Why is AI? 10 Coaching Practices to Try

Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For Why is AI, these are the strongest matches in the current practice library.

Practices that may help

1. Build a library of cases and reason from them
   Accumulate a diverse set of cases with known outcomes, and retrieve structurally similar ones when facing a new problem.
   Analogical Reasoning
2. Automatic Investing, Made Practical
   Automating investments removes the behavioral errors — panic selling, market timing, procrastination — that reliably destroy returns for most individual investors. Systematic, automatic contributions into low-cost index funds have outperformed most active strategies over the long term, as documented in decades of observational and index-fund research.
3. Hire people who share the Why, not just the skills
   Skills can be learned; shared belief cannot — filtering for Why-alignment at hiring is the highest-leverage culture move.
   Start With Why: Leading Through Purpose
4. Use documentary and large-scale art to trigger awe
   Watch content that conveys genuine vastness — deep space, ecosystems, historical scale — with full attention rather than as background.
   Awe and Well-Being, Made Practical
5. End every AAR with one specific, time-bound next action
   An AAR without a concrete next action produces insight without change.
   After-Action Review: The US Army’s Tool for Continuous Learning
6. After-Action Review: The US Army’s Tool for Continuous Learning
   An after-action review (AAR) is a structured debriefing developed by the US Army that asks four questions after any event: What was supposed to happen? What actually happened? What caused the difference? What do we do differently next time? Applied consistently, AARs build a culture of learning from experience rather than simply moving on. The evidence base is primarily observational and practice-based; experimental studies are limited but supportive.
7. Separate judgment from analysis in the debrief
   The AAR only produces learning when the analysis phase is free of performance judgments.
   After-Action Review: The US Army’s Tool for Continuous Learning
8. Consistent-mapping practice
   Always pair the same stimulus with the same response — inconsistency permanently blocks automaticity.
   Automaticity: When Skills Run Themselves
9. Trim model complexity
   Prefer the simplest model of a situation that still fits all the evidence.
   Occam’s Razor: Prefer the Simpler Explanation
10. Automaticity: When Skills Run Themselves
    Automaticity is the state in which a practiced skill operates without consuming working-memory capacity — the result of consistent stimulus-response pairing across many repetitions. Schneider and Shiffrin’s landmark research established that automatic processing is fast, parallel, and load-resistant, while controlled processing is slow, serial, and capacity-limited. The transition requires consistent mapping and sufficient volume of deliberate practice.

Does this sound like the set of challenges you might be facing?

• I keep facing the same shape of decision over and over and starting from scratch every time, and I know I’ve lived through situations just like it that turned out a certain way→
• I keep hiring for the most impressive resume and then watching them work purely transactionally, and I want to start screening for whether someone actually believes in what we’re doing→
• I can’t exactly hop on a plane to see the northern lights, but I’m stuck at home most nights half-watching something while scrolling my phone→
• I have the same realization after every messy episode→
• Every time I try to look back at what went wrong it just turns into me beating myself up→

Describe your situation in your own words to search the complete practice library.