using-deliberate-decisions

name	using-deliberate-decisions
description	Introduction to the Deliberate Decisions framework - use when helping humans make high-stakes decisions

Deliberate Decisions

A framework for systematic decision-making. Helps surface hidden assumptions, separate facts from speculation, and make rigorous choices.

When to Use

Use this framework when a human faces a high-stakes decision:

• Strategic business decisions (M&A, market entry, major investments)
• Career decisions (job changes, pivots)
• Technical decisions (architecture, vendor selection)
• Any decision where being wrong is costly

Decision Weight

Not all decisions need the same rigor. After understanding the decision in Thesis Gate, suggest appropriate depth:

Weight	Time	Best For
Light	<10 min	Reversible decisions, domain expertise, lower stakes
Medium	30-40 min	Moderate stakes, some uncertainty
Complete	60-90 min	High stakes, irreversible, significant uncertainty

Weight affects depth, not gates. All 7 gates always run.

See deliberate-decisions:weight-classification for detailed guidance.

The Seven Gates

Every decision passes through seven mandatory gates. You can exit early, but you cannot skip gates.

Gate	Name	Purpose
1	Thesis	Articulate what we're deciding and why
2	Landscape	Map Decision Points, Intersections, alternatives
3	Research	Gather evidence, find reference class
4	Calibration	Separate Facts from Assumptions, update Knowns/Unknowns
5	Contrarian	Pre-mortem, steel-man opposition, surface biases
6	Synthesis	Must-Be-True Conditions, Exit Criteria, recommendation
7	Decision	Human chooses with full picture

Starting a Decision

Use /deliberate-decisions:decide to begin. Options:

• /deliberate-decisions:decide - AI suggests weight after Thesis gate
• /deliberate-decisions:decide --light - Start at Light depth
• /deliberate-decisions:decide --medium - Start at Medium depth
• /deliberate-decisions:decide --complete - Start at Complete depth

Weight can be upgraded mid-process but not downgraded.

Core Principles

1. Decisions fail in small assumptions - Surface the hidden structure
2. Facts vs Assumptions - Rigorous separation of verifiable from speculative
3. System 2 thinking - Gates enforce deliberate, not intuitive, analysis
4. Adversarial by default - Pre-mortem and steel-manning are required
5. One question at a time - AI builds the model incrementally
6. Right-sized rigor - Match depth to stakes with weight classification

Key Concepts

• Decision Points: Individual choices or assumptions that influence outcome
• Decision Intersections: How Decision Points depend on or conflict with each other
• Must-Be-True Conditions: Assumptions that must hold for the decision to succeed
• Exit Criteria: Pre-committed tripwires to reverse the decision if needed
• Weight: Light/Medium/Complete depth classification

Upgrading Mid-Process

User can upgrade weight anytime by saying "let's go deeper."

AI should suggest upgrading when detecting:

• Emerging complexity beyond current weight
• Low confidence on critical assumptions
• Surprising research findings
• Stakes higher than initially framed

Already-completed gates stay as-is. Only remaining gates run at higher depth.

Commands

Command	Action
/deliberate-decisions:decide	Start new decision from Thesis gate
/deliberate-decisions:decide --light	Start at Light depth
/deliberate-decisions:decide --medium	Start at Medium depth
/deliberate-decisions:decide --complete	Start at Complete depth
/deliberate-decisions:advocate	Generate compelling case FOR
/deliberate-decisions:detract	Generate compelling case AGAINST
/deliberate-decisions:review-decision	Review past decision against outcomes
/deliberate-decisions:resume-decision	Continue paused decision