Who controls retrieval in agentic retrieval augmented generation (RAG), and how is that different from traditional RAG? This episode of Quick Question digs into how an AI agent decides what to search for, evaluates results, and retrieves again if needed, adding an iterative loop around RAG's traditional retrieve-then-generate pipeline. 0:08 - What is RAG? 1:01 - What is agentic RAG? 2:02 - What is the difference between RAG and agentic RAG? 2:48 — RAG vs. agentic RAG: GPS vs. cab driver analogy 3:18 - Why move from RAG to context engineering? [Video] Quick Question - Full Episodes → Quick Question [[Webinar] Getting started with agentic RAG using Elasticsearch→ https://www.elastic.co/virtual-events/agentic-rag?utm_source=youtube&utm_medium=organic-social&utm_campaign=quick-questions-cee-gc&utm_content=ep7] Additional Resources: Additional resources: How to build a RAG agent with Elasticsearch: https://www.elastic.co/search-labs/blog/rag-agent-elasticsearch-github-copilot-sdk Learn more about Elasticsearch: https://www.elastic.co/elasticsearch Start the 14-day trial for free! No credit card required: https://cloud.elastic.co/registration Subscribe to Elastic’s Community YT channel: https://www.youtube.com/c/OfficialElasticCommunity Connect with us on social media: LinkedIn: https://www.linkedin.com/company/elastic-co X: https://twitter.com/elastic Facebook: https://www.facebook.com/elastic.co About Elastic Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale. Elastic’s solutions for search, observability, and security are built on the Elastic Search AI Platform — the development platform used by thousands of companies, including more than 50% of the Fortune 500. #AgenticAI #AIAgents #Elasticsearch

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