Build with AI: Beyond Pair Programming with AI
2h 13mIntermediate2025-01-14
Authors
Morten Rand-Hendriksen
Senior Staff Instructor, Speaker, Web Designer, and Software Developer
Course details
Effective use of AI coding assistants can speed up and improve the software development process through rapid code generation, iteration, experimentation, and a modern take on test-driven development (TDD). Apply AI tools to build and expand coding projects, create new components by generating fit-for-purpose boilerplate code, validate projects with AI-generated tests, automatically document and expand projects, and more. The course covers building new projects from scratch as well as using AI to upgrade and refactor existing codebases.
Learning objectives
Evaluate the capabilities of various AI coding assistants and integrate them into the software development workflow to enhance productivity and code quality.
Design and implement code components, leveraging AI tools to generate code templates, expand functionality, and build new features from developer instructions.
Analyze existing codebases, using AI-driven refactoring techniques to optimize code structure, update legacy code to modern standards, and improve overall maintainability.
Develop test cases and apply test-driven development (TDD) methodologies with AI assistants, generating comprehensive tests and validating code functionality to ensure reliability.
Iterate on different coding approaches and solutions, using AI tools to explore alternative implementations, refine code, and innovate beyond conventional programming paradigms.
Learning objectives
Evaluate the capabilities of various AI coding assistants and integrate them into the software development workflow to enhance productivity and code quality.
Design and implement code components, leveraging AI tools to generate code templates, expand functionality, and build new features from developer instructions.
Analyze existing codebases, using AI-driven refactoring techniques to optimize code structure, update legacy code to modern standards, and improve overall maintainability.
Develop test cases and apply test-driven development (TDD) methodologies with AI assistants, generating comprehensive tests and validating code functionality to ensure reliability.
Iterate on different coding approaches and solutions, using AI tools to explore alternative implementations, refine code, and innovate beyond conventional programming paradigms.
Skills covered
Agile Software DevelopmentWeb Development ToolsArtificial Intelligence FoundationsDevOpsArtificial Intelligence (AI)Web DevelopmentOne-Off
Concepts
Introduction
- Pair-programming with AI
- Prerequisites and how to use the exercise files
Tools, Materials, and Environments
- Tools, materials, and environments
- AI as a chatty collaborator
- AI in the IDE
- AI in the pilot seat
- AI and rethinking what a developer is
Looking the AI in the Mouth
- Where to start and how to start
- Inline generation
- Seeding, selecting, and expanding
- Generating documentation
- Documentation-Driven Development (DDD )
- Chatting with code
- Code from a chat (ChatGPT)
- Artifacts (Claude)
- Knowledge, trust, and conservative models
Iteration, Experimentation, and Expansion
- Let's build an app together
- Start with a prompt
- Use AI to build the layout
- Add an interactive map
- Use DDD to add an AI chat
- AI-driven code iteration
- Hallucinations, errors, and how to address them
Tests and Test-Driven Development
- AI and the renewed importance of tests
- Writing tests with AI
- Getting AI to set up your test environment
- Effective TDD with modern AI tools
- The challenges of AI-powered TDD
Pushing Forward with Conservative Tools
- Understanding bias in LLMs
- Detecting amplified old patterns
- Coaching the AI to use modern standards
- Documentation-driven AI assistance
- Leveraging pattern matching to push forward
Conclusion
- Upskilling is the new skill