The recent launch of OpenAI's GPT-5, hailed as a significant leap in artificial intelligence, has been met with mixed user reactions, particularly concerning its underlying "router" system. While the model demonstrates advanced capabilities, some users report a new form of frustration, feeling intellectually diminished by the AI's effortless problem-solving. This sentiment was encapsulated in a viral social media post by user 'wh', stating, "I think the main UX problem with the GPT5 router is that it makes me feel stupid."
OpenAI positioned GPT-5 as its most capable AI system to date, offering "PhD-level" expertise across coding, mathematics, writing, and visual perception. The model is designed as a unified system that intelligently routes queries to different internal models—such as gpt-5-main
for quick answers and gpt-5-thinking
for deeper reasoning—based on the complexity and intent of the user's prompt. This dynamic routing aims to optimize for both speed and comprehensive responses.
However, this sophisticated routing mechanism has become a focal point of user discussion and, at times, "backlash." The system's ability to seamlessly determine the optimal processing path and deliver expert-level solutions can inadvertently create a user experience where the AI's efficiency highlights the user's own prior struggles. As 'wh' further elaborated in their tweet, "> What do you mean my carefully crafted, super detailed question that I had spent several hours trying to answer on my own needed no thinking to answer?"
This feedback underscores a growing psychological challenge in human-AI interaction: the potential for advanced AI to induce feelings of inadequacy or redundancy. While intended to assist, the AI's superior performance in tasks requiring significant human effort can lead users to question their own intellectual contributions. The debate highlights the delicate balance between AI utility and its impact on user self-perception.
Industry observers note that while OpenAI aims to simplify user interaction by automating model selection, this approach may require further refinement to address the nuanced psychological aspects of human collaboration with highly intelligent systems. The ongoing evolution of AI necessitates not only technical advancement but also a deeper understanding of its broader societal and individual psychological implications.