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skills/rapid-convergence/reference/baseline-metrics.md
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skills/rapid-convergence/reference/baseline-metrics.md
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# Achieving Strong Baseline Metrics
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**Purpose**: How to achieve V_meta(s₀) ≥ 0.40 for rapid convergence
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**Impact**: Strong baseline reduces iterations by 2-3 (40-60% time savings)
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---
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## V_meta Baseline Formula
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```
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V_meta(s₀) = 0.4 × completeness +
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0.3 × transferability +
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0.3 × automation_effectiveness
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Where (at iteration 0):
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- completeness = initial_coverage / target_coverage
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- transferability = existing_patterns_reusable / total_patterns_needed
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- automation_effectiveness = identified_automation_ops / automation_opportunities
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```
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**Target**: V_meta(s₀) ≥ 0.40
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---
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## Component 1: Completeness (40% weight)
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**Definition**: Initial taxonomy/pattern coverage
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**Calculation**:
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```
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completeness = initial_categories / estimated_final_categories
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```
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**Achieve ≥0.50 by**:
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1. Comprehensive data analysis (3-5 hours)
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2. Create initial taxonomy (10-15 categories)
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3. Classify ≥70% of observed cases
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**Example (Bootstrap-003)**:
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```
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Iteration 0 taxonomy: 10 categories
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Estimated final: 12-13 categories
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Completeness: 10/12.5 = 0.80
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Contribution: 0.4 × 0.80 = 0.32 ✅
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```
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---
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## Component 2: Transferability (30% weight)
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**Definition**: Reusability of existing patterns/knowledge
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**Calculation**:
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```
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transferability = (borrowed_patterns + existing_knowledge) / total_patterns_needed
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```
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**Achieve ≥0.30 by**:
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1. Research prior art (1-2 hours)
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2. Identify similar methodologies
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3. Document reusable patterns
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**Example (Bootstrap-003)**:
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```
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Borrowed from industry: 5 error patterns
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Existing knowledge: Error taxonomy basics
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Total patterns needed: ~10
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Transferability: 5/10 = 0.50
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Contribution: 0.3 × 0.50 = 0.15 ✅
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```
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---
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## Component 3: Automation Effectiveness (30% weight)
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**Definition**: Early identification of automation opportunities
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**Calculation**:
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```
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automation_effectiveness = identified_high_ROI_tools / expected_tool_count
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```
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**Achieve ≥0.30 by**:
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1. Analyze high-frequency tasks (1-2 hours)
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2. Identify top 3-5 automation candidates
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3. Estimate ROI (>5x preferred)
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**Example (Bootstrap-003)**:
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```
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Identified in iteration 0: 3 tools
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- validate-path.sh: 65.2% prevention, 61x ROI
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- check-file-size.sh: 100% prevention, 31.6x ROI
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- check-read-before-write.sh: 100% prevention, 26.2x ROI
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Expected final tool count: ~3
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Automation effectiveness: 3/3 = 1.0
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Contribution: 0.3 × 1.0 = 0.30 ✅
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```
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---
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## Worked Example: Bootstrap-003
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### Iteration 0 Investment: 120 min
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**Data Analysis** (60 min):
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- Queried session history: 1,336 errors
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- Calculated error rate: 5.78%
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- Identified frequency distribution
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**Taxonomy Creation** (40 min):
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- Created 10 initial categories
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- Classified 1,056/1,336 errors (79.1%)
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- Estimated 2-3 more categories needed
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**Pattern Research** (15 min):
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- Reviewed industry error taxonomies
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- Identified 5 reusable patterns
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- Documented error handling best practices
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**Automation Identification** (5 min):
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- Top 3 opportunities obvious from data:
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1. File-not-found: 250 errors (18.7%)
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2. File-size-exceeded: 84 errors (6.3%)
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3. Write-before-read: 70 errors (5.2%)
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### V_meta(s₀) Calculation
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```
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Completeness: 10/12.5 = 0.80
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Transferability: 5/10 = 0.50
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Automation: 3/3 = 1.0
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V_meta(s₀) = 0.4 × 0.80 +
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0.3 × 0.50 +
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0.3 × 1.0
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= 0.32 + 0.15 + 0.30
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= 0.77 ✅✅ (far exceeds 0.40 target)
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```
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**Result**: 3 iterations total (rapid convergence)
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---
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## Contrast: Bootstrap-002 (Weak Baseline)
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### Iteration 0 Investment: 60 min
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**Coverage Measurement** (30 min):
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- Ran coverage analysis: 72.1%
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- Counted tests: 590
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- No systematic approach documented
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**Pattern Identification** (20 min):
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- Wrote 3 ad-hoc tests
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- Noted duplication issues
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- No pattern library yet
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**No Prior Research** (0 min):
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- Started from scratch
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- No borrowed patterns
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**No Automation Planning** (10 min):
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- Vague ideas about coverage tools
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- No concrete automation identified
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### V_meta(s₀) Calculation
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```
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Completeness: 0/8 patterns = 0.00 (none documented)
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Transferability: 0/8 = 0.00 (no research)
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Automation: 0/3 tools = 0.00 (none identified)
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V_meta(s₀) = 0.4 × 0.00 +
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0.3 × 0.00 +
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0.3 × 0.00
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= 0.00 ❌ (far below 0.40 target)
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```
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**Result**: 6 iterations total (standard convergence)
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---
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## Achieving V_meta(s₀) ≥ 0.40: Checklist
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### Completeness Target: ≥0.50
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**Tasks**:
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- [ ] Analyze ALL available data (3-5 hours)
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- [ ] Create initial taxonomy/pattern library (10-15 items)
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- [ ] Classify ≥70% of observed cases
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- [ ] Estimate final taxonomy size
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- [ ] Calculate: initial_count / estimated_final ≥ 0.50?
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**Time**: 3-5 hours
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**Contribution**: 0.4 × 0.50 = 0.20
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---
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### Transferability Target: ≥0.30
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**Tasks**:
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- [ ] Research prior art (1-2 hours)
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- [ ] Identify similar methodologies
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- [ ] Document borrowed patterns (≥30% reusable)
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- [ ] List existing knowledge applicable
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- [ ] Calculate: borrowed / total_needed ≥ 0.30?
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**Time**: 1-2 hours
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**Contribution**: 0.3 × 0.30 = 0.09
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---
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### Automation Target: ≥0.30
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**Tasks**:
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- [ ] Analyze task frequency (1 hour)
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- [ ] Identify top 3-5 automation candidates
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- [ ] Estimate ROI for each (>5x preferred)
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- [ ] Document automation plan
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- [ ] Calculate: identified / expected ≥ 0.30?
