Update src/pages/[platform]/ai/concepts/prompting/index.mdx

Co-authored-by: Ian Saultz <[email protected]>

src/pages/[platform]/ai/concepts/prompting/index.mdx

@@ -33,7 +33,7 @@ export function getStaticProps(context) {
 
 LLM prompting refers to the process of providing a language model, such as Claude or Amazon Titan, with a specific input or "prompt" in order to generate a desired output. The prompt can be a sentence, a paragraph, or even a more complex sequence of instructions that guides the model to produce content that aligns with the user's intent.
 
-The key idea behind prompting is that the way the prompt is structured and worded can significantly influence the model's response. By crafting the prompt carefully, users can leverage the LLM's extensive knowledge and language understanding capabilities to generate high-quality and relevant text, code, or other types of output.
+The way the prompt is structured and worded can significantly influence the model's response. By crafting the prompt carefully, users can leverage the LLM's extensive knowledge and language understanding capabilities to generate high-quality and relevant text, code, or other types of output.
 
 Effective prompting involves understanding the model's strengths and limitations, as well as experimenting with different prompt formats, styles, and techniques to elicit the desired responses. This can include using specific keywords, providing context, breaking down tasks into steps, and incorporating formatting elements like bullet points or code blocks.