"Overall I felt it consolidated my knowledge of C++ - filled in some gaps and corrected some misunderstandings in my knowledge, and reminded me of some important things I'd forgotten."
IH, Software Engineer, May 2021
AI Tools, Prompting, and Code Quality
Foundations and Tools
AI in C++ Development
AI Tools Setup
Effective Prompting Techniques for C++
Code Validation and Red Flags
Copy-Paste Workflow Demo
Testing and Implementation
AI-Assisted Test Generation (Google Test & GMock)
Test-Driven Development with AI
Feature Implementation with AI
When to Use AI vs. Manual Coding in C++
Code Cleanup and Readiness for Commit
Git Workflows, Code Quality, and Practical Integration
Git Workflows and Commit Discipline
Why Git History Matters with AI
Atomic Commits and Clear Messages
Interactive Rebase for Clean History
Code Review Discipline
Integration into Development Pipeline
GitHub Actions for CI/CD (C++ Workflows)
Code Analysis Tools (Clang-Tidy, Cppcheck, SonarQube)
Branch Protection and Status Checks
End-to-End Development Cycle
Review and Reflection
Real-World Patterns and Advanced Scenarios
Advanced AI Usage Patterns
Architectural Decisions with AI
Memory Management and AI (RAII, Smart Pointers)
Performance Analysis and Optimization
Debugging and Root Cause Analysis
Security and C++ Vulnerabilities
Integration
Establishing Team Standards
Creating a Team "AI Playbook" for C++
Handling AI Limitations in C++
Code Review
C++ developers looking to acquire AI development skills using C++.
"Overall I felt it consolidated my knowledge of C++ - filled in some gaps and corrected some misunderstandings in my knowledge, and reminded me of some important things I'd forgotten."
IH, Software Engineer, May 2021
“JBI did a great job of customizing their syllabus to suit our business needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and the Instructor handled this particularly well - very impressive”
Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022
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This course is designed for C++ developers who want to effectively integrate AI into their software development workflow. Rather than focusing on building AI models, the course teaches how to leverage modern AI tools to improve productivity, code quality, testing, debugging, and overall software delivery in professional C++ environments.
Participants will learn how to set up and use AI-powered development tools, craft effective prompts for C++ development tasks, validate AI-generated code, and identify common pitfalls and red flags. Through hands-on exercises, developers will explore AI-assisted test generation using Google Test and Google Mock, apply Test-Driven Development (TDD) practices, implement features with AI support, and understand when AI-generated code should be used versus manually written solutions.
The course also covers essential engineering practices that ensure AI-generated code meets professional standards. Topics include Git workflows, atomic commits, interactive rebasing, code review discipline, CI/CD automation with GitHub Actions, and the use of code quality tools such as Clang-Tidy, Cppcheck, and SonarQube.
In the advanced section, participants will learn how to use AI for architectural decision-making, memory management, performance optimization, debugging, root cause analysis, and security reviews. The course concludes with practical guidance on establishing team-wide AI development standards, creating an AI playbook for C++ projects, and integrating AI responsibly into existing development processes.
By the end of the course, developers will have a practical framework for using AI as a trusted engineering assistant while maintaining high standards for code quality, maintainability, performance, and security in modern C++ applications.
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