Overview

/evolve-mycelialize is a production command in the Evolution category of the Prismatic Platform. It provides unified evolution-propagation cycles that integrate the capabilities of /evolve and /mycelialize into a single cohesive operation. Where /evolve focuses on generational fitness improvement and /mycelialize handles biological-inspired pattern propagation, /evolve-mycelialize fuses both capabilities to simultaneously evolve the platform while propagating successful patterns across the entire ecosystem.

The biological metaphor underlying this command is instructive. In natural ecosystems, evolution and mycelial networks are deeply interconnected -- fungal mycelium networks facilitate nutrient transfer and communication between organisms, accelerating evolutionary adaptation across the ecosystem. The /evolve-mycelialize command replicates this synergy in the software domain: evolution generates beneficial mutations (quality improvements, pattern discoveries, architectural refinements), while the mycelial propagation network distributes these improvements across all 100+ umbrella applications simultaneously.

This fusion is not merely a sequential composition of two commands. The evolution-mycelial-fusion-commander agent implements a co-evolutionary protocol where evolution and propagation inform each other in real time. Patterns that propagate successfully across many applications receive higher fitness scores, biasing future evolution toward patterns with proven cross-application applicability. Conversely, evolution cycles that discover novel patterns immediately feed the mycelial network for rapid ecosystem-wide distribution.

This command operates under the SUPREME authority level, the highest non-self-recursive authority in the platform hierarchy. SUPREME authority is required because unified evolution-propagation cycles modify code across the entire umbrella ecosystem simultaneously. It is part of the platform's 216-command slash command registry, built on the AIAD (Autonomous Intelligence Agent Design) standard.

Architecture

The evolve-mycelialize system implements a co-evolutionary feedback loop between the evolution engine and mycelial network:

                    ┌─────────────────────────────────────────┐
                    │         Co-Evolution Controller          │
                    └───────────┬───────────────┬─────────────┘
                                │               │
                    ┌───────────▼───────┐ ┌─────▼───────────┐
                    │  Evolution Engine  │ │ Mycelial Network │
                    │  (5-Phase Cycle)   │ │ (Propagation)    │
                    └───────┬───────────┘ └─────┬───────────┘
                            │                   │
                    ┌───────▼───────┐   ┌───────▼───────┐
                    │ Fitness Eval  │   │ Pattern Router │
                    │ (per domain)  │   │ (500K/sec)     │
                    └───────┬───────┘   └───────┬───────┘
                            │                   │
                    ┌───────▼───────────────────▼───────┐
                    │    Feedback Synthesizer            │
                    │  (propagation success → fitness)   │
                    └───────────────────────────────────┘

Co-Evolution Controller: Orchestrates the synchronized execution of evolution and propagation cycles. The controller manages timing, conflict resolution, and resource allocation between the two subsystems. It ensures that evolution mutations do not conflict with propagation targets and vice versa.

Evolution Engine: The standard 5-phase evolution pipeline (scanning, analysis, mutation, selection, validation) with additional feedback input from propagation results. Successfully propagated patterns receive fitness bonuses, biasing future mutation strategies toward propagatable improvements.

Mycelial Network: The biological-inspired pattern propagation system operating at 500,000 patterns per second. The network routes patterns from source applications to target applications based on applicability scoring, structural compatibility, and dependency analysis.

Feedback Synthesizer: The critical bridge between evolution and propagation. This component transforms propagation success metrics (how many applications accepted a pattern, how much quality improved) into fitness adjustments for the evolution engine, creating a virtuous cycle of improvement.

Usage

Standard Unified Cycle

# Run unified evolve-mycelialize cycle
/evolve-mycelialize

# Run with specific evolution focus
/evolve-mycelialize --evolution-focus=quality --propagation-scope=all

# Run with propagation-first strategy
/evolve-mycelialize --strategy=propagation-first

Targeted Operations

# Focus on a specific application domain
/evolve-mycelialize --domain=storage --apps="prismatic_storage_*"

# Focus on a specific pattern type
/evolve-mycelialize --pattern-type=supervision-tree

# Run with emergence detection enabled
/evolve-mycelialize --detect-emergence --threshold=0.85

Monitoring and Analysis

# Show co-evolution status
/evolve-mycelialize --status

# Display propagation success rates
/evolve-mycelialize --propagation-stats

# Generate co-evolution report
/evolve-mycelialize --report --format=table --verbose

Options & Parameters

Option	Type	Default	Description
`--evolution-focus`	string	balanced	Evolution focus (quality, capability, architecture)
`--propagation-scope`	string	all	Propagation scope (all, domain, app-list)
`--strategy`	string	balanced	Execution strategy (balanced, evolution-first, propagation-first)
`--domain`	string	all	Target specific application domain
`--apps`	string	all	Comma-separated list of target applications
`--pattern-type`	string	all	Focus on specific pattern types
`--detect-emergence`	flag	false	Enable emergence detection for novel patterns
`--threshold`	float	0.80	Propagation success threshold for pattern acceptance
`--status`	flag	false	Display current co-evolution status
`--propagation-stats`	flag	false	Show detailed propagation statistics
`--report`	flag	false	Generate comprehensive co-evolution report
`--format`	string	text	Output format (text, json, table)
`--verbose`	flag	false	Include detailed metrics and diagnostics
`--max-iterations`	integer	10	Maximum co-evolution iterations per cycle
`--fitness-boost`	float	0.1	Fitness bonus for successfully propagated patterns

Execution Flow

The /evolve-mycelialize command follows a structured 7-phase co-evolutionary pipeline:

