The full index
Frameworks
Every named framework pulled from the show — searchable, filterable, and structured down to the steps, examples, and mistakes.
35 frameworks
Fact-or-Discomfort Press Response
Correct factual errors while learning from criticism you merely dislike
Faith-Action-Confidence Loop
Choose belief, take action, and let evidence build confidence.
Objective Truth Reset
Pause emotional momentum and reconcile the story with known facts.
Paranoid Optimism
Pursue upside while actively identifying and mitigating what could go wrong.
The Beginner’s-Mind Growth Loop
Pair experience with unfamiliar challenges to keep curiosity and options alive
Zero Price Effect
Recheck value whenever a price falls to zero
Assistant, Not Autopilot Rule
Use AI to expand creative options while humans own the finished asset
AI First-Pass Marketing Critic
Use an emotionless AI review to strengthen work before human critique
AI Pre-Review Critic
Use emotionless AI feedback to strengthen work before human review
Builder DNA Loop
Turn curiosity into rapid experiments, then iterate from what happens
Creative Collisions
Combine richer life inputs with relevant expertise to trigger new connections
Experiment-Based Quitting
Treat commitments as experiments, extract the lesson, and stop when they no longer work.
Get It Out, Then Edit
Separate idea generation from editing so judgment does not suppress the first draft.
Intellectual CrossFit
Force multiple thoughts, challenge the first, and ground abstractions in examples.
Iterative Reasoning Loop
Generate, inspect, revise, and broaden an answer before presenting it
Sculpting-to-Gardening Creative Model
Design conditions for AI drafts, then sculpt the details yourself
Chunk Up, Down, and Laterally
Navigate abstraction by moving between categories, examples, and analogies.
Directional, Not Absolute AI Rule
Let AI set direction, then apply human judgment to the final 20 percent
Personal Board Advice Filter
Use simulated advice to widen your thinking, then select what fits
Bad-Weather Opportunity Scan
Use adverse conditions to find openings that disappear in easy markets.
High Agency, Low Tolerance Model
Pair proactive experimentation with intolerance for fixable friction.
Two-Phase Grind Mindset
Persist through slow periods and accelerate when results reveal a winning path
AI Capacity Reinvestment Model
Reinvest automated time in higher-value creativity and innovation.
Conviction-Based Perseverance
Make deliberate short-term trade-offs to pursue a deeply held long-term bet.
Convince Me AI Can't Do It
Assume AI can solve the problem, then locate the precise constraint when it cannot
Long-Game Probability Strategy
Judge repeated decisions by expected value instead of one painful outcome.
Point-of-View Feedback Filter
Hear broad feedback, then act only on signals consistent with informed conviction.
Post-Scarcity Intelligence Advantage
Turn abundant intelligence into advantage through ideas and sustained execution.
Pull-It-Apart Learning Method
Deconstruct a topic, question its parts, then progress from learning to making
Zero and Wall Reset
Restore post-achievement momentum by becoming a beginner and choosing a new obstacle.
Second-Act Improvement Loop
Use recurring losses to update the playbook instead of expecting linear progress.
Deliberately Sloppy Practice
Lower the initial quality bar so curiosity and repetition can beat perfectionism
Worst-Case Reframing
Define the realistic downside, accept it, and redirect attention toward opportunity.
Internal-and-External Customer Lens
Define what each customer needs today, then use AI to deliver it faster
Too-Good-to-Be-True Rule
Treat extraordinary ease or upside as a trigger for stronger verification.