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**Time**: 1-2 hours
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**Contribution**: 0.3 × 0.30 = 0.09
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---
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### Total Baseline Investment
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**Minimum**: 5-9 hours for V_meta(s₀) = 0.38-0.40
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**Recommended**: 6-10 hours for V_meta(s₀) = 0.45-0.55
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**Aggressive**: 8-12 hours for V_meta(s₀) = 0.60-0.80
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**ROI**: 5-9 hours investment → Save 10-15 hours overall (2-3x)
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---
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## Quick Assessment: Can You Achieve 0.40?
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**Question 1**: Do you have quantitative data to analyze?
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- YES: Proceed with completeness analysis
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- NO: Gather data first (delays rapid convergence)
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**Question 2**: Does prior art exist in this domain?
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- YES: Research and document (1-2 hours)
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- NO: Lower transferability expected (<0.20)
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**Question 3**: Are high-frequency patterns obvious?
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- YES: Identify automation opportunities (1 hour)
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- NO: Requires deeper analysis (adds time)
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**Scoring**:
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- **3 YES**: V_meta(s₀) ≥ 0.40 achievable (5-9 hours)
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- **2 YES**: V_meta(s₀) = 0.30-0.40 (7-12 hours)
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- **0-1 YES**: V_meta(s₀) < 0.30 (not rapid convergence candidate)
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---
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## Common Pitfalls
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### ❌ Insufficient Data Analysis
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**Symptom**: Analyzing <50% of available data
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**Impact**: Low completeness (<0.40)
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**Fix**: Comprehensive analysis (3-5 hours)
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**Example**:
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```
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❌ Analyzed 200/1,336 errors → 5 categories → completeness = 0.38
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✅ Analyzed 1,336/1,336 errors → 10 categories → completeness = 0.80
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```
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---
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### ❌ Skipping Prior Art Research
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**Symptom**: Starting from scratch
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**Impact**: Zero transferability
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**Fix**: 1-2 hours research
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**Example**:
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```
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❌ No research → 0 borrowed patterns → transferability = 0.00
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✅ Research industry taxonomies → 5 patterns → transferability = 0.50
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```
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---
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### ❌ Vague Automation Ideas
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**Symptom**: "Maybe we could automate X"
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**Impact**: Low automation score
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**Fix**: Concrete identification + ROI estimate
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**Example**:
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```
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❌ "Could automate coverage" → automation = 0.10
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✅ "Coverage gap analyzer, 30x speedup, 6x ROI" → automation = 0.33
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```
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---
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## Measurement Tools
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**Completeness**:
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```bash
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# Count initial categories
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initial=$(grep "^##" taxonomy.md | wc -l)
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# Estimate final (from analysis)
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estimated=12
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# Calculate
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echo "scale=2; $initial / $estimated" | bc
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# Target: ≥0.50
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```
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**Transferability**:
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```bash
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# Count borrowed patterns
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borrowed=$(grep "Source:" patterns.md | grep -v "Original" | wc -l)
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# Estimate total needed
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total=10
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# Calculate
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echo "scale=2; $borrowed / $total" | bc
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# Target: ≥0.30
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```
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**Automation**:
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```bash
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# Count identified tools
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identified=$(ls scripts/ | wc -l)
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# Estimate final count
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expected=3
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# Calculate
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echo "scale=2; $identified / $expected" | bc
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# Target: ≥0.30
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```
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---
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**Source**: BAIME Rapid Convergence Framework
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**Target**: V_meta(s₀) ≥ 0.40 for 3-4 iteration convergence
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**Investment**: 5-10 hours in iteration 0
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**ROI**: 2-3x (saves 10-15 hours overall)
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378
skills/rapid-convergence/reference/criteria.md
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skills/rapid-convergence/reference/criteria.md
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# Rapid Convergence Criteria - Detailed
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**Purpose**: In-depth explanation of 5 rapid convergence criteria
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**Impact**: Understanding when 3-4 iterations are achievable
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---
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## Criterion 1: Clear Baseline Metrics ⭐ CRITICAL
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### Definition
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V_meta(s₀) ≥ 0.40 indicates strong foundational work enables rapid progress.
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### Mathematical Basis
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```
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ΔV_meta needed = 0.80 - V_meta(s₀)
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If V_meta(s₀) = 0.40: Need +0.40 → 3-4 iterations achievable
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If V_meta(s₀) = 0.10: Need +0.70 → 5-7 iterations required
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```
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**Assumption**: Average ΔV_meta per iteration ≈ 0.15-0.20
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### What Strong Baseline Looks Like
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**Quantitative metrics exist**:
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- Error rate, test coverage, build time
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- Measurable via tools (not subjective)
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- Baseline established in <2 hours
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**Success criteria are clear**:
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- Target values defined (e.g., <3% error rate)
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- Thresholds for convergence known
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- No ambiguity about "done"
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**Initial taxonomy comprehensive**:
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- 70-80% coverage in iteration 0
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- 10-15 categories/patterns documented
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- Most edge cases identified
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### Examples
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**✅ Bootstrap-003 (V_meta(s₀) = 0.48)**:
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```
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- 1,336 errors quantified via MCP query
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- Error rate: 5.78% calculated automatically
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- 10 error categories (79.1% coverage)
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- Clear targets: <3% error rate, <2 min MTTR
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- Result: 3 iterations
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```
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**❌ Bootstrap-002 (V_meta(s₀) = 0.04)**:
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```
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- Coverage: 72.1% (but no patterns documented)
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- No clear test patterns identified
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- Ambiguous "done" criteria
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- Had to establish metrics first
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- Result: 6 iterations
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```
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### Impact Analysis
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| V_meta(s₀) | Iterations Needed | Hours | Reason |
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|------------|-------------------|-------|--------|
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| 0.60-0.80 | 2-3 | 6-10h | Minimal gap to 0.80 |
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| 0.40-0.59 | 3-4 | 10-15h | Moderate gap |
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| 0.20-0.39 | 4-6 | 15-25h | Large gap |
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| 0.00-0.19 | 6-10 | 25-40h | Exploratory |
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---
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## Criterion 2: Focused Domain Scope ⭐ IMPORTANT
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### Definition
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Domain described in <3 sentences without ambiguity.
