AI-powered Code Development: The role of prompt engineering
summary
Practical prompt engineering shows up as concrete workflows: define the task, generate PHP or C++ glue code, review for SQL injection and missing error handling, write tests, then integrate. Examples include a Discord chatbot using Llama C++ model served via a REST API, a move from Windows C++ binaries to an API after flawed Flask/C++ advice, and adding a RabbitMQ queue + worker to handle single-request backends. Prompts are refined iteratively, used to refactor to PSR-1/2, and even to explain like I'm five for readable comments.
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chapters (9)
- 0:00Introduction and AI overview
- 5:07AI arms race and model evolution
- 9:33Benefits and challenges of AI
- 11:59Debunking AI myths
- 23:16What is prompt engineering
- 24:55Prompt engineering techniques
- 37:25AI workflow in development
- 39:13Future of AI in coding
- 44:48Q&A session
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