The article explores the disconnect between advancements in AI and their impact on the job market, particularly for entry-level positions. A Stanford analysis from summer 2025 highlights a 6% decline in employment for workers aged 22–25 in AI-exposed fields, while older workers saw a 6–9% increase. The timing aligns with the launch of ChatGPT in late 2022, which marked a significant shift in AI capabilities. Despite impressive benchmarks—like Claude Opus 4.5 completing about 75% of real-world coding tasks—these gains have not translated into broader economic benefits. Many generative AI pilots fail to deliver sustained value, and real-world tests show that even leading AI systems succeed only about 2.5% of the time. The author reflects on personal experiences with hiring, emphasizing that successful candidates often possess not just technical skills, but also judgment and agency. While execution can be easily measured through benchmarks, assessing qualities like common sense and the ability to navigate ambiguity remains challenging. This distinction helps explain why entry-level jobs are most affected by AI advancements, as these roles typically focus on execution. As AI improves in this area, it threatens to erode the foundation that allows early-career workers to develop the judgment and agency needed for more complex tasks. The article argues that without a solid entry-level pipeline, the future workforce could struggle to meet the demands of evolving job roles in an AI-driven economy.