diff --git a/README.md b/README.md
index 5f8a052e..895deb37 100644
--- a/README.md
+++ b/README.md
@@ -142,7 +142,8 @@ Then, run the following commands to get the project on your local environment:
 
 #### Deploying from scratch
 
-[📺 Live stream: Deploying from scratch](https://youtu.be/wgSnkxGH2Sk?si=C4zAbLKhK3LoAS43)
+[📺 Live stream: Deploying from scratch in CodeSpaces](https://youtu.be/TORUsRNimM0)
+[📺 Live stream: Deploying from scratch in Windows 11](https://youtu.be/wgSnkxGH2Sk?si=C4zAbLKhK3LoAS43)
 
 > **Important**:
 > Ensure Docker is running before running any `azd` provisioning / deployment commands.
@@ -380,4 +381,4 @@ To reduce costs, you can switch to free SKUs for various services, but those SKU
 
 **_Question_**: Why do we need to break up the PDFs into chunks when Azure AI Search supports searching large documents?
 
-**_Answer_**: Chunking allows us to limit the amount of information we send to OpenAI due to token limits. By breaking up the content, it allows us to easily find potential chunks of text that we can inject into OpenAI. The method of chunking we use leverages a sliding window of text such that sentences that end one chunk will start the next. This allows us to reduce the chance of losing the context of the text.
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+**_Answer_**: Chunking allows us to limit the amount of information we send to OpenAI due to token limits. By breaking up the content, it allows us to easily find potential chunks of text that we can inject into OpenAI. The method of chunking we use leverages a sliding window of text such that sentences that end one chunk will start the next. This allows us to reduce the chance of losing the context of the text.