Turn On, Tune In, Drop Out

Overview
An essay that traces the historical context of learning-from the 1960s psychedelic rebellion to today's era of cognitive outsourcing-while questioning what learning means when AI can think faster than humans. It argues that technical leaders must rethink education and skill development for teams in an AI-augmented world.

Key Takeaways

• AI changes how we process information and influences brain function.
• Traditional education models are insufficient for rapid AI advancement.
• Leaders should foster meta-learning, critical thinking, and adaptability.
• Emphasize skills like prompt engineering, model interpretation, and ethical AI use.
• Encourage a culture of continuous experimentation and learning.

Who Would Benefit

• Engineering managers looking to upskill their teams.
• Technical leaders navigating AI integration.
• Software architects interested in AI-driven design.
• Learning and development professionals in tech.
• Anyone curious about the future of thinking in an AI era.

Frameworks and Methodologies

• Meta-learning loops for continuous skill adaptation.
• Human-in-the-loop design principles.
• Ethical AI decision frameworks.