diff --git a/docs/setup/getting-started-azure-openai.md b/docs/setup/getting-started-azure-openai.md
index 95aa992..2f15cb0 100644
--- a/docs/setup/getting-started-azure-openai.md
+++ b/docs/setup/getting-started-azure-openai.md
@@ -1,11 +1,11 @@
 # Setting Up the Development Environment for Azure OpenAI
 
-Azure AI Foundry is a service that allows you to deploy and manage AI models in the cloud. You can things like create a project, deploy a model, interact with the model, and more.
+Azure AI Foundry is a service that allows you to deploy and manage AI models in the cloud. You can do things like create a project, deploy a model, interact with the model, and more.
 
 > [!NOTE]
 > If you want to use Azure AI Foundry models for your .NET AI apps in this course, follow the steps in this guide.
 
-👉 [To use GitHub Models this is the guide for you](./README.md)
+👉 [If you want to use GitHub models, follow this guide instruction.](./README.md)
 
 ## Create the Azure AI Foundry resources
 
@@ -15,7 +15,7 @@ To use Azure AI Foundry models, you need to take the following steps:
 1. Deploy a model to your project.
 1. Add the Azure AI library code + API key and other credentials to your code.
 
-### -1- Create a Hub and Project in Azure AI Foundry
+### Step 1: Create a Hub and Project in Azure AI Foundry
 
 1. Go to the [Azure AI Foundry Portal](https://ai.azure.com/).
 1. Sign in with your Azure account.
@@ -36,7 +36,7 @@ To use Azure AI Foundry models, you need to take the following steps:
 
 Before you can interact with the model, you need to deploy it to your project, so let's do that next.
 
-### -2- Deploy a Language Model in Azure AI Foundry
+### Step 2 : Deploy a Language Model in Azure AI Foundry
 
 Now, let’s deploy a **gpt-4o-mini** model to your project:
 
diff --git a/lessons/03-prompt-engineering/sample-app/app.js b/lessons/03-prompt-engineering/sample-app/app.js
index c277e1b..5c4c74e 100644
--- a/lessons/03-prompt-engineering/sample-app/app.js
+++ b/lessons/03-prompt-engineering/sample-app/app.js
@@ -1,6 +1,7 @@
 import { OpenAI } from "openai";
 import readline from "readline";
 
+// User input 
 const rl = readline.createInterface({
   input: process.stdin,
   output: process.stdout
@@ -14,48 +15,38 @@ const question = (query) => {
   });
 };
 
-const height = await question("Enter the current height above the ground in meters:");
+async function main() {
+  const userPrompt = await question("Enter your prompt: ");
 
-const speed = await question("Enter the speed at which you're moving forward in meters per second:");
+  const messages = [
+    {
+      role: "user",
+      content: userPrompt
+    }
+  ];
 
-const gravity = await question("Enter the gravity in meters per second squared:");
-
-const wind = await question("Enter the wind speed upwards in meters per second:");
-
-// Distance to the hill
-const distance = 100;
-
-// Create prompt including inputs should include chain of thought
-
-const prompt = "TODO";
-
-// Call the language model with the prompt
-
-const messages = [
-{
-    "role": "user",
-    "content": prompt
-}];
-
-// 2. Create client
-// -----------------------------------
-
-const openai = new OpenAI({
-  baseURL: "https://models.inference.ai.azure.com",
-  apiKey: process.env.GITHUB_TOKEN,
-});
-
-// 3. Send the request
-// -----------------------------------
+  // OpenAI API setup
+  const openai = new OpenAI({
+    baseURL: "https://models.inference.ai.azure.com",
+    apiKey: process.env.GITHUB_TOKEN,
+  });
 
-const completion = await openai.chat.completions.create({
+  const completion = await openai.chat.completions.create({
     model: 'gpt-4o-mini',
     messages: messages,
-});
+  });
+
+  const answer = completion.choices[0]?.message?.content;
+
+  console.log(`\nAI Response:\n`);
+  console.log(answer);
 
-console.log(`Answer for "${prompt}":`);
+  // Easter Egg Check
+  if (userPrompt.toLowerCase().includes("time-traveling javascript developer") && answer) {
+    console.log("\n Easter Egg Unlocked! You discovered the hidden poem! ");
+  }
 
-// 4. Print the answer
-// -----------------------------------
+  rl.close();
+}
 
-console.log(completion.choices[0]?.message?.content);
+main();