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### Why This Matters
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**Focused scope** → Less exploration → Faster convergence
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**Broad scope** → More patterns needed → Slower convergence
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### Quantifying Focus
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**Metric**: Boundary clarity ratio
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```
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BCR = clear_boundaries / total_boundaries
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Where boundaries = {in-scope, out-of-scope, edge cases}
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```
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**Target**: BCR ≥ 0.80 (80% of boundaries unambiguous)
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### Examples
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**✅ Focused (Bootstrap-003)**:
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```
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Domain: "Error detection, diagnosis, recovery, prevention for meta-cc"
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Boundaries:
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✅ In-scope: All meta-cc errors
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✅ Out-of-scope: Infrastructure failures, user errors
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✅ Edge cases: Cascading errors (handle as single category)
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BCR = 3/3 = 1.0 (perfectly focused)
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```
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**❌ Broad (Bootstrap-002)**:
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```
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Domain: "Develop test strategy"
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Boundaries:
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⚠️ In-scope: Which tests? Unit? Integration? E2E?
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⚠️ Out-of-scope: What about test infrastructure?
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⚠️ Edge cases: Multi-language support? CI integration?
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BCR = 0/3 = 0.00 (needs scoping work)
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```
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### Scoping Technique
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**Step 1**: Write 1-sentence domain definition
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**Step 2**: List 3-5 explicit in-scope items
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**Step 3**: List 3-5 explicit out-of-scope items
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**Step 4**: Define edge case handling
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**Example**:
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```markdown
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## Domain: Error Recovery for Meta-CC
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**In-Scope**:
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- Error detection and classification
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- Root cause diagnosis
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- Recovery procedures
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- Prevention automation
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- MTTR reduction
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**Out-of-Scope**:
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- Infrastructure failures (Docker, network)
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- User mistakes (misuse of CLI)
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- Feature requests
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- Performance optimization (unless error-related)
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**Edge Cases**:
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- Cascading errors: Treat as single error with multiple symptoms
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- Intermittent errors: Require 3+ occurrences for pattern
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- Error prevention: In-scope if automatable
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```
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---
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## Criterion 3: Direct Validation ⭐ IMPORTANT
|
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### Definition
|
||||
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Can validate methodology without multi-context deployment.
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### Validation Complexity Spectrum
|
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**Level 1: Retrospective** (Fastest)
|
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- Use historical data
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- No deployment needed
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- Example: 1,336 historical errors
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|
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**Level 2: Single-Context** (Fast)
|
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- Test in one environment
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- Minimal deployment
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||||
- Example: Validate on current project
|
||||
|
||||
**Level 3: Multi-Context** (Slow)
|
||||
- Test across multiple projects/languages
|
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- Significant deployment overhead
|
||||
- Example: 3 project archetypes
|
||||
|
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**Level 4: Production** (Slowest)
|
||||
- Real-world validation required
|
||||
- Months of data collection
|
||||
- Example: Monitor for 3-6 months
|
||||
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||||
### Time Impact
|
||||
|
||||
| Validation Level | Overhead | Example Iterations Added |
|
||||
|------------------|----------|--------------------------|
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| Retrospective | 0h | +0 (Bootstrap-003) |
|
||||
| Single-Context | 2-4h | +0 to +1 |
|
||||
| Multi-Context | 6-12h | +2 to +3 (Bootstrap-002) |
|
||||
| Production | Months | N/A (not rapid) |
|
||||
|
||||
### When Retrospective Validation Works
|
||||
|
||||
**Requirements**:
|
||||
1. Historical data exists (session logs, error logs)
|
||||
2. Data is representative of current/future work
|
||||
3. Metrics can be calculated from historical data
|
||||
4. Methodology can be applied retrospectively
|
||||
|
||||
**Example** (Bootstrap-003):
|
||||
```
|
||||
✅ 1,336 historical errors in session logs
|
||||
✅ Representative of typical development work
|
||||
✅ Can classify errors retrospectively
|
||||
✅ Can measure prevention rate via replay
|
||||
|
||||
Result: Direct validation, 0 overhead
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Criterion 4: Generic Agent Sufficiency 🟡 MODERATE
|
||||
|
||||
### Definition
|
||||
|
||||
Generic agents (data-analyst, doc-writer, coder) sufficient for execution.
|
||||
|
||||
### Specialization Overhead
|
||||
|
||||
**Generic agents**: 0 overhead (use as-is)
|
||||
**Specialized agents**: +1 to +2 iterations for design + testing
|
||||
|
||||
### When Specialization Adds Value
|
||||
|
||||
**10x+ speedup opportunity**:
|
||||
- Example: coverage-analyzer (15 min → 30 sec = 30x)
|
||||
- Example: test-generator (10 min → 1 min = 10x)
|
||||
- Worth 1-2 iteration investment
|
||||
|
||||
**<5x speedup**:
|
||||
- Use generic agents + simple scripts
|
||||
- Not worth specialization overhead
|
||||
|
||||
### Examples
|
||||
|
||||
**✅ Generic Sufficient (Bootstrap-003)**:
|
||||
```
|
||||
Tasks:
|
||||
- Analyze errors (generic data-analyst)
|
||||
- Document taxonomy (generic doc-writer)
|
||||
- Create validation scripts (generic coder)
|
||||
|
||||
Speedup from specialization: 2-3x (not worth it)
|
||||
Result: 0 specialization overhead
|
||||
```
|
||||
|
||||
**⚠️ Specialization Needed (Bootstrap-002)**:
|
||||
```
|
||||
Tasks:
|
||||
- Coverage analysis (15 min → 30 sec = 30x with coverage-analyzer)
|
||||
- Test generation (10 min → 1 min = 10x with test-generator)
|
||||
|
||||
Speedup: >10x for both
|
||||
Investment: 1 iteration to design and test agents
|
||||
Result: +1 iteration, but ROI positive overall
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Criterion 5: Early High-Impact Automation 🟡 MODERATE
|
||||
|
||||
### Definition
|
||||
|
||||
Top 3 automation opportunities identified by iteration 1.
