# Intelligent Automation Framework ## Context-Aware and Adaptive Automation for Enhanced BMAD System The Intelligent Automation Framework provides sophisticated automation capabilities that can intelligently automate development tasks, workflows, and processes based on context, patterns, learned behaviors, and safety considerations. ### Automation Architecture #### Comprehensive Automation Framework ```yaml intelligent_automation_architecture: automation_levels: task_level_automation: - simple_task_automation: "Automate individual development tasks" - repetitive_operation_automation: "Automate repetitive operations" - data_processing_automation: "Automate data processing tasks" - file_management_automation: "Automate file operations and management" - code_formatting_automation: "Automate code formatting and styling" workflow_level_automation: - development_workflow_automation: "Automate development workflows" - testing_workflow_automation: "Automate testing and validation workflows" - deployment_workflow_automation: "Automate deployment and release workflows" - maintenance_workflow_automation: "Automate maintenance and monitoring workflows" - documentation_workflow_automation: "Automate documentation generation and updates" process_level_automation: - project_lifecycle_automation: "Automate project lifecycle management" - quality_assurance_automation: "Automate quality assurance processes" - continuous_integration_automation: "Automate CI/CD processes" - monitoring_alerting_automation: "Automate monitoring and alerting" - compliance_automation: "Automate compliance and governance" system_level_automation: - infrastructure_automation: "Automate infrastructure provisioning and management" - security_automation: "Automate security scanning and remediation" - performance_optimization_automation: "Automate performance optimization" - disaster_recovery_automation: "Automate backup and disaster recovery" - environment_management_automation: "Automate environment setup and teardown" automation_intelligence: context_awareness: - project_context_awareness: "Understand project context for automation decisions" - team_context_awareness: "Consider team preferences and practices" - environment_context_awareness: "Adapt automation to different environments" - temporal_context_awareness: "Consider timing and deadlines in automation" - domain_context_awareness: "Understand business domain for relevant automation" adaptive_automation: - feedback_based_adaptation: "Adapt automation based on user feedback" - performance_based_adaptation: "Adapt automation based on performance metrics" - pattern_based_adaptation: "Adapt automation based on identified patterns" - context_based_adaptation: "Adapt automation based on changing context" - learning_based_adaptation: "Adapt automation based on accumulated learning" decision_intelligence: - automation_candidate_identification: "Identify tasks suitable for automation" - automation_priority_determination: "Prioritize automation opportunities" - automation_approach_selection: "Select optimal automation approaches" - risk_assessment_integration: "Assess risks before automation" - cost_benefit_analysis: "Evaluate cost-benefit of automation" safety_mechanisms: - human_oversight_integration: "Integrate human oversight where needed" - rollback_capability: "Provide rollback for automated actions" - validation_checkpoints: "Include validation checkpoints in automation" - error_handling_automation: "Automate error detection and handling" - safety_constraint_enforcement: "Enforce safety constraints in automation" automation_capabilities: code_automation: - automated_code_generation: "Generate code based on specifications" - automated_code_refactoring: "Refactor code automatically with safety checks" - automated_code_review: "Perform automated code reviews and suggestions" - automated_testing_generation: "Generate comprehensive test suites" - automated_documentation_generation: "Generate and update code documentation" build_deployment_automation: - automated_build_processes: "Automate build and compilation processes" - automated_testing_execution: "Execute automated test suites" - automated_deployment_pipelines: "Deploy applications automatically" - automated_environment_provisioning: "Provision and configure environments" - automated_rollback_procedures: "Implement automated rollback procedures" quality_automation: - automated_quality_assessment: "Assess code and system quality automatically" - automated_security_scanning: "Scan for security vulnerabilities" - automated_performance_testing: "Execute performance tests and analysis" - automated_compliance_checking: "Check compliance with standards and policies" - automated_technical_debt_analysis: "Analyze and report technical debt" collaboration_automation: - automated_notification_management: "Manage notifications and