Build an Automated Agent Optimization Workflow

Learn to build automated agent optimization workflows using the Opik Agent Optimizer toolkit. The guide covers setting up automated prompt optimization that iteratively improves LLM prompts based on evaluation datasets and metrics. Additionally, explore three key prompting techniques for better LLM reasoning: Chain of Thought for step-by-step thinking, Self-Consistency for majority voting across multiple responses, and Tree of Thoughts for exploring multiple reasoning paths. The tutorial includes practical code examples and demonstrates how to evaluate prompt effectiveness using metrics like LevenshteinRatio.