to leverage their potential and lead in innovation, particularly in areas like software testing where practical applications are still emerging.