Decisions

Good decisions follow good questions that clearly define the real problem

The eternal cognitive loop — awareness, intent, obstacle, question, theory, experiment, feedback, reflection, evolve. The point of play is mastery of this loop. Games compress it to seconds. Offices stretch it to quarters. Play is where you get thousands of reps at the thing that actually matters.

VVFL Flow

Decisions are only as valuable as they are practiced and learned from.

The Validated Virtuous Feedback Loop — Flow

Tight-Five	Question	Dig Deeper
Frame	What are we actually deciding?	Problem Solving
Gather	What do we know? What's missing?	Decision Algorithms
Prioritise	Which option, given constraints?	Domains
Impact	What's the next concrete step?	Protocols
Learn	What happened? Why?	Decision Journal

Navigation System

Decisions are where your navigation system define your behavior patterns.

System	Decision Function
Value	Select setpoints: what you are unwilling to violate
Belief	Select direction: what future you are betting on
Control	Select execution: which protocol runs now

Conviction

Use tight-five prioritising questions before committing with full conviction:

1. Why does this matter now?
2. What truths must constrain this choice?
3. What leverage do we actually control?
4. What perspective gives us edge?
5. Which metric proves this was the right move?

Dis-ease comes from lack of commitment to convictions

Philosophy

A good database of problems, decisions, and flow of logic is the most valuable asset any organisation can own. Most organisations lose this asset — a problem solved is a problem forgotten, and the judgment that produced the solution walks out the door with the person who made the call.

Free will, exercised well, is decision process mastery. Not better predictions — better calibration. Wayne Smith coaches this in rugby: review HOW the decision was made, not IF it was right. Todd Simkin runs the same loop in trading: state your prior, take the action, observe the actual, update the prior.

• Single-loop learning: Adjust actions to fix errors (e.g., working harder after a failure).
• Double-loop learning: Re-examine value and beliefs (e.g., "Is this goal still meaningful?").

Decisions must be judged on the process for making them not their outcomes.

Domains

Apply the loop to specific contexts:

Domain	Focus	Key Trade-offs
Tech Stack	What tools to build with	Speed vs. flexibility, control vs. convenience
Infrastructure Economics	What to run where at each stage	Cost vs. control, simplicity vs. scale
AI Strategy Review	Where AI earns its keep	Exploration vs. exploitation, spend vs. savings
Blockchain	Which chain, which consensus	Decentralization vs. throughput, security vs. cost
Meetings	How groups decide together	Speed vs. alignment, async vs. synchronous
Decision Journal	How to document choices	Speed of decision vs. quality of learning
Decision Algorithms	Which heuristics to apply	Explore vs. exploit, optimize vs. satisfice

Cognitive-Emotive Loops

This model describes a cyclical pattern where thoughts and emotions fuel each other, often leading to stuck behaviors. For example:

• Cognitive trigger: A belief like "I'm underpaid and undervalued".
• Emotive response: Anger or resentment, which reinforces the initial thought.
• Behavioural outcome: Avoidance or entitlement, perpetuating the loop.

Breaking this loop requires self-awareness to recognize the pattern, acceptance to reduce self-judgment, and interruption through body-focused attention or cognitive restructuring.

Habit Loops

Popularized by Charles Duhigg and others, this framework explains how habits form through a three-step cycle:

1. Cue: A trigger (e.g., a notification on your phone) prompts action.
2. Routine: The habitual behavior (e.g., scrolling social media).
3. Reward: A dopamine-driven reinforcement (e.g., momentary distraction).

To modify habits, interventions target the cue (e.g., removing triggers) or reward (e.g., substituting healthier alternatives).

OODA Loops

These loops describe how behavior is shaped by responses to actions:

• Balancing loops: Stabilize behavior (e.g., slowing down when a car speed monitor shows you're over the limit).
• Reinforcing loops: Amplify behavior (e.g., social media "likes" encouraging more posts).

Effective feedback loops rely on timely measurement and actionable comparisons (e.g., tracking progress toward a goal).

Analysis Paralysis

Constant questioning of life choices can create a "loop" of indecision. Key features include:

• Overanalysis: Repeatedly weighing options without resolution.
• Fear of regret: Avoiding decisions to prevent potential mistakes.
• Emotional exhaustion: The loop drains mental energy, worsening self-doubt.

Strategies to escape this cycle include setting decision deadlines and embracing "good enough" choices.

Context

• Navigation — Value, belief, and control systems that guide choices
• Problem Solving — The upstream process that feeds decisions
• Meetings — Where group decisions get made (or wasted)
• Decision Algorithms — Heuristics for when to commit
• Decision Journal — Document the process, not just the outcome
• Questions — The capability that sharpens what you decide
• Tech Stack Decisions — The decision process applied to technology
• AI Strategy Review — The decision process applied to AI investment
• Infrastructure Economics — The decision process applied to infrastructure cost
• Wayne Smith — Process coaching: review HOW, not IF
• Todd Simkin — Calibration loops: prior → action → actual → update

Questions

What decision are you avoiding by gathering more information?

• If decisions are judged on process not outcomes, how would you rate your current process?
• Which of your decisions run on values and which run on fear?
• When did you last break an analysis paralysis loop — and what broke it?