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This tutorial provides a step-by-step guide to understanding prompt chaining in AI Engineering. Learn the structure and application of this simple yet powerful technique through practical code examples. Explore different implementation approaches including single prompt, long prompt chaining, and short prompt chaining versions. The 22-minute video covers the cost-benefits of prompt chaining, demonstrates a complete example project, shows implementation in Jupyter Notebook, and discusses backend engineering improvements. Includes timestamps for easy navigation and links to valuable resources like Rivet (an open-source LLM diagram software), along with recommended articles from DataCamp and Anthropic on prompt chaining techniques.
