The speaker discusses the relevance of developer workshops in the age of AI, noting that AI excels at providing step-by-step guides and tutorials. However, the core value of workshops lies in active learning through doing, where mistakes have consequences and require problem-solving. This hands-on struggle deepens understanding in ways passive reading or AI-generated explanations cannot replicate. Furthermore, workshops expose learners to issues they might not have anticipated, a crucial aspect for real-world development.The effectiveness of workshops depends on overcoming common pitfalls: environmental setup issues, overly large steps, insufficient explanation of "why," and inadequate verification. The speaker advocates for hosted environments that standardize the starting point for all participants, enabling better support and more complex learning scenarios. While AI can assist in drafting workshop content, it falters in understanding the human learning process. AI optimizes for correctness, not teachability, and cannot anticipate learner confusion.The critical step in workshop creation is testing with real people, as AI-generated material often reads well but fails in practice. The pressure from AI is most acutely felt in voluntary learning scenarios driven by curiosity, as AI can satisfy that curiosity more efficiently and at no cost. However, workshops with a clear business driver, like sales demos or customer training, remain highly relevant. Ultimately, workshops are about fostering a learning rhythm that AI cannot fully replicate.