Tech Events & Workshops

A practical two-hour session on the principles behind document question-answering systems, with Rust as the implementation context. The session focuses on how applications can answer questions from a known set of documents instead of relying only on what a language model already knows. We will cover the core workflow: loading documents, preparing them for search, finding relevant passages, passing useful context to a model, and producing answers that stay connected to the source material. The goal is to teach the engineering ideas behind RAG systems without turning the session into a product demo or an abstract AI lecture. The emphasis is on system boundaries, retrieval quality, answer grounding, error handling, and the practical decisions developers need to make when building document-aware applications. Audience: entry-level and intermediate developers who want a practical session on document search, retrieval, grounded generation, and Rust application design. Outcomes: * Understand how document-based question answering systems work * Explain the purpose of chunking, embeddings, retrieval, and context assembly * Design a simple retrieve-first, answer-second workflow * Use Rust to organize the main parts of a small RAG application * Recognize common causes of poor or unsupported answers * Apply basic techniques for improving retrieval and answer quality * Think about how to evaluate whether the system is actually useful Format: two hours with a short framing walkthrough, a concrete example, discussion of tradeoffs, and a closing checklist for practice.

A practical two-hour session on the principles behind document question-answering systems, with Rust as the implementation context. The session focuses on how applications can answer questions from a known set of documents instead of relying only on what a language model already knows. We will cover the core workflow: loading documents, preparing them for search, finding relevant passages, passing useful context to a model, and producing answers that stay connected to the source material. The goal is to teach the engineering ideas behind RAG systems without turning the session into a product demo or an abstract AI lecture. The emphasis is on system boundaries, retrieval quality, answer grounding, error handling, and the practical decisions developers need to make when building document-aware applications. Audience: entry-level and intermediate developers who want a practical session on document search, retrieval, grounded generation, and Rust application design. Outcomes: * Understand how document-based question answering systems work * Explain the purpose of chunking, embeddings, retrieval, and context assembly * Design a simple retrieve-first, answer-second workflow * Use Rust to organize the main parts of a small RAG application * Recognize common causes of poor or unsupported answers * Apply basic techniques for improving retrieval and answer quality * Think about how to evaluate whether the system is actually useful Format: two hours with a short framing walkthrough, a concrete example, discussion of tradeoffs, and a closing checklist for practice.