Letting LLMs Write RAG Applications
What we'll cover:
"The hottest new programming language is English," as Andrej Karpathy famously said. But does that hold true for writing end-to-end RAG applications with Qdrant? We put it to the test.
Join us on Tuesday, March 18th, for an interactive live coding session where we'll demonstrate how to build a complete RAG application by avoiding writing code ourselves at all costs. We'll explore how far we can push AI systems to generate both frontend and backend code through natural language prompts and instructions, creating a fully functional RAG application powered by Qdrant's vector search capabilities.
We've evaluated different AI coding assistants, including Cursor, Aider, Claude Code, and GitHub Copilot. While Claude 3.5 and 3.7 have earned recognition for producing amazing frontend code, we'll assess its capabilities for full-stack development and discuss which frameworks deliver the most consistent and high-quality results.
Learning outcomes:
- Understand the process of building a RAG application using AI-powered tools.
- Explore how AI can be leveraged to generate both frontend and backend code with natural language prompts.
- Gain insights into vector search capabilities through Qdrant in the context of a RAG application.
- Learn about different AI coding assistants (Cursor, Aider, Claude Code, GitHub Copilot) and their strengths for full-stack development.
- Evaluate which frameworks and approaches deliver the most consistent and high-quality results for AI-driven development.
Who should attend:
- Developers interested in AI-assisted programming and no-code/low-code solutions.
- Engineers looking to explore the potential of natural language for end-to-end application development.
- Anyone curious about using AI tools for full-stack development, including building RAG applications.
- Professionals interested in understanding the latest trends in AI coding assistants and vector search technology.
Pre-req's:
- Basic understanding of software development, particularly in frontend and backend frameworks.
- Familiarity with the concepts of RAG and vector search.
- Some experience with general programming concepts will be helpful.
- No prior knowledge of specific coding assistants like Cursor, Aider, or Claude required.