Essential reference guide for Java programmers of all skill levels to use AI to speed up tedious tasks, reduce mistakes, and gather suggestions for better ways to use the language they already know. In just 6 laminated pages you can reference the skills to deliberately direct AI tools to explain unfamiliar code, navigate libraries faster, design cleaner architecture, and write better tests. Used the right way, AI becomes a second brain, true assistant, and force multiplier for serious developers. This is not a vibe coding guide. Author Robin Nixon worked with computers in the 80s and started developing websites in the 90s becoming an expert and writing over 40 programming books and over 500 articles for top computer magazines. With his expertise in the field and writing to his audience in our succinct and organized QuickStudy format, this reference has more quality actionable facts per page than any book or website. Designed for quick access to the facts you need, this inexpensive tool is an easy add to your programming toolbox. As our programming reference guides climb in sales to best-selling status, it is clear that print is not dead and this handy desktop tool is an unbeatable value.
6 page laminated guide includes:
- AI & Your Development Environment
- IntelliJ IDEA
- Eclipse IDE
- VS Code
- GitHub Copilot
- Cursor
- Windsurf
- Tabnine
- Amazon Q
- Extensions to Consider
- Setting Up AI API Keys
- Storing API Keys Securely
- Common AI APIs & Key Names
- Local Models & Offline AI
- Token Costs
- Copyright Issues
- AI Assistance Core Use Cases
- Code Completion & Refactoring
- Code Search & Retrieval
- Library & API Familiarization
- Code Conversion & Translation
- AI for Specific Coding Tasks
- Authentication & Integration
- AI for Testing
- AI for Regx & String Handling
- AI for Debugging
- Diagnosis Errors & Exceptions
- Reading Stack Traces with AI
- Multilevel Stack Traces
- AI for Code Design & Planning
- System Design via Conversation
- Data Models & Class Design
- AI for Advanced Java
- From Code Assistant to Engineering Partner
- AI-Assisted Docs & Commenting
- Commenting what Matters
- Markdown & README Generation
- AI in Responsible Java Development
- Hallucination Risks
- Lack of Long-Term Memory
- Other Limitations
- Managing Context Limits
- When Not to Trust Autocomplete
- AI Prompt Hygiene & Version Control
- Checking Diffs
- Saving Useful Prompts & Results
- Use .gptignore or Equivalent for Sharing
- AI-Assisted Security
- AI-Assisted Optimization
- AI for Maintaining Legacy Code
- Reading & Understanding Old Code
- Refactoring & Modernizing
- Risk Reduction & Safe Refactoring
- Top Java AI Assistant Prompts
- AI & Java Developer’s Checklist
