Enhanced System Architect Validation Checklist with Intelligence

JAEGIS Enhanced Validation & Research System

Purpose

• Comprehensive architecture validation with real-time validation and research integration

• Conduct architecture reviews with validated design methodologies and collaborative intelligence

• Ensure architecture excellence with current software architecture standards and design practices

• Integrate web research for current architecture frameworks and design patterns

• Provide validated architecture assessments with cross-team coordination and continuous optimization

Enhanced Capabilities

Architecture Intelligence

• Architecture Validation: Real-time architecture validation against current software architecture standards

• Research Integration: Current architecture design best practices and validation frameworks

• Design Assessment: Comprehensive architecture design analysis and optimization

• Quality Validation: Architecture quality analysis and design validation with continuous improvement

Collaborative Intelligence

• Shared Context Integration: Access to all architecture contexts and design requirements

• Cross-Team Coordination: Seamless collaboration with architecture teams and design stakeholders

• Quality Assurance: Professional-grade architecture validation with validation reports

• Research Integration: Current software architecture, design methodologies, and validation best practices

[[LLM: VALIDATION CHECKPOINT - All architecture validations must be validated for completeness, scalability, and current architecture standards. Include research-backed design methodologies and architecture principles.]]

This enhanced checklist ensures comprehensive architecture validation with research integration, dependency validation, and collaborative intelligence. All items must be validated with current standards and research backing.

Validation Integration Points

• Pre-Generation: Research current architectural patterns and technology standards

• Real-Time: Continuous validation during architecture design

• Post-Generation: Comprehensive quality assurance with validation reports

• Handoff: Validated context transfer to development teams

1. REQUIREMENTS ALIGNMENT

1.1 Functional Requirements Coverage

• Architecture supports all functional requirements in the PRD

• Technical approaches for all epics and stories are addressed

• Edge cases and performance scenarios are considered

• All required integrations are accounted for

• User journeys are supported by the technical architecture

1.2 Non-Functional Requirements Alignment

• Performance requirements are addressed with specific solutions

• Scalability considerations are documented with approach

• Security requirements have corresponding technical controls

• Reliability and resilience approaches are defined

• Compliance requirements have technical implementations

1.3 Technical Constraints Adherence

• All technical constraints from PRD are satisfied

• Platform/language requirements are followed

• Infrastructure constraints are accommodated

• Third-party service constraints are addressed

• Organizational technical standards are followed

2. ARCHITECTURE FUNDAMENTALS

2.1 Architecture Clarity

• Architecture is documented with clear diagrams

• Major components and their responsibilities are defined

• Component interactions and dependencies are mapped

• Data flows are clearly illustrated

• Technology choices for each component are specified

2.2 Separation of Concerns

• Clear boundaries between UI, business logic, and data layers

• Responsibilities are cleanly divided between components

• Interfaces between components are well-defined

• Components adhere to single responsibility principle

• Cross-cutting concerns (logging, auth, etc.) are properly addressed

2.3 Design Patterns & Best Practices

• Appropriate design patterns are employed

• Industry best practices are followed

• Anti-patterns are avoided

• Consistent architectural style throughout

• Pattern usage is documented and explained

2.4 Modularity & Maintainability

• System is divided into cohesive, loosely-coupled modules

• Components can be developed and tested independently

• Changes can be localized to specific components

• Code organization promotes discoverability

• Architecture specifically designed for AI agent implementation

3. TECHNICAL STACK & DECISIONS

3.1 Technology Selection

• Selected technologies meet all requirements

• Technology versions are specifically defined (not ranges)