communications" - automated_task_assignment: "Assign tasks based on capabilities and availability" - automated_progress_tracking: "Track project progress automatically" - automated_reporting_generation: "Generate status and progress reports" - automated_meeting_scheduling: "Schedule meetings and coordinate activities" ``` #### Intelligent Automation Implementation ```python import asyncio import inspect from typing import Dict, List, Any, Optional, Callable, Union from dataclasses import dataclass, field from enum import Enum import json from datetime import datetime, timedelta import networkx as nx from pathlib import Path import subprocess import tempfile import logging from concurrent.futures import ThreadPoolExecutor import yaml import re class AutomationLevel(Enum): TASK = "task" WORKFLOW = "workflow" PROCESS = "process" SYSTEM = "system" class AutomationTrigger(Enum): MANUAL = "manual" SCHEDULED = "scheduled" EVENT_DRIVEN = "event_driven" PATTERN_BASED = "pattern_based" CONTEXT_DRIVEN = "context_driven" class AutomationStatus(Enum): PENDING = "pending" RUNNING = "running" COMPLETED = "completed" FAILED = "failed" PAUSED = "paused" CANCELLED = "cancelled" @dataclass class AutomationTask: """ Represents an automation task with context and execution details """ task_id: str name: str description: str automation_level: AutomationLevel trigger_type: AutomationTrigger context: Dict[str, Any] = field(default_factory=dict) prerequisites: List[str] = field(default_factory=list) dependencies: List[str] = field(default_factory=list) safety_checks: List[str] = field(default_factory=list) rollback_strategy: Optional[str] = None timeout: Optional[int] = None retry_config: Dict[str, Any] = field(default_factory=dict) validation_rules: List[str] = field(default_factory=list) human_oversight_required: bool = False @dataclass class AutomationWorkflow: """ Represents a complete automation workflow """ workflow_id: str name: str description: str tasks: List[AutomationTask] = field(default_factory=list) execution_strategy: str = "sequential" parallel_groups: List[List[str]] = field(default_factory=list) conditional_logic: Dict[str, Any] = field(default_factory=dict) error_handling: Dict[str, Any] = field(default_factory=dict) success_criteria: Dict[str, Any] = field(default_factory=dict) @dataclass class AutomationExecution: """ Tracks automation execution state and results """ execution_id: str workflow_id: str start_time: datetime end_time: Optional[datetime] = None status: AutomationStatus = AutomationStatus.PENDING task_results: Dict[str, Any] = field(default_factory=dict) execution_context: Dict[str, Any] = field(default_factory=dict) performance_metrics: Dict[str, float] = field(default_factory=dict) safety_validations: List[Dict[str, Any]] = field(default_factory=list) human_interventions: List[Dict[str, Any]] = field(default_factory=list) class IntelligentAutomationFramework: """ Advanced intelligent automation framework with context-awareness and safety """ def __init__(self, claude_code_interface, config=None): self.claude_code = claude_code_interface self.config = config or { 'max_concurrent_automations': 5, 'safety_validation_required': True, 'human_oversight_threshold': 0.8, 'automation_timeout': 3600, 'rollback_enabled': True, 'learning_enabled': True } # Core automation components self.task_automator = TaskAutomator(self.claude_code, self.config) self.workflow_engine = WorkflowEngine(self.claude_code, self.config) self.safety_monitor = SafetyMonitor(self.config) self.context_analyzer = ContextAnalyzer(self.config) # Intelligence components self.automation_intelligence = AutomationIntelligence(self.config) self.decision_engine = AutomationDecisionEngine(self.config) self.adaptation_engine = AutomationAdaptationEngine(self.config) self.learning_engine = AutomationLearningEngine(self.config) # Safety and oversight self.human_oversight = HumanOversightManager(self.config) self.rollback_manager = RollbackManager(self.config) self.validation_engine = AutomationValidationEngine(self.config) # State management self.active_executions = {} self.automation_registry = {} self.execution_history = [] # Performance tracking self.performance_tracker = AutomationPerformanceTracker() async def register_automation(self, automation_workflow: AutomationWorkflow): """ Register an automation workflow with the framework """ registration_result = { 'workflow_id': automation_workflow.workflow_id, 'registration_time': datetime.utcnow(), 'validation_results': {}, 'optimization_suggestions': [], 'safety_assessment': {}, 'registered': False } # Validate automation workflow validation_results = await self.validation_engine.validate_workflow(automation_workflow) registration_result['validation_results'] = validation_results if not validation_results.get('valid', False): registration_result['error'] = 'Workflow validation failed' return