|
||||
|
||||
### Pareto Principle Application
|
||||
|
||||
**80/20 rule**: 20% of automations provide 80% of value
|
||||
|
||||
**Implication**: Identify top 3 early → rapid V_instance improvement
|
||||
|
||||
### Identification Signals
|
||||
|
||||
**High-frequency patterns**:
|
||||
- Appears in >10% of cases
|
||||
- Example: File-not-found (18.7% of errors)
|
||||
|
||||
**High-impact prevention**:
|
||||
- Prevents >50% of pattern occurrences
|
||||
- Example: validate-path.sh prevents 65.2%
|
||||
|
||||
**High ROI**:
|
||||
- Time saved / time invested > 5x
|
||||
- Example: validate-path.sh = 61x ROI
|
||||
|
||||
### Early Identification Techniques
|
||||
|
||||
**Frequency Analysis**:
|
||||
```bash
|
||||
# Count error types
|
||||
cat errors.jsonl | jq -r '.error_type' | sort | uniq -c | sort -rn
|
||||
|
||||
# Top 3 = high-frequency candidates
|
||||
```
|
||||
|
||||
**Impact Estimation**:
|
||||
```
|
||||
If tool prevents X% of pattern Y:
|
||||
- Pattern Y occurs N times
|
||||
- Prevention: X% × N
|
||||
- Impact: (X% × N) / total_errors
|
||||
```
|
||||
|
||||
**ROI Calculation**:
|
||||
```
|
||||
Manual time: M min per occurrence
|
||||
Tool investment: T hours
|
||||
Expected uses: N
|
||||
|
||||
ROI = (M × N) / (T × 60)
|
||||
```
|
||||
|
||||
### Example (Bootstrap-003)
|
||||
|
||||
**Iteration 0 Analysis**:
|
||||
```
|
||||
Top 3 by frequency:
|
||||
1. File-not-found: 250/1,336 = 18.7%
|
||||
2. MCP errors: 228/1,336 = 17.1%
|
||||
3. Build errors: 200/1,336 = 15.0%
|
||||
|
||||
Automation feasibility:
|
||||
1. File-not-found: ✅ Path validation (high prevention %)
|
||||
2. MCP errors: ❌ Infrastructure (low automation value)
|
||||
3. Build errors: ⚠️ Language-specific (moderate value)
|
||||
|
||||
Selected:
|
||||
1. validate-path.sh: 250 errors, 65.2% prevention, 61x ROI
|
||||
2. check-file-size.sh: 84 errors, 100% prevention, 31.6x ROI
|
||||
3. check-read-before-write.sh: 70 errors, 100% prevention, 26.2x ROI
|
||||
|
||||
Total impact: 317/1,336 = 23.7% error prevention
|
||||
```
|
||||
|
||||
**Result**: Clear automation path from iteration 0
|
||||
|
||||
---
|
||||
|
||||
## Criteria Interaction Matrix
|
||||
|
||||
| Criterion 1 | Criterion 2 | Criterion 3 | Likely Iterations |
|
||||
|-------------|-------------|-------------|-------------------|
|
||||
| ✅ (≥0.40) | ✅ Focused | ✅ Direct | 3-4 ⚡ |
|
||||
| ✅ (≥0.40) | ✅ Focused | ❌ Multi | 4-5 |
|
||||
| ✅ (≥0.40) | ❌ Broad | ✅ Direct | 4-5 |
|
||||
| ❌ (<0.40) | ✅ Focused | ✅ Direct | 5-6 |
|
||||
| ❌ (<0.40) | ❌ Broad | ❌ Multi | 7-10 |
|
||||
|
||||
**Key Insight**: Criteria 1-3 are multiplicative. Missing any = slower convergence.
|
||||
|
||||
---
|
||||
|
||||
## Decision Tree
|
||||
|
||||
```
|
||||
Start
|
||||
│
|
||||
├─ Can you achieve V_meta(s₀) ≥ 0.40?
|
||||
│ YES → Continue
|
||||
│ NO → Standard convergence (5-7 iterations)
|
||||
│
|
||||
├─ Is domain scope <3 sentences?
|
||||
│ YES → Continue
|
||||
│ NO → Refine scope first
|
||||
│
|
||||
├─ Can you validate without multi-context?
|
||||
│ YES → Rapid convergence likely (3-4 iterations)
|
||||
│ NO → Add +2 iterations for validation
|
||||
│
|
||||
└─ Generic agents sufficient?
|
||||
YES → No overhead
|
||||
NO → Add +1 iteration for specialization
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
**Source**: BAIME Rapid Convergence Criteria
|
||||
**Validation**: 13 experiments, 85% prediction accuracy
|
||||
**Critical Path**: Criteria 1-3 (must all be met for rapid convergence)
|
||||
329
skills/rapid-convergence/reference/prediction-model.md
Normal file
329
skills/rapid-convergence/reference/prediction-model.md
Normal file
@@ -0,0 +1,329 @@
|
||||
# Convergence Speed Prediction Model
|
||||
|
||||
**Purpose**: Predict iteration count before starting experiment
|
||||
**Accuracy**: 85% (±1 iteration) across 13 experiments
|
||||
|
||||
---
|
||||
|
||||
## Formula
|
||||
|
||||
```
|
||||
Predicted_Iterations = Base(4) + Σ penalties
|
||||
|
||||
Penalties:
|
||||
1. V_meta(s₀) < 0.40: +2
|
||||
2. Domain scope fuzzy: +1
|
||||
3. Multi-context validation: +2
|
||||
4. Specialization needed: +1
|
||||
5. Automation unclear: +1
|
||||
```
|
||||
|
||||
**Range**: 4-11 iterations (min 4, max 4+2+1+2+1+1=11)
|
||||
|
||||
---
|
||||
|
||||
## Penalty Definitions
|
||||
|
||||
### Penalty 1: Low Baseline (+2 iterations)
|
||||
|
||||
**Condition**: V_meta(s₀) < 0.40
|
||||
|
||||
**Rationale**: More gap to close (0.40+ needed to reach 0.80)
|
||||
|
||||
**Check**:
|
||||
```bash
|
||||
# Calculate V_meta(s₀) from iteration 0
|
||||
completeness=$(calculate_initial_coverage)
|
||||
transferability=$(calculate_borrowed_patterns)
|
||||
automation=$(calculate_identified_tools)
|
||||
|
||||
v_meta=$(echo "0.4*$completeness + 0.3*$transferability + 0.3*$automation" | bc)
|
||||
|
||||
if (( $(echo "$v_meta < 0.40" | bc -l) )); then
|
||||
penalty=2
|
||||
fi
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Penalty 2: Fuzzy Scope (+1 iteration)
|
||||
|
||||
**Condition**: Cannot describe domain in <3 clear sentences
|
||||
|
||||
**Rationale**: Requires scoping work, adds exploration
|
||||
|
||||
**Check**:
|
||||
- Write domain definition
|
||||
- Count sentences
|
||||
- Ask: Are boundaries clear?
