Gate 4: Calibration

Purpose: Pause to consolidate what we know versus what we assume before analysis.

Announce: "Moving to Calibration Gate - let's separate facts from assumptions."

Entry Criteria

• Research Gate completed
• Evidence gathered and evaluated

Why This Gate Exists

Research often blurs the line between facts and assumptions. Before making critical decisions, we must:

1. Distinguish verified facts from beliefs - What do we actually know vs. what do we think we know?
2. Acknowledge uncertainty honestly - Overconfidence kills good decisions
3. Surface hidden assumptions - Unexamined assumptions are the most dangerous
4. Calibrate confidence levels - Ensure our certainty matches our evidence

Skipping calibration leads to decisions built on shaky foundations that feel solid.

Process

1. Review All Claims

Go through all findings from previous gates and categorize each claim:

Fact - Verified with reliable evidence

• Has credible source
• Can be independently verified
• Not based on projection or extrapolation

Assumption - Believed but not verified

• Based on judgment or experience
• Extrapolated from limited data
• Accepted without direct evidence

Ask for each claim:

• "What evidence supports this?"
• "Could a skeptic accept this as fact?"
• "Are we treating an assumption as fact?"

2. Update Confidence Levels

Revisit all Decision Points from Landscape Gate. For each:

• Review evidence gathered in Research Gate
• Adjust confidence based on what we learned
• Document what changed and why

Confidence scale:

• High - Strong evidence, multiple sources, directly applicable
• Medium - Some evidence, reasonable extrapolation
• Low - Limited evidence, significant uncertainty
• Unknown - No evidence, pure assumption

3. Rebuild Knowns/Unknowns

Update the Knowns/Unknowns matrix with research findings:

Known - Verified facts with evidence

• Move items from Unknown-Knowable when answered
• Add new facts discovered in research

Unknown-Knowable - Still unanswered but answerable

• Remove items that were researched
• Add new questions that emerged

Unknown-Unknowable - Cannot be determined

• Accept these as necessary assumptions
• Document the uncertainty explicitly

4. Assumption Inventory

Create a comprehensive list of all assumptions the decision depends on:

For each assumption:

• Statement: What we're assuming
• Criticality: How much does the decision depend on this? (critical/important/minor)
• Testability: Could we test this before committing? (testable/partially testable/untestable)
• Fallback: What if this assumption is wrong?

Prioritize assumptions that are both critical and untestable - these are your biggest risks.

Depth by Weight

Light: Quick categorization of key claims. Focus on critical assumptions only. Simple confidence (high/low).

Medium: Full fact/assumption separation. Standard confidence scale. Important and critical assumptions inventoried.

Complete: Detailed categorization with evidence citations. Full confidence calibration with reasoning. Comprehensive assumption inventory. Deep blind spot analysis.

Upgrade Detection

Suggest upgrading if:

• Many claims fall into "assumption" category
• Confidence on critical assumptions is Low
• Significant blind spots identified
• User realizes they're less certain than they thought

Upgrade prompt:

⚠️ Calibration is revealing significant uncertainty:
- [X of Y key claims are assumptions, not facts]
- [Critical assumption X has low confidence]
- [Blind spot identified: Y]

This level of uncertainty suggests deeper analysis would be valuable.

Current: [Weight]
Suggested: [Higher Weight] - would provide [more rigorous assumption testing]

Continue at current depth, or upgrade?

Output

Create calibration log:

# Calibration Log: [Decision]

## Facts (Verified)

| Claim | Evidence | Source | Confidence |
|-------|----------|--------|------------|
| [claim 1] | [supporting evidence] | [source] | High |
| [claim 2] | [supporting evidence] | [source] | High |

## Assumptions (Unverified)

| Claim | Basis | Criticality | Testability |
|-------|-------|-------------|-------------|
| [assumption 1] | [why we believe it] | Critical | Untestable |
| [assumption 2] | [why we believe it] | Important | Testable |

## Critical Risks

Assumptions that are both critical and hard to verify:

1. **[Assumption]**: [Why it's risky and what could go wrong]
2. **[Assumption]**: [Why it's risky and what could go wrong]

## Blind Spots

Areas where we lack information and haven't made explicit assumptions:

- [blind spot 1]
- [blind spot 2]

## Updated Knowns/Unknowns

**Known:**
- [verified fact with source]

**Unknown-Knowable:**
- [remaining question we could still research]

**Unknown-Unknowable:**
- [uncertainty we must accept]

## Confidence Changes

| Decision Point | Previous | Current | Reason |
|----------------|----------|---------|--------|
| [DP1] | Medium | High | [what evidence changed it] |
| [DP2] | High | Medium | [what evidence changed it] |

Save to: docs/decisions/YYYY-MM-DD-<decision-slug>/calibration-log.md

Exit Criteria

• All claims categorized as fact or assumption (depth per weight)
• Confidence levels updated based on research
• Knowns/Unknowns matrix refreshed
• Assumption inventory complete (depth per weight)
• Critical risks explicitly identified

Bias Watch

Watch for:

• Overconfidence - Treating assumptions as facts, inflating certainty
• Wishful thinking - Assuming favorable outcomes without evidence
• Complexity bias - Using sophisticated analysis to obscure weak foundations

Ask: "If we're wrong about our key assumptions, would we still make this decision?"

Next Gate

Proceed to: deliberate-decisions:contrarian-analysis