RAG beats Fine-Tuning in learning your code base - but it doesn’t make AI a better dev
AI Summary
Video Title: AI Coding Assistant Exploration
Guests: Guy Gurari, Co-founder of Augment; Dion (Co-host)
Key Points:
- Purpose of Augment: AI coding assistant that provides complete code base awareness to make developers more productive.
- Efficiency Gains: Users can quickly get up to speed on unfamiliar code parts, reducing onboarding time from weeks to hours.
- Evolution of Language Models: Guy’s journey from Google to building AI coding assistants; significance of models like GPT-3.
- Context Matters: Importance of understanding the full code base for effective coding and good completion generation.
- Future of Automation: Predictions on the role of coding assistants in future development and how they can automate certain tasks.
- Developer Skills for the Future:
- Deep understanding of systems remains essential.
- Learning how to effectively use AI models will become increasingly important.
- Open Source Models: Discussion on the challenges and potential of open weights versus truly open-source models.
- Viewer Takeaway: Encouragement to try Augment and share feedback.
Call to Action: Visit augmentcode.com to start using Augment and provide feedback.