|
||||
|
||||
**Example**:
|
||||
```
|
||||
✅ Clear: "Error detection, diagnosis, recovery, prevention for meta-cc"
|
||||
❌ Fuzzy: "Improve testing" (which tests? what aspects? how much?)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Penalty 3: Multi-Context Validation (+2 iterations)
|
||||
|
||||
**Condition**: Requires testing across multiple projects/languages
|
||||
|
||||
**Rationale**: Deployment + validation overhead
|
||||
|
||||
**Check**:
|
||||
- Is retrospective validation possible? (NO penalty)
|
||||
- Single-context sufficient? (NO penalty)
|
||||
- Need 2+ contexts? (+2 penalty)
|
||||
|
||||
---
|
||||
|
||||
### Penalty 4: Specialization Needed (+1 iteration)
|
||||
|
||||
**Condition**: Generic agents insufficient, need specialized agents
|
||||
|
||||
**Rationale**: Agent design + testing adds iteration
|
||||
|
||||
**Check**:
|
||||
- Can generic agents handle all tasks? (NO penalty)
|
||||
- Need >10x speedup from specialist? (+1 penalty)
|
||||
|
||||
---
|
||||
|
||||
### Penalty 5: Automation Unclear (+1 iteration)
|
||||
|
||||
**Condition**: Top 3 automations not obvious by iteration 0
|
||||
|
||||
**Rationale**: Requires discovery phase
|
||||
|
||||
**Check**:
|
||||
- Frequency analysis reveals clear candidates? (NO penalty)
|
||||
- Need exploration to find automations? (+1 penalty)
|
||||
|
||||
---
|
||||
|
||||
## Worked Examples
|
||||
|
||||
### Example 1: Bootstrap-003 (Error Recovery)
|
||||
|
||||
**Assessment**:
|
||||
```
|
||||
Base: 4
|
||||
|
||||
1. V_meta(s₀) = 0.48 ≥ 0.40? YES → +0 ✅
|
||||
2. Domain scope clear? YES ("Error detection, diagnosis...") → +0 ✅
|
||||
3. Retrospective validation? YES (1,336 historical errors) → +0 ✅
|
||||
4. Generic agents sufficient? YES → +0 ✅
|
||||
5. Automation clear? YES (top 3 from frequency analysis) → +0 ✅
|
||||
|
||||
Predicted: 4 + 0 = 4 iterations
|
||||
Actual: 3 iterations ✅ (within ±1)
|
||||
```
|
||||
|
||||
**Analysis**: All criteria met → minimal penalties → rapid convergence
|
||||
|
||||
---
|
||||
|
||||
### Example 2: Bootstrap-002 (Test Strategy)
|
||||
|
||||
**Assessment**:
|
||||
```
|
||||
Base: 4
|
||||
|
||||
1. V_meta(s₀) = 0.04 < 0.40? NO → +2 ❌
|
||||
2. Domain scope clear? NO (testing is broad) → +1 ❌
|
||||
3. Multi-context validation? YES (3 archetypes) → +2 ❌
|
||||
4. Specialization needed? YES (coverage-analyzer, test-gen) → +1 ❌
|
||||
5. Automation clear? YES (coverage tools obvious) → +0 ✅
|
||||
|
||||
Predicted: 4 + 2 + 1 + 2 + 1 + 0 = 10 iterations
|
||||
Actual: 6 iterations ✅ (model conservative)
|
||||
```
|
||||
|
||||
**Analysis**: Model predicts upper bound. Efficient execution beat estimate.
|
||||
|
||||
---
|
||||
|
||||
### Example 3: Hypothetical CI/CD Optimization
|
||||
|
||||
**Assessment**:
|
||||
```
|
||||
Base: 4
|
||||
|
||||
1. V_meta(s₀) = ?
|
||||
- Historical CI logs exist: YES
|
||||
- Initial analysis: 5 pipeline patterns identified
|
||||
- Estimated final: 7 patterns
|
||||
- Completeness: 5/7 = 0.71
|
||||
- Transferability: 0.40 (industry practices)
|
||||
- Automation: 0.67 (2/3 tools identified)
|
||||
- V_meta(s₀) = 0.4×0.71 + 0.3×0.40 + 0.3×0.67 = 0.49 ≥ 0.40 → +0 ✅
|
||||
|
||||
2. Domain scope: "Reduce CI/CD build time through caching, parallelization, optimization"
|
||||
- Clear? YES → +0 ✅
|
||||
|
||||
3. Validation: Single CI pipeline (own project)
|
||||
- Single-context? YES → +0 ✅
|
||||
|
||||
4. Specialization: Pipeline analysis can use generic bash/jq
|
||||
- Sufficient? YES → +0 ✅
|
||||
|
||||
5. Automation: Top 3 = caching, parallelization, fast-fail
|
||||
- Clear? YES → +0 ✅
|
||||
|
||||
Predicted: 4 + 0 = 4 iterations
|
||||
Expected actual: 3-5 iterations (rapid convergence)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Calibration Data
|
||||
|
||||
**13 Experiments, Actual vs Predicted**:
|
||||
|
||||
| Experiment | Predicted | Actual | Δ | Accurate? |
|
||||
|------------|-----------|--------|---|-----------|
|
||||
| Bootstrap-003 | 4 | 3 | -1 | ✅ |
|
||||
| Bootstrap-007 | 4 | 5 | +1 | ✅ |
|
||||
| Bootstrap-005 | 5 | 5 | 0 | ✅ |
|
||||
| Bootstrap-002 | 10 | 6 | -4 | ⚠️ |
|
||||
| Bootstrap-009 | 6 | 7 | +1 | ✅ |
|
||||
| Bootstrap-011 | 7 | 6 | -1 | ✅ |
|
||||
| ... | ... | ... | ... | ... |
|
||||
|
||||
**Accuracy**: 11/13 = 85% within ±1 iteration
|
||||
|
||||
**Model Bias**: Slightly conservative (over-predicts by avg 0.7 iterations)
|
||||
|
||||
---
|
||||
|
||||
## Usage Guide
|
||||
|
||||
### Step 1: Assess Domain (15 min)
|
||||
|
||||
**Tasks**:
|
||||
1. Analyze available data
|
||||
2. Research prior art
|
||||
3. Identify automation candidates
|
||||
4. Calculate V_meta(s₀)
|
||||
|
||||
**Output**: V_meta(s₀) value
|
||||
|
||||
---
|
||||
|
||||
### Step 2: Evaluate Penalties (10 min)
|
||||
|
||||
**Checklist**:
|
||||
- [ ] V_meta(s₀) ≥ 0.40? (NO → +2)
|
||||
- [ ] Domain <3 clear sentences? (NO → +1)
|
||||
- [ ] Direct/retrospective validation? (NO → +2)
|
||||
- [ ] Generic agents sufficient? (NO → +1)
|
||||
- [ ] Top 3 automations clear? (NO → +1)
|
||||
|
||||
**Output**: Total penalty sum
|
||||
|
||||
---
|
||||
|
||||
### Step 3: Calculate Prediction
|
||||
|
||||
```
|
||||
Predicted = 4 + penalty_sum
|
||||
|
||||
Examples:
|
||||
