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Learn practical strategies for building robust AI applications using Large Language Models in this 39-minute conference talk from Conf42 LLMs 2025. Discover essential techniques for handling LLM inconsistencies and implementing effective retry mechanisms with proper timeout configurations. Master the art of managing structured outputs from language models and explore streaming implementation patterns that enhance user experience in LLM-powered applications. Understand how to leverage background job processing for handling computationally intensive tasks and gain insights into prompt evaluation methodologies using systematic evaluation frameworks. Get an overview of foundational models and their practical applications in real-world scenarios, with actionable advice for developers looking to build production-ready AI systems that can handle the inherent challenges of working with large language models.
Syllabus
00:00 Introduction to AI Application Development
01:02 Handling LLM Inconsistencies
05:32 Implementing Retries and Timeouts
10:33 Managing Structured Outputs
15:13 Implementing Streaming in LLM Applications
20:53 Using Background Jobs for Long Tasks
29:09 Evaluating Prompts with Evals
31:53 Overview of Foundational Models
38:03 Conclusion and Contact Information
Taught by
Conf42