LLM Prompt Optimizations: Practical Techniques for Developers Optimizing inputs for LLMs ensures better, more consistent outputs while leveraging the full potential of the model s underlying capabilities. By understanding core concepts like tokenization, embeddings, self-attention, and context limits, you can tailor inputs to achieve desired outcomes reliably. Below, you ll find fundamental…