Beyond Copilot:Leveraging the Latest AI Tools to Build Better Software | John Lindquist | ngconf2024

AI coding assistants are becoming increasingly sophisticated, with options beyond GitHub Copilot like Cursor, Codium, and Claude 3 offering enhanced capabilities

Script automation and AI tools can reduce development time by 100x or more, especially for repetitive or complex tasks

Modern AI tools can effectively understand and explain complex codebases, data flows, and system architectures without requiring explicit documentation

Problem-solving and reasoning skills remain crucial - AI should be viewed as a productivity multiplier rather than a replacement for developer expertise

Tools like Whisper (transcription), Deepgram (audio), and various UI generators are making previously complex tasks accessible through simple prompts

Custom rules and prompts can significantly improve AI coding assistant output by enforcing consistent coding styles and practices

Local AI model options exist but are hardware-intensive; cloud-based solutions remain more practical for most use cases

AI is particularly effective for:

• Code path explanation
• New developer onboarding
• Documentation generation
• Quick script creation
• Edge case analysis

Companies investing heavily in AI tooling suggests rapid advancement and broader adoption in coming years

Focus should shift toward documentation, explanation, and teaching rather than just code production, as these skills become increasingly valuable