registration_result # Assess safety requirements safety_assessment = await self.safety_monitor.assess_workflow_safety(automation_workflow) registration_result['safety_assessment'] = safety_assessment # Optimize workflow if possible optimization_suggestions = await self.automation_intelligence.optimize_workflow( automation_workflow ) registration_result['optimization_suggestions'] = optimization_suggestions # Register workflow self.automation_registry[automation_workflow.workflow_id] = { 'workflow': automation_workflow, 'registration_time': registration_result['registration_time'], 'validation_results': validation_results, 'safety_assessment': safety_assessment, 'execution_count': 0, 'success_rate': 0.0, 'average_execution_time': 0.0 } registration_result['registered'] = True return registration_result async def execute_automation(self, workflow_id: str, execution_context=None): """ Execute a registered automation workflow """ if workflow_id not in self.automation_registry: raise ValueError(f"Automation workflow {workflow_id} not registered") execution = AutomationExecution( execution_id=generate_uuid(), workflow_id=workflow_id, start_time=datetime.utcnow(), execution_context=execution_context or {} ) # Store active execution self.active_executions[execution.execution_id] = execution try: # Get registered workflow workflow_info = self.automation_registry[workflow_id] workflow = workflow_info['workflow'] # Analyze execution context context_analysis = await self.context_analyzer.analyze_execution_context( workflow, execution_context ) execution.execution_context['context_analysis'] = context_analysis # Perform pre-execution safety checks safety_validation = await self.safety_monitor.validate_execution_safety( workflow, execution ) execution.safety_validations.append(safety_validation) if not safety_validation.get('safe', False): execution.status = AutomationStatus.FAILED execution.end_time = datetime.utcnow() return execution # Determine execution strategy execution_strategy = await self.decision_engine.determine_execution_strategy( workflow, context_analysis ) # Execute workflow based on strategy if execution_strategy == 'sequential': execution_result = await self.execute_sequential_workflow(workflow, execution) elif execution_strategy == 'parallel': execution_result = await self.execute_parallel_workflow(workflow, execution) elif execution_strategy == 'adaptive': execution_result = await self.execute_adaptive_workflow(workflow, execution) else: execution_result = await self.execute_intelligent_workflow(workflow, execution) # Update execution with results execution.task_results = execution_result.get('task_results', {}) execution.performance_metrics = execution_result.get('performance_metrics', {}) execution.status = execution_result.get('status', AutomationStatus.COMPLETED) # Perform post-execution validation post_validation = await self.validation_engine.validate_execution_results( workflow, execution ) execution.safety_validations.append(post_validation) # Learn from execution if self.config['learning_enabled']: learning_insights = await self.learning_engine.learn_from_execution( workflow, execution ) execution.execution_context['learning_insights'] = learning_insights # Update workflow statistics await self.update_workflow_statistics(workflow_id, execution) except Exception as e: execution.status = AutomationStatus.FAILED execution.execution_context['error'] = str(e) # Attempt rollback if enabled if self.config['rollback_enabled']: rollback_result = await self.rollback_manager.rollback_execution(execution) execution.execution_context['rollback_result'] = rollback_result finally: execution.end_time = datetime.utcnow() # Remove from active executions if execution.execution_id in self.active_executions: del self.active_executions[execution.execution_id] # Store in history self.execution_history.append(execution) # Update performance metrics await self.performance_tracker.update_metrics(execution) return execution async def execute_sequential_workflow(self, workflow: AutomationWorkflow, execution: AutomationExecution): """ Execute workflow tasks sequentially """ sequential_result = { 'execution_type': 'sequential', 'task_results': {}, 'performance_metrics': {}, 'status': AutomationStatus.RUNNING } current_context = execution.execution_context.copy() for task in workflow.tasks: task_start_time = datetime.utcnow() try: # Check prerequisites prerequisites_met = await self.check_task_prerequisites(task, current_context) if not prerequisites_met: raise Exception(f"Prerequisites not met for task {task.task_id}") # Execute task task_result = await self.task_automator.execute_task(task, current_context) # Validate task result if task.validation_rules: validation_result = await self.validation_engine.validate_task_result( task, task_result ) if not validation_result.get('valid', False): raise