- 0 penalties → 4 iterations (rapid)
|
||||
- 2-3 penalties → 6-7 iterations (standard)
|
||||
- 5+ penalties → 9-11 iterations (exploratory)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
### Step 4: Plan Experiment
|
||||
|
||||
**Rapid (4-5 iterations predicted)**:
|
||||
- Strong iteration 0: 3-5 hours
|
||||
- Aggressive iteration 1: Fix all P1 issues
|
||||
- Target: 10-15 hours total
|
||||
|
||||
**Standard (6-8 iterations predicted)**:
|
||||
- Normal iteration 0: 1-2 hours
|
||||
- Incremental improvements
|
||||
- Target: 20-30 hours total
|
||||
|
||||
**Exploratory (9+ iterations predicted)**:
|
||||
- Minimal iteration 0: <1 hour
|
||||
- Discovery-driven
|
||||
- Target: 30-50 hours total
|
||||
|
||||
---
|
||||
|
||||
## Prediction Confidence
|
||||
|
||||
**High Confidence** (0-2 penalties):
|
||||
- Predicted ±1 iteration
|
||||
- 90% accuracy
|
||||
|
||||
**Medium Confidence** (3-4 penalties):
|
||||
- Predicted ±2 iterations
|
||||
- 75% accuracy
|
||||
|
||||
**Low Confidence** (5+ penalties):
|
||||
- Predicted ±3 iterations
|
||||
- 60% accuracy
|
||||
|
||||
**Reason**: More penalties = more unknowns = higher variance
|
||||
|
||||
---
|
||||
|
||||
## Model Limitations
|
||||
|
||||
### 1. Assumes Competent Execution
|
||||
|
||||
**Model assumes**:
|
||||
- Comprehensive iteration 0 (if V_meta(s₀) ≥ 0.40)
|
||||
- Efficient iteration execution
|
||||
- No major blockers
|
||||
|
||||
**Reality**: Execution quality varies
|
||||
|
||||
---
|
||||
|
||||
### 2. Conservative Bias
|
||||
|
||||
**Model tends to over-predict** (actual < predicted)
|
||||
|
||||
**Reason**: Penalties are additive, but some synergies exist
|
||||
|
||||
**Example**: Bootstrap-002 predicted 10, actual 6 (efficient work offset penalties)
|
||||
|
||||
---
|
||||
|
||||
### 3. Domain-Specific Factors
|
||||
|
||||
**Not captured**:
|
||||
- Developer experience
|
||||
- Tool ecosystem maturity
|
||||
- Team collaboration
|
||||
- Unforeseen blockers
|
||||
|
||||
**Recommendation**: Use as guideline, not guarantee
|
||||
|
||||
---
|
||||
|
||||
## Decision Support
|
||||
|
||||
### Use Prediction to Decide:
|
||||
|
||||
**4-5 iterations predicted**:
|
||||
→ Invest in strong iteration 0 (rapid convergence worth it)
|
||||
|
||||
**6-8 iterations predicted**:
|
||||
→ Standard approach (diminishing returns from heavy baseline)
|
||||
|
||||
**9+ iterations predicted**:
|
||||
→ Exploratory mode (discovery-first, optimize later)
|
||||
|
||||
---
|
||||
|
||||
**Source**: BAIME Rapid Convergence Prediction Model
|
||||
**Validation**: 13 experiments, 85% accuracy (±1 iteration)
|
||||
**Usage**: Planning tool for experiment design
|
||||
426
skills/rapid-convergence/reference/strategy.md
Normal file
426
skills/rapid-convergence/reference/strategy.md
Normal file
@@ -0,0 +1,426 @@
|
||||
# Rapid Convergence Strategy Guide
|
||||
|
||||
**Purpose**: Iteration-by-iteration tactics for 3-4 iteration convergence
|
||||
**Time**: 10-15 hours total (vs 20-30 standard)
|
||||
|
||||
---
|
||||
|
||||
## Pre-Iteration 0: Planning (1-2 hours)
|
||||
|
||||
### Objectives
|
||||
|
||||
1. Confirm rapid convergence feasible
|
||||
2. Establish measurement infrastructure
|
||||
3. Define scope boundaries
|
||||
4. Plan validation approach
|
||||
|
||||
### Tasks
|
||||
|
||||
**1. Baseline Assessment** (30 min):
|
||||
```bash
|
||||
# Query existing data
|
||||
meta-cc query-tools --status=error
|
||||
meta-cc query-user-messages --pattern="test|coverage"
|
||||
|
||||
# Calculate baseline metrics
|
||||
# Estimate V_meta(s₀)
|
||||
```
|
||||
|
||||
**2. Scope Definition** (20 min):
|
||||
```markdown
|
||||
## Domain: [1-sentence definition]
|
||||
|
||||
**In-Scope**: [3-5 items]
|
||||
**Out-of-Scope**: [3-5 items]
|
||||
**Edge Cases**: [Handling approach]
|
||||
```
|
||||
|
||||
**3. Success Criteria** (20 min):
|
||||
```markdown
|
||||
## Convergence Targets
|
||||
|
||||
**V_instance ≥ 0.80**:
|
||||
- Metric 1: [Target]
|
||||
- Metric 2: [Target]
|
||||
|
||||
**V_meta ≥ 0.80**:
|
||||
- Patterns: [8-10 documented]
|
||||
- Tools: [3-5 created]
|
||||
- Transferability: [≥80%]
|
||||
```
|
||||
|
||||
**4. Prediction** (10 min):
|
||||
```
|
||||
Use prediction model:
|
||||
Base(4) + penalties = [X] iterations expected
|
||||
```
|
||||
|
||||
**Deliverable**: `README.md` with scope, targets, prediction
|
||||
|
||||
---
|
||||
|
||||
## Iteration 0: Comprehensive Baseline (3-5 hours)
|
||||
|
||||
### Objectives
|
||||
|
||||
- Achieve V_meta(s₀) ≥ 0.40
|
||||
- Initial taxonomy: 70-80% coverage
|
||||
- Identify top 3 automations
|
||||
|
||||
### Time Allocation
|
||||
|
||||
- Data analysis: 60-90 min (40%)
|
||||
- Taxonomy creation: 45-75 min (30%)
|
||||
- Pattern research: 30-45 min (20%)
|
||||
- Automation planning: 15-30 min (10%)
|
||||
|
||||
### Tasks
|
||||
|
||||
**1. Comprehensive Data Analysis** (60-90 min):
|
||||
```bash
|
||||
# Extract ALL available data
|
||||
meta-cc query-tools --scope=project > tools.jsonl
|
||||
meta-cc query-user-messages --pattern=".*" > messages.jsonl
|
||||
|
||||
# Analyze patterns
|
||||
cat tools.jsonl | jq -r '.error' | sort | uniq -c | sort -rn | head -20
|
||||
|
||||
# Calculate frequencies
|
||||
total=$(cat tools.jsonl | wc -l)
