Deel's CEO predicts that new graduates, being "AI native," will master AI tools so effectively they'll become more productive than experienced workers reluctant to adapt. This generation will leverage AI as a superpower, fundamentally changing the value of experience versus tool proficiency.

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.

With AI models and workflows becoming obsolete in as little as a year, mastering a single tool is a failing strategy. The most valuable skill is becoming comfortable with constant change and the process of repeatedly being a beginner, as this adaptability is the only sustainable advantage.

AI tools are so novel they neutralize the advantage of long-term experience. A junior designer who is curious and quick to adopt AI workflows can outperform a veteran who is slower to adapt, creating a major career reset based on agency, not tenure.

With frontier AI models doubling their autonomous task-handling capability every seven months, any specific tool or workflow will quickly become obsolete. The sustainable career advantage lies not in mastering one system, but in developing a habit of constant experimentation to adapt to the accelerating pace of change.

In the current AI landscape, knowledge and assumptions become obsolete within months, not years. This rapid pace of evolution creates significant stress, as investors and founders must constantly re-educate themselves to make informed decisions. Relying on past knowledge is a quick path to failure.

The pace of AI development is so rapid that technologists, even senior leaders, face a constant struggle to maintain their expertise. Falling behind for even a few months can create a significant knowledge gap, making continuous learning a terrifying necessity for survival.

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.

In an AI-driven world, education and career development must shift focus from deep, narrow knowledge (which AI can replicate) to 'horizontal skills.' These include critical thinking, reasoning, and judgment—essentially, knowing the right questions to ask the AI model to get the best results.