Exception(f"Task {task.task_id} result validation failed") sequential_result['task_results'][task.task_id] = task_result # Update context with task outputs current_context.update(task_result.get('outputs', {})) # Calculate task execution time task_duration = (datetime.utcnow() - task_start_time).total_seconds() sequential_result['performance_metrics'][f'{task.task_id}_duration'] = task_duration # Check for human oversight requirements if task.human_oversight_required: oversight_result = await self.human_oversight.request_oversight( task, task_result, current_context ) if not oversight_result.get('approved', False): raise Exception(f"Human oversight rejected task {task.task_id}") execution.human_interventions.append({ 'task_id': task.task_id, 'oversight_result': oversight_result, 'timestamp': datetime.utcnow() }) except Exception as e: # Handle task failure sequential_result['status'] = AutomationStatus.FAILED sequential_result['error'] = f"Task {task.task_id} failed: {str(e)}" # Attempt task-level recovery if task.retry_config and task.retry_config.get('enabled', False): retry_result = await self.retry_task(task, current_context, str(e)) if retry_result.get('success', False): sequential_result['task_results'][task.task_id] = retry_result current_context.update(retry_result.get('outputs', {})) continue # If no recovery possible, stop execution break if sequential_result['status'] != AutomationStatus.FAILED: sequential_result['status'] = AutomationStatus.COMPLETED return sequential_result async def execute_intelligent_workflow(self, workflow: AutomationWorkflow, execution: AutomationExecution): """ Execute workflow with intelligent adaptation and optimization """ intelligent_result = { 'execution_type': 'intelligent', 'task_results': {}, 'adaptations_made': [], 'optimizations_applied': [], 'performance_metrics': {}, 'status': AutomationStatus.RUNNING } current_context = execution.execution_context.copy() # Create dynamic execution plan execution_plan = await self.create_intelligent_execution_plan(workflow, current_context) for phase in execution_plan['phases']: phase_start_time = datetime.utcnow() # Execute tasks in phase (may be parallel or sequential) if phase['execution_mode'] == 'parallel': phase_result = await self.execute_parallel_task_group( phase['tasks'], current_context ) else: phase_result = await self.execute_sequential_task_group( phase['tasks'], current_context ) # Analyze phase results and adapt if necessary adaptation_needed = await self.automation_intelligence.analyze_phase_results( phase_result, execution_plan, current_context ) if adaptation_needed['adapt']: adaptation_result = await self.adaptation_engine.adapt_execution_plan( execution_plan, phase_result, adaptation_needed ) intelligent_result['adaptations_made'].append(adaptation_result) # Update execution plan with adaptations execution_plan = adaptation_result['updated_plan'] # Apply optimizations if beneficial optimization_opportunities = await self.automation_intelligence.identify_optimizations( phase_result, execution_plan, current_context ) for optimization in optimization_opportunities: if optimization['benefit_score'] > 0.7: # High benefit threshold optimization_result = await self.apply_optimization(optimization, execution_plan) intelligent_result['optimizations_applied'].append(optimization_result) # Update context and metrics intelligent_result['task_results'].update(phase_result.get('task_results', {})) current_context.update(phase_result.get('context_updates', {})) phase_duration = (datetime.utcnow() - phase_start_time).total_seconds() intelligent_result['performance_metrics'][f'phase_{phase["id"]}_duration'] = phase_duration intelligent_result['status'] = AutomationStatus.COMPLETED return intelligent_result class TaskAutomator: """ Executes individual automation tasks with intelligence and safety """ def __init__(self, claude_code, config): self.claude_code = claude_code self.config = config async def execute_task(self, task: AutomationTask, context: Dict[str, Any]): """ Execute a single automation task """ task_execution = { 'task_id': task.task_id, 'start_time': datetime.utcnow(), 'context': context, 'outputs': {}, 'execution_steps': [], 'success': False } try: # Determine task execution approach execution_approach = await self.determine_execution_approach(task, context) # Execute based on automation level if task.automation_level == AutomationLevel.TASK: result = await self.execute_simple_task(task, context, execution_approach) elif task.automation_level == AutomationLevel.WORKFLOW: result = await self.execute_workflow_task(task, context, execution_approach) elif task.automation_level == AutomationLevel.PROCESS: result = await self.execute_process_task(task, context, execution_approach) elif task.automation_level == AutomationLevel.SYSTEM: result = await self.execute_system_task(task, context, execution_approach) else: result = await self.execute_generic_task(task, context, execution_approach) task_execution.update(result) task_execution['success'] = True except Exception as e: task_execution['error'] = str(e) task_execution['success'] = False finally: task_execution['end_time'] = datetime.utcnow() task_execution['duration'] = ( task_execution['end_time'] - task_execution['start_time'] ).total_seconds() return task_execution async def execute_simple_task(self, task: AutomationTask, context: Dict[str, Any], execution_approach: Dict[str, Any]): """ Execute simple task automation """ simple_result = { 'execution_type': 'simple_task', 'outputs': {}, 'execution_steps': [] } # Parse task description to determine actions task_actions = await self.parse_task_actions(task.description, context) for action in task_actions: step_result = await self.execute_task_action(action, context) simple_result['execution_steps'].append(step_result) simple_result['outputs'].update(step_result.get('outputs', {})) return simple_result async def execute_task_action(self, action: Dict[str, Any], context: Dict[str, Any]): """ Execute a specific task action """ action_type = action.get('type') action_params = action.get('parameters', {}) step_result = { 'action': action_type, 'parameters': action_params, 'start_time': datetime.utcnow(), 'outputs': {}, 'success': False } try: if action_type == 'file_operation': result = await self.execute_file_operation(action_params, context) elif action_type == 'code_generation': result = await self.execute_code_generation(action_params, context) elif action_type == 'command_execution': result = await self.execute_command(action_params, context) elif action_type == 'api_call': result = await self.execute_api_call(action_params, context) elif action_type == 'data_processing': result = await self.execute_data_processing(action_params, context) else: result = await self.execute_generic_action(action_params, context) step_result['outputs'] = result step_result['success'] = True except Exception as e: step_result['error'] = str(e) step_result['success'] = False finally: step_result['end_time'] = datetime.utcnow() step_result['duration'] = ( step_result['end_time'] - step_result['start_time'] ).total_seconds() return step_result async def execute_file_operation(self, params: Dict[str, Any], context: Dict[str, Any]): """ Execute file operations using Claude Code """ operation = params.get('operation') file_path = params.get('file_path') if operation == 'read': content = await self.claude_code.read(file_path) return {'file_content': content, 'file_path': file_path} elif operation == 'write': content = params.get('content') await self.claude_code.write(file_path, content) return {'file_written': file_path, 'content_length': len(content)} elif operation == 'edit': old_content = params.get('old_content') new_content = params.get('new_content') await self.claude_code.edit(file_path, old_content, new_content) return {'file_edited': file_path, 'changes_made': True} elif operation == 'delete': # Use bash to delete file safely await self.claude_code.bash(f'rm "{file_path}"') return {'file_deleted': file_path} else: raise ValueError(f"Unknown file operation: {operation}") async def execute_code_generation(self, params: Dict[str, Any], context: Dict[str, Any]): """ Execute intelligent code generation """ generation_request = { 'description': params.get('description'), 'requirements': params.get('requirements', []), 'language': params.get('language', 'python'), 'context': context } # Use Claude Code to generate code generated_code = await self.claude_code.generate_code(generation_request) # Optionally write to file if params.get('output_file'): await self.claude_code.write(params['output_file'], generated_code) return { 'generated_code': generated_code, 'output_file': params.get('output_file'), 'code_length': len(generated_code) } async def execute_command(self, params: Dict[str, Any], context: Dict[str, Any]): """ Execute system command using Claude Code bash """ command = params.get('command') timeout = params.get('timeout', 30) # Execute command result = await self.claude_code.bash(command, timeout=timeout * 1000) # Convert to ms return { 'command': command, 'result': result, 'success': True } class SafetyMonitor: """ Monitors automation safety and enforces safety constraints """ def __init__(self, config): self.config = config self.safety_rules = self.load_safety_rules() def load_safety_rules(self): """ Load safety rules for automation """ return { 'file_operations': { 'forbidden_paths': ['/etc', '/usr/bin', '/bin'], 'require_backup': True, 'max_file_size': 10000000 # 10MB }, 'command_execution': { 'forbidden_commands': ['rm -rf /', 'dd if=/dev/zero', 'mkfs'], 'require_confirmation': ['rm', 'mv', 'cp'], 'timeout_limits': {'default': 300, 'max': 3600} }, 'network_operations': { 'allowed_domains': [], 