|
||||
# For each pattern: count / total
|
||||
```
|
||||
|
||||
**2. Initial Taxonomy** (45-75 min):
|
||||
```markdown
|
||||
## Taxonomy v0
|
||||
|
||||
### Category 1: [Name] ([frequency]%, [count])
|
||||
**Pattern**: [Description]
|
||||
**Examples**: [3-5 examples]
|
||||
**Root Cause**: [Analysis]
|
||||
|
||||
### Category 2: ...
|
||||
[Repeat for 10-15 categories]
|
||||
|
||||
**Coverage**: [X]% ([classified]/[total])
|
||||
```
|
||||
|
||||
**3. Pattern Research** (30-45 min):
|
||||
```markdown
|
||||
## Prior Art
|
||||
|
||||
**Source 1**: [Industry taxonomy/framework]
|
||||
- Borrowed: [Pattern A, Pattern B, ...]
|
||||
- Transferability: [X]%
|
||||
|
||||
**Source 2**: [Similar project]
|
||||
- Borrowed: [Pattern C, Pattern D, ...]
|
||||
- Adaptations needed: [List]
|
||||
|
||||
**Total Borrowable**: [X]/[Y] patterns = [Z]%
|
||||
```
|
||||
|
||||
**4. Automation Planning** (15-30 min):
|
||||
```markdown
|
||||
## Top Automation Candidates
|
||||
|
||||
**1. [Tool Name]**
|
||||
- Frequency: [X]% of cases
|
||||
- Prevention: [Y]% of pattern
|
||||
- ROI estimate: [Z]x
|
||||
- Feasibility: [High/Medium/Low]
|
||||
|
||||
**2. [Tool Name]**
|
||||
[Same structure]
|
||||
|
||||
**3. [Tool Name]**
|
||||
[Same structure]
|
||||
```
|
||||
|
||||
### Metrics
|
||||
|
||||
Calculate V_meta(s₀):
|
||||
```
|
||||
Completeness: [initial_categories] / [estimated_final] = [X]
|
||||
Transferability: [borrowed] / [total_needed] = [Y]
|
||||
Automation: [identified] / [expected] = [Z]
|
||||
|
||||
V_meta(s₀) = 0.4×[X] + 0.3×[Y] + 0.3×[Z] = [RESULT]
|
||||
|
||||
Target: ≥ 0.40 ✅/❌
|
||||
```
|
||||
|
||||
**Deliverables**:
|
||||
- `taxonomy-v0.md` (10-15 categories, ≥70% coverage)
|
||||
- `baseline-metrics.md` (V_meta(s₀), frequencies)
|
||||
- `automation-plan.md` (top 3 tools, ROI estimates)
|
||||
|
||||
---
|
||||
|
||||
## Iteration 1: High-Impact Automation (3-4 hours)
|
||||
|
||||
### Objectives
|
||||
|
||||
- V_instance ≥ 0.60 (significant improvement)
|
||||
- Implement top 2-3 tools
|
||||
- Expand taxonomy to 90%+ coverage
|
||||
|
||||
### Time Allocation
|
||||
|
||||
- Tool implementation: 90-120 min (50%)
|
||||
- Taxonomy expansion: 45-60 min (25%)
|
||||
- Testing & validation: 45-60 min (25%)
|
||||
|
||||
### Tasks
|
||||
|
||||
**1. Build Automation Tools** (90-120 min):
|
||||
```bash
|
||||
# Tool 1: validate-path.sh (30-40 min)
|
||||
#!/bin/bash
|
||||
# Fuzzy path matching, typo correction
|
||||
# Target: 150-200 LOC
|
||||
|
||||
# Tool 2: check-file-size.sh (20-30 min)
|
||||
#!/bin/bash
|
||||
# File size check, auto-pagination
|
||||
# Target: 100-150 LOC
|
||||
|
||||
# Tool 3: check-read-before-write.sh (40-50 min)
|
||||
#!/bin/bash
|
||||
# Workflow validation
|
||||
# Target: 150-200 LOC
|
||||
```
|
||||
|
||||
**2. Expand Taxonomy** (45-60 min):
|
||||
```markdown
|
||||
## Taxonomy v1
|
||||
|
||||
### [New Category 11]: [Name]
|
||||
[Analysis of remaining 10-20% of cases]
|
||||
|
||||
### [New Category 12]: [Name]
|
||||
[Continue until ≥90% coverage]
|
||||
|
||||
**Coverage**: [X]% ([classified]/[total])
|
||||
**Gap Analysis**: [Remaining uncategorized patterns]
|
||||
```
|
||||
|
||||
**3. Test & Measure** (45-60 min):
|
||||
```bash
|
||||
# Test tools on historical data
|
||||
./scripts/validate-path.sh "path/to/file" # Expect suggestions
|
||||
./scripts/check-file-size.sh "large-file.json" # Expect warning
|
||||
|
||||
# Calculate impact
|
||||
prevented=$(estimate_prevention_rate)
|
||||
time_saved=$(calculate_time_savings)
|
||||
roi=$(calculate_roi)
|
||||
|
||||
# Update metrics
|
||||
```
|
||||
|
||||
### Metrics
|
||||
|
||||
```
|
||||
V_instance calculation:
|
||||
- Success rate: [X]%
|
||||
- Quality: [Y]/5
|
||||
- Efficiency: [Z] min/task
|
||||
|
||||
V_instance = 0.4×[success] + 0.3×[quality/5] + 0.2×[efficiency] + 0.1×[reliability]
|
||||
= [RESULT]
|
||||
|
||||
Target: ≥ 0.60 (progress toward 0.80)
|
||||
```
|
||||
|
||||
**Deliverables**:
|
||||
- `scripts/tool1.sh`, `scripts/tool2.sh`, `scripts/tool3.sh`
|
||||
- `taxonomy-v1.md` (≥90% coverage)
|
||||
- `iteration-1-results.md` (V_instance, V_meta, gaps)
|
||||
|
||||
---
|
||||
|
||||
## Iteration 2: Validation & Refinement (3-4 hours)
|
||||
|
||||
### Objectives
|
||||
|
||||
- V_instance ≥ 0.80 ✅
|
||||
- V_meta ≥ 0.80 ✅
|
||||
- Validate stability (2 consecutive iterations)
|
||||
|
||||
### Time Allocation
|
||||
|
||||
- Retrospective validation: 60-90 min (40%)
|
||||
- Taxonomy completion: 30-45 min (20%)
|
||||
- Tool refinement: 45-60 min (25%)
|
||||
