To overcome the fear of new AI technology, block out dedicated, unstructured "playtime" in your calendar. This low-pressure approach encourages experimentation, helping you build the essential skill of quickly learning and applying new tools without being afraid to fail.

Mandating AI usage can backfire by creating a threat. A better approach is to create "safe spaces" for exploration. Atlassian runs "AI builders weeks," blocking off synchronous time for cross-functional teams to tinker together. The celebrated outcome is learning, not a finished product, which removes pressure and encourages genuine experimentation.

To get teams comfortable with AI, start with playful, interactive exercises that have no business goal, like styling an app to look like MySpace. This low-stakes experimentation makes the technology less intimidating, fosters creative thinking, and helps participants discover novel applications they can later bring to their actual work.

To drive AI adoption, CMO Laura Kneebush avoids appointing a single expert and instead makes experimentation "everybody's job." She encourages her team to start by simply playing with AI for personal productivity and hobbies, lowering the barrier to entry and fostering organic learning.

For those without a technical background, the path to AI proficiency isn't coding but conversation. By treating models like a mentor, advisor, or strategic partner and experimenting with personal use cases, users can quickly develop an intuitive understanding of prompting and AI capabilities.

Simply instructing engineers to "build AI" is ineffective. Leaders must develop hands-on proficiency with no-code tools to understand AI's capabilities and limitations. This direct experience provides the necessary context to guide technical teams, make bolder decisions, and avoid being misled.

Mastering generative AI requires more than carving out an hour for thinking. It demands large, uninterrupted blocks of time for experimentation and play. Tavel restructured her schedule to dedicate entire days (like Mondays) to this deep work, a practice contrary to the typical high-velocity, meeting-driven VC calendar.

In the AI era, leaders' decades-old intuitions may be wrong. To lead effectively, they must become practitioners again, actively learning and using AI daily. The CEO of Rackspace blocks out 4-6 a.m. for "catching up with AI," demonstrating the required commitment to rebuild foundational knowledge.

A product marketer with a non-technical background found that learning AI fundamentals and vocabulary gave her the confidence to collaborate effectively with engineers. This specific knowledge put her far ahead of her peers, demonstrating that coding isn't a prerequisite for leadership in AI-driven teams.