When EV Misleads: Expected Utility and Asymmetric Downside

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1Why Good Decisions Can Have Bad Outcomes 2Risk vs Uncertainty: How Much Rigor Is Worth It 3The Decision Quality Spine: From Objective to Commitment 4The Decision One-Pager: Minimum Viable Rigor 5Rewrite and Log: Turning Decisions Into Learning Assets

6Fast vs Slow as a Control Lever, Not a Personality Test 7The Slowdown Conditions: When Intuition Degrades 8The Slowdown Trigger List: A Minimum-Viable Escalation Rule 9The Meeting Checkpoint Script: Escalate Without Drama 10Fast vs Slow in Practice: Incidents and Roadmap Bets

11From Bias Labels to Safeguards: The Three Failure Clusters 12Estimation Traps: Overconfidence, Ranges, and De-Anchoring 13Narrative and Evidence Failures: Disconfirming Evidence and Motivated Reasoning 14Social and Team Debiasing: Pre-Mortems, Red Teams, and Role Separation

15The Framing Workflow: From Fuzzy Ask to Decision-Ready 16Incentives: The Hidden Engine Behind Stakeholder Behavior 17Opportunity Cost: Choosing Means Not Choosing 18Second-Order Effects and Inversion: Seeing Around Corners Without Guessing 19Feedback Loops and Model Selection: A Small Toolkit That Stays Usable

20Reference Classes: Starting From the Outside View 21The Base Rate Sheet: Making Assumptions Auditable 22Decomposition: Turning One Big Guess Into Several Smaller Ones 23Range Formats That Work: 50/80/90 and Low–Most Likely–High 24Calibration and Update-Ready Forecasts

25From Ranges to Choices: The EV + Risk Table

26When EV Misleads: Expected Utility and Asymmetric Downside

27Robustness Tactics: Reversibility, Downside Protection, and Regret Minimization 28Value of Information: Decide What to Learn Before You Decide 29Proportional Experiments: A Learning Plan That Respects Cost of Delay 30The Decision Playbook Loop: Logs, After-Action Reviews, and a Learning Mindset

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When EV Misleads: Expected Utility and Asymmetric Downside