AI automates the entry-level "grunt work" that traditionally formed the base of the corporate pyramid. This transforms organizations into diamond shapes, with fewer junior roles. This poses a new challenge: junior hires may know AI tools but lack the wisdom and judgment gained from that foundational experience.

Previously, teams needed specialists ('ammunition') to execute tasks. With AI copilots, a single, high-agency individual ('barrel') can now build entire products. This changes hiring strategy to prioritize resourceful generalists who can leverage AI to knock down doors and get things done independently.

AI's primary impact won't be replacing experienced professionals but rather eliminating the need for junior hires. By giving senior employees "10x" capabilities, companies can scale output without expanding headcount at the entry level, creating a significant hiring bottleneck for new graduates.

While AI-native, new graduates often lack the business experience and strategic context to effectively manage AI tools. Companies will instead prioritize senior leaders with high AI literacy who can achieve massive productivity gains, creating a challenging job market for recent graduates and a leaner organizational structure.

Short-term, AI amplifies senior engineers who can validate its output. Long-term, as AI tools improve and coding becomes a commodity, the advantage will shift. Junior developers who are native to AI tooling and don't have to "unlearn" old habits will become highly valuable, especially given their lower cost.

When building core AI technology, prioritize hiring 'AI-native' recent graduates over seasoned veterans. These individuals often possess a fearless execution mindset and a foundational understanding of new paradigms that is critical for building from the ground up, countering the traditional wisdom of hiring for experience.

The 'cracked engineer' archetype is a direct response to AI's growing capabilities. As AI automates the work of average engineers, the value of human engineers shifts to exceptional tasks. Companies now prioritize hiring these highly productive superstars who can supervise multiple AI instances, as AI itself can handle the rest.

Experience alone no longer determines engineering productivity. An engineer's value is now a function of their experience plus their fluency with AI tools. Experienced coders who haven't adapted are now less valuable than AI-native recent graduates, who are in high demand.

Notion skips mid-level hires, focusing on a "barbell" shape: junior engineers who are highly productive with AI tools and senior engineers who provide architectural direction and "taste," which AI lacks. This maximizes leverage and mentorship.