- Documentation: 30-45 min (15%)
|
||||
|
||||
### Tasks
|
||||
|
||||
**1. Retrospective Validation** (60-90 min):
|
||||
```bash
|
||||
# Apply methodology to historical data
|
||||
meta-cc validate \
|
||||
--methodology error-recovery \
|
||||
--history .claude/sessions/*.jsonl
|
||||
|
||||
# Measure:
|
||||
# - Coverage: [X]% of historical cases handled
|
||||
# - Time savings: [Y] hours saved
|
||||
# - Prevention: [Z]% errors prevented
|
||||
# - Confidence: [Score]
|
||||
```
|
||||
|
||||
**2. Complete Taxonomy** (30-45 min):
|
||||
```markdown
|
||||
## Taxonomy v2 (Final)
|
||||
|
||||
[Review all categories]
|
||||
[Add final 1-2 categories if needed]
|
||||
[Refine existing categories]
|
||||
|
||||
**Final Coverage**: [X]% ≥ 95% ✅
|
||||
**Uncategorized**: [Y]% (acceptable edge cases)
|
||||
```
|
||||
|
||||
**3. Refine Tools** (45-60 min):
|
||||
```bash
|
||||
# Based on validation feedback
|
||||
# - Fix bugs discovered
|
||||
# - Improve accuracy
|
||||
# - Add edge case handling
|
||||
# - Optimize performance
|
||||
|
||||
# Re-test
|
||||
# Re-measure ROI
|
||||
```
|
||||
|
||||
**4. Documentation** (30-45 min):
|
||||
```markdown
|
||||
## Complete Methodology
|
||||
|
||||
### Patterns: [8-10 documented]
|
||||
### Tools: [3-5 with usage]
|
||||
### Transferability: [≥80%]
|
||||
### Validation: [Results]
|
||||
```
|
||||
|
||||
### Metrics
|
||||
|
||||
```
|
||||
V_instance: [X] (≥0.80? ✅/❌)
|
||||
V_meta: [Y] (≥0.80? ✅/❌)
|
||||
|
||||
Stability check:
|
||||
- Iteration 1: V_instance = [A]
|
||||
- Iteration 2: V_instance = [B]
|
||||
- Change: [|B-A|] < 0.05? ✅/❌
|
||||
|
||||
Convergence: ✅/❌
|
||||
```
|
||||
|
||||
**Decision**:
|
||||
- ✅ Converged → Deploy
|
||||
- ❌ Not converged → Iteration 3 (gap analysis)
|
||||
|
||||
**Deliverables**:
|
||||
- `validation-report.md` (confidence, coverage, ROI)
|
||||
- `methodology-complete.md` (production-ready)
|
||||
- `transferability-guide.md` (80%+ reuse documentation)
|
||||
|
||||
---
|
||||
|
||||
## Iteration 3 (If Needed): Gap Closure (2-3 hours)
|
||||
|
||||
### Objectives
|
||||
|
||||
- Close specific gaps preventing convergence
|
||||
- Reach dual-layer convergence (V_instance ≥ 0.80, V_meta ≥ 0.80)
|
||||
|
||||
### Gap Analysis
|
||||
|
||||
```markdown
|
||||
## Why Not Converged?
|
||||
|
||||
**V_instance gaps** ([X] < 0.80):
|
||||
- Metric A: [current] vs [target] = gap [Z]
|
||||
- Root cause: [Analysis]
|
||||
- Fix: [Action]
|
||||
|
||||
**V_meta gaps** ([Y] < 0.80):
|
||||
- Component: [completeness/transferability/automation]
|
||||
- Current: [X]
|
||||
- Target: [Y]
|
||||
- Fix: [Action]
|
||||
```
|
||||
|
||||
### Focused Improvements
|
||||
|
||||
**Time**: 2-3 hours (targeted, not comprehensive)
|
||||
|
||||
**Tasks**:
|
||||
- Address 1-2 major gaps only
|
||||
- Refine existing work (no new patterns)
|
||||
- Validate fixes
|
||||
|
||||
**Re-measure**:
|
||||
```
|
||||
V_instance: [X] ≥ 0.80? ✅/❌
|
||||
V_meta: [Y] ≥ 0.80? ✅/❌
|
||||
Stable for 2 iterations? ✅/❌
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Timeline Summary
|
||||
|
||||
### Rapid Convergence (3 iterations)
|
||||
|
||||
```
|
||||
Pre-Iteration 0: 1-2h
|
||||
Iteration 0: 3-5h (comprehensive baseline)
|
||||
Iteration 1: 3-4h (automation + expansion)
|
||||
Iteration 2: 3-4h (validation + convergence)
|
||||
---
|
||||
Total: 10-15h ✅
|
||||
```
|
||||
|
||||
### Standard (If Iteration 3 Needed)
|
||||
|
||||
```
|
||||
Pre-Iteration 0: 1-2h
|
||||
Iteration 0: 3-5h
|
||||
Iteration 1: 3-4h
|
||||
Iteration 2: 3-4h
|
||||
Iteration 3: 2-3h (gap closure)
|
||||
---
|
||||
Total: 12-18h (still faster than standard 20-30h)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Anti-Patterns
|
||||
|
||||
### ❌ Rushing Iteration 0
|
||||
|
||||
**Symptom**: Spending 1-2 hours (vs 3-5)
|
||||
**Impact**: Low V_meta(s₀), requires more iterations
|
||||
**Fix**: Invest 3-5 hours for comprehensive baseline
|
||||
|
||||
### ❌ Over-Engineering Tools
|
||||
|
||||
**Symptom**: Spending 4+ hours per tool
|
||||
**Impact**: Delays convergence
|
||||
**Fix**: Simple tools (150-200 LOC, 30-60 min each)
|
||||
|
||||
### ❌ Premature Convergence
|
||||
|
||||
**Symptom**: Declaring done at V = 0.75
|
||||
**Impact**: Quality issues in production
|
||||
**Fix**: Respect 0.80 threshold, ensure 2-iteration stability
|
||||
|
||||
---
|
||||
|
||||
**Source**: BAIME Rapid Convergence Strategy
|
||||
**Validation**: Bootstrap-003 (3 iterations, 10 hours)
|
||||
**Success Rate**: 85% (11/13 experiments)
|
||||
Reference in New Issue
Block a user