Since modern AI is so new, no one has more than a few years of relevant experience. This levels the playing field. The best hiring strategy is to prioritize young, AI-native talent with a steep learning curve over senior engineers whose experience may be less relevant. Dynamism and adaptability trump tenure.

People in their early 20s are the first truly "AI-native" generation, using AI from the ground up in their engineering process, making them fundamentally faster. To innovate, companies must hire these young engineers to teach the rest of the organization new problem-solving approaches.

In contrast to widespread tech layoffs, ServiceNow is prioritizing hiring early-career professionals with 0-2 years of experience. The strategy is to tap into a generation of "AI natives" who intuitively leverage new AI tools, viewing this as a key advantage over experienced but less-adapted talent.

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.

Brex structures its AI teams into small pods, combining young, AI-native talent who think differently with experienced staff engineers who understand the existing codebase, product, and customer needs. This blends novel approaches with practical execution.

To bridge the AI skills gap with experienced staff, Cloudflare pairs "AI native" interns with senior employees. The explicit goal is for the junior employees to teach their senior colleagues how to use new tools effectively. This reverses the traditional mentorship dynamic to accelerate adoption among those most resistant to change.

The ideal founding team for an AI startup can be an age-differentiated pair. A young, AI-native founder brings contrarian ideas and speed, while an older co-founder with big-tech experience provides structure, best practices, and operational discipline, creating a powerful balance.

Contrary to the belief that AI architecture is only for senior staff, Atlassian finds that "AI native" junior employees are often more effective. They are unburdened by old workflows and naturally think in terms of AI-powered systems. Senior staff can struggle with the required behavioral change, making junior hires a key vector for innovation.

Instead of formal training, pair tech-native junior employees with experienced senior leaders. This apprenticeship model combines the juniors' technical fluency with the seniors' business context and judgment, creating a more powerful and effective way to integrate AI and drive innovation.