<ul><li>LLM models, like OpenAI's ChatGPT, rely heavily on well-written prompts for accurate responses.</li><li>Crafting effective prompts involves iterating, evaluating, and templatizing queries.</li><li>Quality prompts lead to better AI model output, saving time and improving results.</li><li>Iteration is key: start simple, test the output, refine, and iterate further for specificity.</li><li>By refining prompts iteratively, you can achieve accurate and relevant responses.</li><li>A prompt template example for generating SQL queries is provided, emphasizing metadata and user instructions.</li><li>An example prompt involving generating a BigQuery SQL query based on metadata and user requirements is demonstrated.</li><li>The sample prompt leads to the generation of a specific SQL query for calculating total deposits of yesterday.</li><li>Submitting the prompt to LLM resulted in a BigQuery SQL query for total deposits of yesterday.</li><li>Crafting precise prompts is essential for AI models to provide contextually appropriate responses.</li></ul>

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