'forbidden_ips': ['127.0.0.1', 'localhost'], 'rate_limits': {'requests_per_minute': 60} } } async def assess_workflow_safety(self, workflow: AutomationWorkflow): """ Assess the safety of an automation workflow """ safety_assessment = { 'workflow_id': workflow.workflow_id, 'safety_score': 0.0, 'risk_factors': [], 'safety_recommendations': [], 'requires_human_oversight': False } risk_factors = [] for task in workflow.tasks: task_risks = await self.assess_task_safety(task) risk_factors.extend(task_risks) safety_assessment['risk_factors'] = risk_factors # Calculate safety score (0.0 = very risky, 1.0 = very safe) if not risk_factors: safety_assessment['safety_score'] = 1.0 else: # Calculate based on risk severity total_risk = sum(risk['severity'] for risk in risk_factors) max_possible_risk = len(risk_factors) * 1.0 # Max severity is 1.0 safety_assessment['safety_score'] = max(0.0, 1.0 - (total_risk / max_possible_risk)) # Determine if human oversight is required safety_assessment['requires_human_oversight'] = ( safety_assessment['safety_score'] < self.config.get('human_oversight_threshold', 0.8) ) return safety_assessment async def assess_task_safety(self, task: AutomationTask): """ Assess the safety of a single automation task """ risk_factors = [] # Check for dangerous operations if 'delete' in task.description.lower() or 'remove' in task.description.lower(): risk_factors.append({ 'type': 'destructive_operation', 'severity': 0.8, 'description': 'Task involves potentially destructive operations' }) # Check for system-level operations if task.automation_level == AutomationLevel.SYSTEM: risk_factors.append({ 'type': 'system_level_automation', 'severity': 0.6, 'description': 'System-level automation carries inherent risks' }) # Check for missing safety checks if not task.safety_checks: risk_factors.append({ 'type': 'missing_safety_checks', 'severity': 0.4, 'description': 'Task lacks explicit safety checks' }) # Check for missing rollback strategy if not task.rollback_strategy: risk_factors.append({ 'type': 'no_rollback_strategy', 'severity': 0.3, 'description': 'Task lacks rollback strategy' }) return risk_factors ``` ### Automation Commands ```bash # Automation workflow management bmad automate register --workflow "deployment.yaml" --validate-safety bmad automate execute --workflow-id "uuid" --context "production" bmad automate status --active --show-progress # Task automation bmad automate task --type "code-generation" --description "create REST API" bmad automate task --type "testing" --target "src/" --comprehensive bmad automate task --type "deployment" --environment "staging" # Intelligent automation bmad automate intelligent --analyze-context --adaptive-execution bmad automate optimize --workflow "ci-cd" --based-on-performance bmad automate learn --from-executions --improve-automation # Safety and oversight bmad automate safety --assess --workflow "critical-deployment" bmad automate rollback --execution-id "uuid" --to-checkpoint "safe-state" bmad automate oversight --require-human --for-high-risk-tasks # Automation insights and optimization bmad automate analytics --performance --execution-patterns bmad automate suggestions --optimization --based-on-history bmad automate monitor --active-automations --real-time-alerts ``` This Intelligent Automation Framework provides sophisticated automation capabilities that can intelligently automate development tasks, workflows, and processes while maintaining safety, context-awareness, and adaptive behavior for enhanced development productivity. [{"content": "Phase 1: Core Intelligence Foundation - COMPLETED \u2705", "status": "completed", "priority": "high", "id": "phase1"}, {"content": "Phase 2: LLM Integration and Knowledge Management - COMPLETED \u2705", "status": "completed", "priority": "high", "id": "phase2"}, {"content": "Phase 3: Advanced Intelligence and Claude Code Integration - IN PROGRESS", "status": "in_progress", "priority": "high", "id": "phase3"}, {"content": "Create Autonomous Development Engine", "status": "completed", "priority": "high", "id": "3.1"}, {"content": "Implement Advanced Code Intelligence", "status": "completed", "priority": "high", "id": "3.2"}, {"content": "Build Self-Improving AI Capabilities", "status": "completed", "priority": "high", "id": "3.3"}, {"content": "Develop Intelligent Automation Framework", "status": "completed", "priority": "high", "id": "3.4"}, {"content": "Create Quality Assurance Automation", "status": "in_progress", "priority": "high", "id": "3.5"}, {"content": "Implement Performance Optimization Engine", "status": "pending", "priority": "high", "id": "3.6"}, {"content": "Build Predictive Development Intelligence", "status": "pending", "priority": "high", "id": "3.7"}, {"content": "Phase 4: Self-Optimization and Enterprise Features", "status": "pending", "priority": "medium", "id": "phase4"}]