Table of Contents

Front Matter

• 00.00 AI-Augmented Product Development
• 00.01 Copyright and Legal
• 00.02 Dedication
• 00.03 About the Author
• 00.04 Preface
• 00.05 Acknowledgments
• 00.06 Table of Contents

Part I: Foundations

• 01.00 Part I Introduction: Foundations of Process-Driven Development
• 01.01 The Case for Process Excellence
• 01.02 Understanding ASPICE 4.0
• 01.03 The V-Model Philosophy
• 01.04 AI as Process Enabler
• 02.00 ASPICE Process Groups Deep Dive
• 02.01 Process Reference Model (PRM)
• 02.02 Process Assessment Model (PAM)
• 02.03 Capability Levels 0-5
• 02.04 Generic Practices
• 03.00 The AI Automation Framework
• 03.01 Automation Levels L0-L3
• 03.02 Human-in-the-Loop Patterns
• 03.03 AI Capabilities and Limitations
• 03.04 Tool Qualification for AI
• 04.00 Architecture Principles
• 04.01 Source Code as Single Source of Truth
• 04.02 Technology-Agnostic Process Design
• 04.03 The AI Augmentation Mindset

Part II: ASPICE Processes

• 05.00 System Engineering Processes
• 05.01 SYS.1 Requirements Elicitation
• 05.02 SYS.2 System Requirements Analysis
• 05.03 SYS.3 System Architectural Design
• 05.04 SYS.4 System Integration and Integration Verification
• 05.05 SYS.5 System Verification
• 05.06 AI Tools for System Engineering
• 06.00 Software Engineering Processes
• 06.01 SWE.1 Software Requirements Analysis
• 06.02 SWE.2 Software Architectural Design
• 06.03 SWE.3 Software Detailed Design and Unit Construction
• 06.04 SWE.4 Software Unit Verification
• 06.05 SWE.5 Software Component Verification and Integration Verification
• 06.06 SWE.6 Software Verification
• 06.07 AI Tools for Software Engineering
• 07.00 Hardware Engineering Processes
• 07.01 HWE.1 Hardware Requirements Analysis
• 07.02 HWE.2 Detailed Hardware Design
• 07.02a Hardware-Software Interface Management
• 07.03 HWE.3 Hardware Implementation
• 07.03a AI Integration Points for Hardware Engineering
• 07.04 HWE.4 Hardware Verification
• 07.05 Hardware Release Practices
• 08.00 Machine Learning Engineering Processes
• 08.01 MLE.1 ML Requirements Analysis
• 08.02 MLE.2 ML Model Architecture
• 08.03 MLE.3 ML Training and Learning
• 08.04 MLE.4 ML Model Testing
• 08.05 MLE.5 ML Model Deployment
• 08.06 MLE-SWE Integration Patterns
• 09.00 Support Processes
• 09.01 SUP.1 Quality Assurance
• 09.02 SUP.2 Verification
• 09.03 SUP.8 Configuration Management
• 09.03a SEC.3 Cybersecurity Verification
• 09.04 SUP.9 Problem Resolution Management
• 09.05 SUP.10 Change Request Management
• 09.06 Support Process Tools and Automation
• 10.00 Security Processes (SEC)
• 10.01 SEC.1 Cybersecurity Requirements
• 10.02 SEC.2 Cybersecurity Implementation
• 10.03 SEC.3 Risk Treatment Verification
• 10.04 ISO/SAE 21434 Integration
• 10.06 MLE Process Checklists
• 11.00 Management Processes (MAN)
• 11.01 MAN.3 Project Management
• 11.02 MAN.5 Risk Management
• 11.03 MAN.6 Measurement
• 12.00 Process Improvement
• 12.01 Capability Levels Deep Dive
• 12.02 Assessment Preparation
• 12.03 Continuous Improvement

Part III: AI Toolchain

• 11.05 Hardware-in-Loop (HwIL) Testing Framework
• 11.06 Toolchain Validation Framework
• 11.07 Debugging and Profiling Tools for Embedded Systems
• 13.00 Requirements and Architecture Tools
• 13.01 Requirements Management Systems
• 13.02 AI Requirements Analysis
• 13.03 Traceability Automation
• 13.04 MBSE and Architecture Tools
• 13.05 AUTOSAR Tools
• 14.00 Implementation Tools
• 14.01 AI Code Generation
• 14.02 Code Quality and Standards
• 14.03 AI Code Review Tools
• 14.04 Static Analysis Integration
• 14.05 Embedded Development Platforms
• 15.00 Verification and Testing Tools
• 15.03 HIL/SIL/PIL Testing
• 15.04 Coverage Analysis
• 15.05 Flaky Test Detection
• 16.00 CI/CD Integration
• 16.01 Jenkins Configuration
• 16.02 GitHub Actions Configuration
• 16.03 GitLab CI Configuration
• 16.04 Bitbucket Pipelines Configuration
• 16.05 Container Security with AI
• 16.06 Pipeline Patterns for Embedded Systems
• 17.00 Workflow Automation
• 17.01 n8n Workflow Patterns
• 17.02 Automated Traceability
• 17.03 Intelligent Notifications
• 17.04 Report Generation
• 18.00 Tool Selection Guide
• 18.01 Tool Comparison Matrices
• 18.02 Selection Criteria by Project
• 18.03 Integration Patterns
• 18.04 Tool Qualification Evidence Generation for Aviation and Automotive
• 18.05 Tool Qualification Across Standards - Unified Framework

