Coursera Flash Sale
40% Off Coursera Plus for 3 Months!
Grab it
Learn how to deploy agentic generative AI systems to production environments in this 41-minute conference talk from the Data Science Festival. Explore the evolution of large language model architectures into sophisticated agentic systems and discover practical approaches for observing and measuring their performance in enterprise settings. Begin with an examination of large language model architectures, focusing on the transition from simple LLM wrappers to systems incorporating retrieval-augmented generation techniques that address data cut-off issues and hallucinations for more reliable, contextually relevant outputs. Dive deep into agentic architecture that leverages large language models as reasoning engines to enable dynamic decision-making and flexible application flow through tool integration and cyclical reasoning processes. Examine critical deployment considerations for production environments, including observability frameworks and evaluation metrics essential for monitoring and improving LLM application performance. Experience a live demonstration of the tool's user interface alongside its observability platform to see these concepts in action. Gain practical insights into building, deploying, operating, and continuously improving agentic systems within enterprise environments, with content delivered at a technical practitioner level by Oliver Parson and Richard Moss from National Grid.
