weight-classification

name	weight-classification
description	Classify decision weight (Light/Medium/Complete) and adjust gate depth accordingly

Weight Classification

Purpose: Match decision rigor to decision stakes. All 7 gates run at appropriate depth.

The Three Weights

Weight	Time	When to Use
Light	<10 min	Reversible decisions, domain expert, lower stakes
Medium	30-40 min	Moderate stakes, some uncertainty, standard rigor
Complete	60-90 min	High stakes, irreversible, significant uncertainty

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

Weight Selection

When to Suggest Weight

Weight is suggested at the end of Thesis Gate, after the AI understands:

• Financial/strategic impact
• Reversibility
• Time horizon
• User's domain expertise
• Complexity revealed

Suggestion Format

Based on what you've described:
- [Key factor 1]
- [Key factor 2]
- [Key factor 3]

I recommend **[Weight]** depth (~[time] minutes).

[Light: Quick pass through all gates - good for reversible decisions where you have expertise]
[Medium: Standard rigor - balances thoroughness with efficiency]
[Complete: Full analysis - for high-stakes, hard-to-reverse decisions]

Does that feel right, or would you prefer [alternative]?

Weight Selection Criteria

Factor	Light	Medium	Complete
Financial impact	<$10K	$10K-$100K	>$100K
Reversibility	Easy (days)	Moderate (weeks/months)	Hard (years/permanent)
Domain expertise	Expert	Familiar	New territory
Stakeholders affected	Just me	Team/department	Organization/customers
Time to know outcome	Days/weeks	Months	Years

If any factor suggests Complete, recommend Complete.

Depth by Gate

Gate 1: Thesis

Aspect	Light	Medium	Complete
Questions	3-4 key questions	5-6 questions	Full exploration
Stakeholders	List only	Identify conflicts	Map relationships
Constraints	Non-negotiables only	All constraints	Constraint flexibility analysis
Success criteria	1-2 metrics	3-4 metrics	Comprehensive metrics + timeline

Gate 2: Landscape

Aspect	Light	Medium	Complete
Alternatives	2-3 + do nothing	4-5 + do nothing	5-6+ + creative options
Decision Points	Surface level (3-5)	Thorough (6-10)	Comprehensive (10+)
Intersections	Note obvious ones	Map dependencies	Full intersection analysis
Knowns/Unknowns	Quick categorization	Standard matrix	Detailed with confidence

Gate 3: Research

Aspect	Light	Medium	Complete
Web research	None - user knowledge	1-2 targeted searches	Thorough multi-source
Reference class	Ask user if known	Find basic reference	Deep reference class analysis
Document review	Skip unless provided	Review key docs	Comprehensive review
Evidence quality	Trust user	Basic assessment	Full quality evaluation

Gate 4: Calibration

Aspect	Light	Medium	Complete
Fact/Assumption split	Quick pass	Full categorization	Detailed with evidence
Confidence levels	High/Low only	High/Medium/Low	Calibrated percentages
Assumption inventory	Critical only	Important + critical	Comprehensive inventory
Blind spots	Quick check	Identify gaps	Deep blind spot analysis

Gate 5: Contrarian

Aspect	Light	Medium	Complete
Pre-mortem scenarios	Top 3 risks	5 scenarios	5+ with probability/severity
Steel-man	Skip	Top rejected alternative	All rejected alternatives
Bias audit	Quick self-check	Standard audit	Full bias analysis
Second-order effects	Note obvious	One level deep	Two levels deep

Gate 6: Synthesis

Aspect	Light	Medium	Complete
Must-Be-True	Top 3 conditions	5-6 conditions	Comprehensive conditions
Exit criteria	1-2 basic tripwires	3-4 specific tripwires	Detailed thresholds + dates
Risk assessment	High-level summary	Consolidated risks	Full risk matrix
Recommendation	Brief	Standard with rationale	Comprehensive with confidence

Gate 7: Decision

Aspect	Light	Medium	Complete
Summary	One paragraph	Standard summary	Full decision summary
Documentation	Minimal artifact	Standard artifact	Complete artifact
Rationale capture	Brief	Key factors	Verbatim + deciding factors

Upgrading Mid-Process

User-Initiated Upgrade

User can say "let's go deeper" at any point. AI responds:

Upgrading to [Weight]. Remaining gates will run at [Weight] depth.
[If past gates were Light, note what was skipped that won't be revisited]

Already-completed gates stay as-is. No going back.

AI-Suggested Upgrade

AI should suggest upgrading when it detects:

Signal	Example	Suggestion
Emerging complexity	More alternatives than expected	"This is more complex than it first appeared. Want to upgrade to Medium/Complete?"
Low confidence on critical assumptions	Key assumption rated Low	"A critical assumption has low confidence. Recommend upgrading to get more rigor here."
Surprising research findings	Reference class shows high failure rate	"The reference class suggests higher risk than expected. Want to go deeper?"
Stakes seem higher	Financial impact larger than initially framed	"The stakes seem higher than initially framed. Recommend Complete depth."
User uncertainty	User expresses doubt repeatedly	"You seem uncertain about some key points. Want to spend more time here?"

Upgrade Suggestion Format

⚠️ **Upgrade Suggestion**

I'm noticing [signal]. This suggests [weight] depth might be more appropriate.

Current: [Weight] (~X min remaining)
Suggested: [Weight] (~Y min remaining)

[Brief explanation of what deeper analysis would add]

Continue at current depth, or upgrade?

Weight in Artifact

Document the weight in the decision artifact header:

# Decision: [Statement]

**Weight:** [Light/Medium/Complete]
**Estimated time:** [X minutes]
**Upgraded:** [Yes - from Light at Gate 3 / No]

Commands

Weight can be specified when starting:

/decide              → AI suggests weight after Thesis
/decide --light      → Start at Light (can upgrade)
/decide --medium     → Start at Medium (can upgrade)
/decide --complete   → Start at Complete

If weight is pre-specified, skip the weight suggestion step in Thesis but still allow upgrades.