AI Empowered Software Development Introduction explores how experienced software developers and teams can dramatically boost productivity using modern AI tools, across two intensive, hands-on days. Attendees work with generative AI systems, coding assistants, development environment add-ons, simulated data generation tools, testing tools, and deployment tools. Day one covers foundational concepts, AI-powered coding assistants and development environments, advanced coding assistant usage, and prompt engineering techniques. Day two moves into AI in CI/CD, testing, and deployment. It covers AI-assisted testing and QA, deployment pipelines, collaborative development with AI, and data analytics and log analysis. Throughout, the course also covers generative AI tools such as ChatGPT, Gemini, Claude, and Perplexity. These are applied to cross analysis, ideation, architecture design, and best-practices auditing.
Labs anchor each topic in hands-on practice. Attendees configure coding assistants such as Visual Studio Code, JetBrains IDEs, and Claude Code. They then work with AGENTS.md, CLAUDE.md, and GEMINI.md files to give agents durable project context. Prompt engineering labs move through zero-shot, few-shot, and chain-of-thought techniques before using generative AI as a design and architecture collaborator. On day two, attendees write and optimize test cases with AI-powered testing tools like Cody and DeepSource. They also generate synthetic data with Faker and set up an AI-enhanced CI/CD pipeline using tools such as Harness. A collaborative development lab has teams manage version control and code reviews with AI insights. The course then closes by analyzing logs and extracting trends with AI to inform ongoing development decisions.
Who Should Attend
Anyone interested in generative AI accelerated software engineering
What Attendees Will Learn
Upon completing AI Empowered Software Development Introduction, participants will be able to:
- Demonstrate mastery of AI tools and techniques to enhance software development productivity
- Show proficiency in applying the target language and SQL with AI-powered assistants
- Understand the basis for hallucinations and how to reduce them
- Have confidence using AI for testing, deployment, and collaboration
- Create high-quality tests and documentation
Prerequisites
- Proficiency in some programming language
- Experience with basic software development workflows
- Familiarity with typical development tools like Git, Docker, and Editors/IDEs