Part 5/12:
For instance, GPT-5 quickly and accurately generated tailored Twitter content, analyzed tone and style, and even researched psychological triggers from MIT sources to craft compelling ad scripts—all within seconds. When it worked properly, the model’s routing system showed promise, automatically selecting the most appropriate model for each task without user intervention. This automation simplifies the user experience, reducing the need to manually pick different AI tools.
However, this success was marred by foundational issues. Basic math errors persisted, and complex coding tasks still favored specialized models like Claude in performance. Speed was unpredictable—sometimes blazing fast, other times sluggish—and these inconsistencies hampered real-world usability.