• Technology choices are justified with clear rationale

• Alternatives considered are documented with pros/cons

• Selected stack components work well together

3.2 Frontend Architecture

• UI framework and libraries are specifically selected

• State management approach is defined

• Component structure and organization is specified

• Responsive/adaptive design approach is outlined

• Build and bundling strategy is determined

3.3 Backend Architecture

• API design and standards are defined

• Service organization and boundaries are clear

• Authentication and authorization approach is specified

• Error handling strategy is outlined

• Backend scaling approach is defined

3.4 Data Architecture

• Data models are fully defined

• Database technologies are selected with justification

• Data access patterns are documented

• Data migration/seeding approach is specified

• Data backup and recovery strategies are outlined

4. RESILIENCE & OPERATIONAL READINESS

4.1 Error Handling & Resilience

• Error handling strategy is comprehensive

• Retry policies are defined where appropriate

• Circuit breakers or fallbacks are specified for critical services

• Graceful degradation approaches are defined

• System can recover from partial failures

4.2 Monitoring & Observability

• Logging strategy is defined

• Monitoring approach is specified

• Key metrics for system health are identified

• Alerting thresholds and strategies are outlined

• Debugging and troubleshooting capabilities are built in

4.3 Performance & Scaling

• Performance bottlenecks are identified and addressed

• Caching strategy is defined where appropriate

• Load balancing approach is specified

• Horizontal and vertical scaling strategies are outlined

• Resource sizing recommendations are provided

4.4 Deployment & DevOps

• Deployment strategy is defined

• CI/CD pipeline approach is outlined

• Environment strategy (dev, staging, prod) is specified

• Infrastructure as Code approach is defined

• Rollback and recovery procedures are outlined

5. SECURITY & COMPLIANCE

5.1 Authentication & Authorization

• Authentication mechanism is clearly defined

• Authorization model is specified

• Role-based access control is outlined if required

• Session management approach is defined

• Credential management is addressed

5.2 Data Security

• Data encryption approach (at rest and in transit) is specified

• Sensitive data handling procedures are defined

• Data retention and purging policies are outlined

• Backup encryption is addressed if required

• Data access audit trails are specified if required

5.3 API & Service Security

• API security controls are defined

• Rate limiting and throttling approaches are specified

• Input validation strategy is outlined

• CSRF/XSS prevention measures are addressed

• Secure communication protocols are specified

5.4 Infrastructure Security

• Network security design is outlined

• Firewall and security group configurations are specified

• Service isolation approach is defined

• Least privilege principle is applied

• Security monitoring strategy is outlined

6. IMPLEMENTATION GUIDANCE

6.1 Coding Standards & Practices

• Coding standards are defined

• Documentation requirements are specified

• Testing expectations are outlined

• Code organization principles are defined

• Naming conventions are specified

6.2 Testing Strategy

• Unit testing approach is defined

• Integration testing strategy is outlined

• E2E testing approach is specified

• Performance testing requirements are outlined

• Security testing approach is defined

6.3 Development Environment

• Local development environment setup is documented

• Required tools and configurations are specified

• Development workflows are outlined

• Source control practices are defined

• Dependency management approach is specified

6.4 Technical Documentation

• API documentation standards are defined

• Architecture documentation requirements are specified

• Code documentation expectations are outlined

• System diagrams and visualizations are included

• Decision records for key choices are included

7. DEPENDENCY & INTEGRATION MANAGEMENT

7.1 External Dependencies

• All external dependencies are identified

• Versioning strategy for dependencies is defined

• Fallback approaches for critical dependencies are specified

• Licensing implications are addressed

• Update and patching strategy is outlined

7.2 Internal Dependencies

• Component dependencies are clearly mapped

• Build order dependencies are addressed

• Shared services and utilities are identified

• Circular dependencies are eliminated

• Versioning strategy for internal components is defined

7.3 Third-Party Integrations

• All third-party integrations are identified

• Integration approaches are defined

• Authentication with third parties is addressed

• Error handling for integration failures is specified

• Rate limits and quotas are considered

8. AI AGENT IMPLEMENTATION SUITABILITY

8.1 Modularity for AI Agents

• Components are sized appropriately for AI agent implementation

• Dependencies between components are minimized

• Clear interfaces between components are defined

• Components have singular, well-defined responsibilities

• File and code organization optimized for AI agent understanding

8.2 Clarity & Predictability

• Patterns are consistent and predictable

• Complex logic is broken down into simpler steps

• Architecture avoids overly clever or obscure approaches

• Examples are provided for unfamiliar patterns

• Component responsibilities are explicit and clear

8.3 Implementation Guidance

• Detailed implementation guidance is provided

• Code structure templates are defined

• Specific implementation patterns are documented

• Common pitfalls are identified with solutions

• References to similar implementations are provided when helpful

8.4 Error Prevention & Handling

• Design reduces opportunities for implementation errors

• Validation and error checking approaches are defined

• Self-healing mechanisms are incorporated where possible

• Testing patterns are clearly defined

• Debugging guidance is provided