In today’s world, personalization is no longer a premium - it’s the baseline. Users expect systems to anticipate their needs seamlessly, yet building pipelines that deliver relevance without breaking infrastructure or trust is still one of the hardest engineering challenges. This session explains how modern personalization works and why hybrid approaches matter. We’ll trace the path from user signals to smart retrieval and ranking, and show how large language models fit in - not as replacements, but as helpers that make recommendations more natural, contextual, and cost-efficient. Whether you’re working on feeds, search, or IoT-driven experiences, you’ll leave with a blueprint for adaptive systems that continuously learn, respect user intent, and balance real-time scale with long-term trust.