Claim 1: Adoption fails from habits not training
AI adoption failure is primarily a habit problem rather than a training problem
AI adoption failure is primarily a habit problem rather than a training problem
Building an AI reflex muscle can be accomplished in a 20-minute exercise
The exercise involves identifying three time-wasting tasks, selecting one, and creating a solution using ChatGPT or Claude
The reflex to automatically spot AI opportunities is more valuable than individual automated solutions
Regular practice trains the brain to automatically identify tasks suitable for AI automation
"The solution you build today is nice. The reflex you develop is what changes everything."
Kamil Banc
20 minutes
Time required to complete the AI reflex muscle building exercise and create one automated workflow
3 tasks
Number of time-wasting tasks to identify during the initial assessment phase
1 workflow
Number of automated solutions participants will create during the 20-minute exercise
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This methodology builds on the previous week's analysis of AI adoption failures, identifying habits as the core issue rather than training deficiencies. The 20-minute exercise provides a structured approach: practitioners stop their regular work, document three time-consuming tasks, select one for automation, and implement a solution using tools like ChatGPT or Claude. The framework emphasizes that while the immediate output (one automated task) provides value, the real transformation comes from developing pattern recognition skills that automatically identify AI opportunities. Practitioners can apply this by treating the exercise as the first step in building a consistent habit of spotting automation opportunities throughout their daily work.