Ecosystem Snapshot: A point-in-time snapshot of the entire umbrella ecosystem is captured, including all application states, quality scores, active patterns, and dependency relationships. This snapshot serves as both the evolution baseline and propagation context.
Evolution Cycle: The standard 5-phase evolution cycle executes, producing a set of candidate mutations. Each mutation is annotated with its propagation potential -- an estimate of how many other applications could benefit from the same change.
Pattern Extraction: Successfully validated mutations are extracted as reusable patterns. Pattern extraction identifies the invariant structure of each mutation (the generalizable improvement) separate from its application-specific context.
Mycelial Propagation: Extracted patterns are fed into the mycelial network for cross-application distribution. The network evaluates each pattern against every target application using structural compatibility analysis, dependency checking, and quality impact prediction.
Propagation Validation: Each propagated pattern instance is validated in its target application context. Validation includes compilation checking, test execution, and quality gate verification. Failed propagations are rolled back without affecting the source application.
Feedback Synthesis: Propagation results (success rates, quality improvements, application coverage) are synthesized into fitness adjustments. Patterns that propagated successfully to many applications receive higher fitness scores, influencing future evolution strategy.
State Persistence: The final state -- evolution results, propagation outcomes, and fitness adjustments -- is persisted to Quality DNA for cross-session continuity.

Integration Points

Component	Integration Type	Description
Evolution Engine	Core	5-phase evolution cycle with fitness evaluation
Mycelial Network	Core	Pattern propagation at 500K patterns/sec
Quality DNA	Persistence	Cross-session state and fitness history
Quality Gates	Validation	Pre/post cycle quality verification
Prismatic Agents	Execution	Fusion commander agent orchestrates
Telemetry	Monitoring	Co-evolution metrics and propagation events
SEADF	Framework	Self-evolving framework integration
AIAD Registry	Discovery	Command specification and agent binding

Best Practices

Use balanced strategy for general improvement: The default balanced strategy alternates between evolution-focused and propagation-focused iterations, producing the most consistent cross-application improvement.

Enable emergence detection for novel systems: When working with new application domains or experimental features, enable --detect-emergence to identify novel patterns that emerge from the co-evolutionary process.

Set appropriate propagation thresholds: The default 0.80 threshold means patterns must succeed in 80% of target applications to be retained. Lower thresholds (0.60) for experimental propagation, higher (0.95) for production-critical domains.

Monitor feedback synthesis: The feedback loop between propagation success and evolution fitness is the most powerful -- and most sensitive -- aspect of the system. Use --verbose to monitor how propagation results influence subsequent evolution strategies.

Run after major cross-cutting changes: When architectural changes affect multiple applications, /evolve-mycelialize is more effective than running /evolve and /mycelialize independently, because the co-evolutionary feedback ensures consistency.

Error Handling

Error	Cause	Resolution
`CO_EVOLUTION_CONFLICT`	Evolution and propagation targeting the same code	Increase conflict resolution timeout or serialize operations
`PROPAGATION_THRESHOLD_NOT_MET`	Pattern success rate below configured threshold	Lower threshold or refine pattern for broader compatibility
`FEEDBACK_LOOP_DIVERGENCE`	Feedback synthesis producing unstable fitness adjustments	Reduce `--fitness-boost` value to dampen feedback
`ECOSYSTEM_SNAPSHOT_FAILED`	Cannot capture consistent ecosystem state	Ensure no other evolution cycles are running concurrently
`MYCELIAL_NETWORK_SATURATED`	Pattern volume exceeds network capacity	Reduce `--max-iterations` or narrow propagation scope

Advanced Usage

Custom Co-Evolution Strategies

# Define a custom strategy prioritizing security patterns
/evolve-mycelialize --custom-strategy="security-hardening" \
  --evolution-focus=security --pattern-type="input-validation,auth" \
  --propagation-scope=all --fitness-boost=0.2

# Multi-phase co-evolution with increasing scope
/evolve-mycelialize --phase=1 --propagation-scope=core-apps && \
/evolve-mycelialize --phase=2 --propagation-scope=all --inherit-patterns

Emergence Analysis

# Analyze emerged patterns from recent co-evolution cycles
/evolve-mycelialize --analyze-emergence --last=5 --verbose

# Export emerged patterns for manual review
/evolve-mycelialize --export-emergence --format=json

Integration with Formal Verification

The co-evolutionary pipeline can optionally route emerged patterns through the /mycelialize-formal formal verification pipeline, using Lean4 proofs to validate pattern correctness before ecosystem-wide propagation.

Doctrine Compliance

All commands operate under the NO MERCY, NO DOUBTS doctrine:

NO MERCY: Zero tolerance for degradation during co-evolution. Every propagated pattern must pass quality gates in every target application. Failed propagations are rolled back completely -- no partial application, no "good enough" compromises.
NO DOUBTS: Full investigation through the co-evolutionary feedback loop. Pattern effectiveness is measured empirically through propagation success rates. Fitness adjustments are evidence-based, not heuristic.

The SUPREME authority level reflects the scope of this command's impact. Unified evolution-propagation cycles modify code across the entire umbrella ecosystem. This level of authority requires commensurate validation rigor.

/evolve - Living AIAD ecosystem evolution with 5-phase cycle and GitLab observability
/mycelialize - Biological-inspired pattern propagation at 500K patterns/sec with emergence detection
/mycelialize-formal - Lean4 + Prolog formal verification for mathematically proven pattern propagation
/evolve-enforced - Evolution with mandatory QDP reduction
/evolve-patterns - Pattern evolution through meta-evolution analysis
/evolve-quality-gates - Quality gate evolution for warnings, tests and static analysis
/quality-gates - Enforce quality gate checkpoints with zero-warning compilation validation
/regression-check - Execute 25 custom Credo regression checks preventing 700+ violations

Connect & Contribute

Created by Tomáš Korcak (korczis) | Open Source under GHL

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/evolve-mycelialize