How senior developers actually use AI day to day
AI Summary
- AI in Software Engineering Overview
- Current hype around AI vs. real applications in software development
- Senior software engineer’s use of AI for daily tasks
- Main Points on AI Usage
- Realistic Expectations: AI won’t replace jobs but can help automate boring tasks
- Two Major Use Cases:
- Writing entire features without understanding (not efficient long-term)
- Automating repetitive tasks
- Automation Tasks
- Unit Tests:
- AI can write effective unit tests (e.g., using Claude 3.7)
- Initial prompt with style guide improves accuracy
- API Discovery:
- AI can summarize API functions, saving time in reading documentation
- Example: Asking for Stripe API usage
- Boilerplate Code:
- AI can generate initial UI code based on design prompts (e.g., using Chakra UI)
- Function Generation:
- AI can quickly create function shells for typed languages
- Idea Discussion:
- Using AI to bounce ideas off, similar to rubber ducking
- Cautions
- Engineers must understand the code they push to production
- Inexperience can lead to production bugs if relying too heavily on AI
- Conclusion
- Understanding fundamentals is crucial even as AI tools evolve