\n In this video, I walk through the complete setup of a Retrieval-Augmented Generation (RAG) system built entirely with Claude Code, from initial idea to working prototype.<\/p>\n
The project starts from simple user stories and evolves into a practical AI assistant usable across multiple domains:
\n– Journalism
\n– Human Resources (HR)
\n– RFP (Request for Proposal)
\n– Screenwriting<\/p>\n
The key idea behind this RAG is not just answering questions, but enabling a human expert to navigate a dense corpus of information while preserving traceability of sources.<\/p>\n
This video focuses on:
\n– Structuring a RAG pipeline from scratch
\n– Using Claude Code as the sole development assistant
\n– Managing token consumption efficiently during development
\n– Transforming raw content into a usable knowledge base<\/p>\n
This is part of a broader experiment: building a complete AI product without traditional coding workflows, relying fully on Claude Code.\n <\/p>\n","protected":false},"excerpt":{"rendered":"
In this video, I walk through the complete setup of a Retrieval-Augmented Generation (RAG) system built entirely with Claude Code, from initial idea to working… <\/p>\n