Many teams and stakeholders want to add AI features to their applications, but quickly discover that real, reliable functionality takes more than a simple call to an LLM. This session focuses on practical, production-ready ways to bring intelligent capabilities to existing .NET applications without hype or unnecessary complexity.

We will cover proven patterns such as retrieval-augmented generation, structured prompting, vector search, agent-style workflows, and hybrid approaches that combine LLMs with traditional .NET code. The examples include features that organizations are shipping today: natural language search, document summarization, conversational help, analytics insights, automated workflows, and smarter administrative tools.

Along the way, we will address the architectural and operational considerations that matter in real systems, including data readiness, security boundaries, performance, observability, and cost management. The goal is to give you a clear and practical roadmap for building AI features that users can trust and that your existing .NET architecture can support.