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Evolution Phases

The Evolution System progresses through five distinct phases, each building capabilities that enable the next.

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Phase 1: Instrumentation & Memory

Objective: Build the observational infrastructure to learn from every execution. Duration: 2-3 iterations

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Execution Telemetry

Every workflow execution captures: 
execution_record:
  # Identity
  execution_id: uuid
  request_fingerprint: hash(raw_input + audience + type)
  
  # Inputs
  raw_input: string
  input_complexity_score: float
  detected_intent_signals: string[]
  
  # Process
  drafts:
    - version: int
      quality_scores:
        technical_accuracy: float
        clarity_structure: float
        completeness: float
        audience_fit: float
        actionability: float
        overall: float
  
  # Outcomes
  final_quality_score: float
  iterations_required: int
  total_duration_seconds: int

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Corpus Database

Build a searchable corpus of all generated documents for pattern analysis.

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Phase 2: Pattern Recognition

Objective: Identify correlations between inputs, processes, and outcomes. Duration: 3-4 iterations

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Analysis Targets

  • What input characteristics predict high-quality outputs?
  • Which prompt variations produce better results?
  • What human edit patterns indicate systematic issues?

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Weekly Reports

Automated analysis producing actionable insights.

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Phase 3: Prompt Evolution

Objective: Iteratively improve prompts based on learned patterns. Duration: Ongoing

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Mechanisms

  1. A/B testing prompt variations
  2. Gradient-free optimization
  3. Human-in-the-loop refinement

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Safety Rails

  • Maximum deviation limits
  • Quality regression detection
  • Rollback capabilities

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Phase 4: Architecture Optimization

Objective: Optimize workflow structure and model selection. Duration: As needed

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Targets

  • Stage ordering optimization
  • Model routing improvements
  • Parallelization opportunities
  • Cost/quality tradeoffs

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Phase 5: Emergent Intelligence

Objective: Enable the system to discover novel documentation patterns. Duration: Long-term

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Characteristics

  • Self-directed exploration
  • Novel pattern discovery
  • Human-interpretable explanations
  • Value alignment verification

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Guardrails

  • Human oversight on all changes
  • Interpretability requirements
  • Alignment testing