Teach AI to Answer Questions Based on Your Documents
I started this 2026 series because document-grounded AI has become both more common and more confusing.
In 2023, my first tutorials focused on getting Azure AI Search and Azure OpenAI working for document question answering. That was the right starting point then: show retrieval, indexing, embeddings, and answer generation in a concrete Azure workflow.
This new series starts earlier in the decision process. Before choosing tools, developers need to understand when RAG is the right fit, when a managed Azure stack makes sense, when open-source components are a better choice, and where fine-tuning actually belongs.
The first article is meant to reset the architecture conversation. Document-grounded AI is not only a prompt pattern. It is a system design problem involving source documents, retrieval quality, evaluation, operations, and the trade-offs between managed and self-managed infrastructure.
The principle for the series is simple: choose the architecture before choosing the stack.
Read the full article on GitHub: