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Author: danieloh30

content/modules/ROOT/pages/module-prompt.adoc

@@ -38,7 +38,7 @@ You might choose to use prompt engineering over other techniques if you're looki
 
 There are many tools and approaches available to you as the AI application developer to interface an LLM.  We will briefly review a few of these and then make a recommendation for you to follow with the subsequent steps of this module.
 
-Before jumping into specific tools, let's review the basics of interfacing with an LLM through a chat or agentic experience.  Since LLMs can often support a wide variety of use cases and personas, it is important that the LLM receive clear, upfront guidance to define its objectives, constraints, persona, and tone.  These instructions are provided in natural language form and are form the "System Prompt".  Once a System Prompt is defined and a chat session begins, the System Prompt cannot be changed.
+Before jumping into specific tools, let's review the basics of interfacing with an LLM through a chat or agentic experience.  Since LLMs can often support a wide variety of use cases and personas, it is important that the LLM receive clear, upfront guidance to define its objectives, constraints, persona, and tone.  These instructions are provided in natural language format that are specified in the "System Prompt". Once a System Prompt is defined and a chat session begins, the System Prompt cannot be changed.
 
 Depending on use case, it may be necessary for the LLM to produce a more creative or a more predictable response to the user message.  Temperature is a floating point number, usually between 0 and 1, that is used to steer the model accordingly.  Lower temperature values (such as 0) are more predictable and higher values (such as 1) are more creative, although even at 0 LLMs will never product 100% repeatable responses.  Many tools simply use 0.8 as a default.