Part IV: Practical Implementation

• 15.05 Multi-Standard Compliance Roadmap
• 16.01 Legacy System ASPICE Retrofit
• 19.00 Project Setup
• 19.01 Process Tailoring
• 19.02 Repository Structure
• 19.03 CI/CD Pipeline Setup
• 19.04 Tool Selection and Integration
• 19.05 Team Onboarding
• 20.00 Work Product Templates
• 20.01 Requirements Templates
• 20.02 Architecture Templates
• 20.03 Test Specification Templates
• 20.04 Review and Report Templates
• 21.00 Safety Standards Integration
• 21.01 ISO 26262 Integration
• 21.02 IEC 61508 Integration
• 21.03 DO-178C Integration
• 21.04 Tool Qualification
• 22.00 Agile and ASPICE
• 22.01 Agile Principles in ASPICE Context
• 22.02 Sprint Work Products
• 22.03 Continuous ASPICE Compliance
• 23.00 Organizational Considerations
• 23.01 Pilot Project Selection
• 23.02 Rollout Strategy
• 23.03 Training and Competency
• 23.04 Metrics and KPIs
• 24.00 Assessment Preparation
• 24.01 Evidence Collection
• 24.02 Common Findings
• 24.03 Continuous Readiness

Part V: Industry Applications

• 21.05 Space Systems and ECSS Standards
• 25.00 Automotive ECU Development
• 25.01 Project Context and Requirements
• 25.02 Architecture and Design
• 25.03 Implementation with AI
• 25.04 Verification and Validation
• 25.05 ASIL Decomposition Methods
• 25.06 Lessons Learned
• 26.00 Industrial Controller Development
• 26.01 IEC 61508 Context
• 26.02 Hardware-Software Co-Design
• 26.03 Certification Path
• 27.00 Medical Device Software
• 27.01 IEC 62304 Requirements
• 27.02 Regulatory Documentation
• 27.03 Risk-Based Approach
• 28.00 ML-Enabled ADAS Systems
• 28.01 MLE Process Application
• 28.02 SOTIF Considerations
• 28.03 Perception Pipeline
• 28.04 Aerospace DO-178C Application with ASPICE Integration

Part VI: AI Agent Guide

• 29.00 Agent Framework
• 29.01 Agent Roles and Responsibilities
• 29.02 HITL Integration Protocol
• 29.03 Capability Mapping
• 29.04 Limitation Acknowledgment
• 29.05 Agent Teams
• 30.00 Process Execution Instructions
• 30.01 Requirements Agent Instructions
• 30.02 Architecture Agent Instructions
• 30.03 Implementation Agent Instructions
• 30.04 Verification Agent Instructions
• 30.05 Review Agent Instructions
• 30.06 AI Agent Error Detection and Recovery
• 31.00 Workflow Instructions
• 31.01 Pull Request Workflow Instructions
• 31.02 Testing Workflow Instructions
• 31.03 Release Workflow Instructions
• 32.00 Prompt Templates
• 32.01 Requirements Analysis Prompt Templates
• 32.02 Code Generation Prompt Templates
• 32.03 Code Review Prompt Templates
• 32.04 Testing Prompt Templates

Part VII: Engineer's Tutorial

• 33.00 Thinking Like a Systems Engineer
• 33.01 The Systems Engineering Mindset
• 33.02 Requirements Engineering Practice
• 33.03 Architecture Decision Making
• 33.04 Traceability in Practice
• 34.00 Thinking Like a Software Engineer
• 34.01 Clean Code Principles
• 34.02 Test-Driven Development
• 34.03 Code Review Excellence
• 34.04 Continuous Integration Mastery
• 35.00 Working with AI Assistants
• 35.01 Effective Prompting
• 35.02 Reviewing AI Output
• 35.03 HITL Decision Making
• 35.04 AI Tool Selection
• 36.00 Putting It All Together
• 36.01 End-to-End Example
• 36.02 Common Pitfalls
• 36.03 Continuous Learning

Appendices

• 99.01 Appendix A: Tool Configuration Reference
• 99.02 Appendix B: Work Product Templates
• 99.03 Appendix C: Process Quick Reference
• 99.04 Appendix D: AI Tool Comparison Matrix
• 99.05 Appendix E: ASPICE-Safety Standard Mapping
• 99.06 Appendix F: Checklist Library
• 99.07 Appendix G: Glossary
• 99.08 Appendix H: Acronyms
• 99.09 Appendix I: Bibliography
• 99.10 Appendix J: Index