52 Weeks of Cloud

Context Driven Development

Episode Summary

The podcast discusses context-driven development as an emerging methodology that combines AI assistance with traditional DevOps principles. By providing AI tools with complete project context rather than using them for incremental code completion, developers can get more meaningful insights while maintaining control over their development process. This approach mirrors CI/CD practices, where system-wide feedback drives improvements, but applies it to AI-assisted development workflows.

Episode Notes

Title: Context-Driven Development with AI Assistants

Key Points:

• Compares context-driven development to DevOps practices
• Emphasizes using AI tools for project-wide analysis vs line-by-line assistance
• Focuses on feeding entire project context to AI for specific insights
• Highlights similarities with CI/CD feedback loops
• Positions this approach as non-controversial use of AI coding assistants

Main Arguments:

1. AI tools work best with full project context rather than isolated code completion
2. Developer maintains control over which AI suggestions to implement
3. Similar to DevOps feedback loops but for code quality and improvements
4. Works equally well with open-source and proprietary AI tools

Key Applications:

• Code reviews
• Test coverage analysis
• Documentation improvements
• Feature development guidance