making AI insight lowercase

Author: anupras-mohapatra-arm

content/learning-paths/servers-and-cloud-computing/performix-agentic-dynamic-insights-codex/_index.md

@@ -11,7 +11,7 @@ learning_objectives:
     - Configure the Arm Performix MCP server for the Codex extension in VS Code.
     - Verify that Codex can access Arm Performix recipes, targets, and runs.
     - Create or select a supported Code Hotspots run.
-    - Generate an AI Insight and validate its recommendations against profile evidence.
+    - Generate an AI insight and validate its recommendations against profile evidence.
 
 prerequisites:
     - Arm Performix version 2026.2.5 or later installed. For installation and target setup instructions, see the [Arm Performix install guide](/install-guides/performix/).
@@ -55,10 +55,10 @@ generated_summary_faq:
       enough samples.
   - question: How do I make sure Codex uses the exact profile I want?
     answer: >-
-      Request the AI Insight using the run ID. If you don’t know it, ask Codex to list supported
+      Request the AI insight using the run ID. If you don’t know it, ask Codex to list supported
       Code Hotspots runs with IDs, targets, workloads, and creation times. Then, select the correct
       ID.
-  - question: What should I check to validate an AI Insight against the profile?
+  - question: What should I check to validate an AI insight against the profile?
     answer: >-
       Open the same run in Arm Performix and inspect the **Flame graph**, **Functions**, **Call Stack**,
       **Source**, and **Disassembly** views. Confirm that the cited functions, call paths, and sample percentages

content/learning-paths/servers-and-cloud-computing/performix-agentic-dynamic-insights-codex/configure_mcp_codex.md

@@ -123,7 +123,7 @@ If Codex returns Performix recipes or runs, the end-to-end connection works. An
 Next, ask Codex to identify runs that support the insight workflow:
 
 ```text
-List the Arm Performix Code Hotspots runs that can be used to generate an AI Insight. Include the run ID and enough workload and target details for me to choose the correct run.
+List the Arm Performix Code Hotspots runs that can be used to generate an AI insight. Include the run ID and enough workload and target details for me to choose the correct run.
 ```
 
 Record the run ID you want to analyze. A run name can be changed and might not be unique, so use the run ID in later prompts.
@@ -171,7 +171,7 @@ Use the Arm Performix MCP server to list the available Arm Performix runs.
 For a specific run:
 
 ```text
-Use Arm Performix to generate an AI Insight for run ID "<run-id>".
+Use Arm Performix to generate an AI insight for run ID "<run-id>".
 ```
 
 If you have several MCP servers, an ambiguous prompt such as `give me insights` might not select Arm Performix.

content/learning-paths/servers-and-cloud-computing/performix-agentic-dynamic-insights-codex/generate_ai_insights.md

@@ -22,7 +22,7 @@ Use Arm Performix to list supported Code Hotspots runs. Include the run ID, targ
 Request an insight for the selected run:
 
 ```text
-Use Arm Performix to generate an AI Insight for run ID "<run-id>". Identify the highest-impact finding, cite the profile evidence that supports it, and suggest the first investigation or optimization step. State any missing evidence or uncertainty.
+Use Arm Performix to generate an AI insight for run ID "<run-id>". Identify the highest-impact finding, cite the profile evidence that supports it, and suggest the first investigation or optimization step. State any missing evidence or uncertainty.
 ```
 
 Replace `<run-id>` with the ID returned by Arm Performix.

content/learning-paths/servers-and-cloud-computing/performix-agentic-dynamic-insights-codex/open-in-performix.md

@@ -24,6 +24,6 @@ For a before-and-after comparison, keep the workload, target, input, thread coun
 
 ## What you've accomplished
 
-You've now configured the Arm Performix MCP server, selected or created a Code Hotspots run, generated an AI Insight, and checked its recommendation against the profile. 
+You've now configured the Arm Performix MCP server, selected or created a Code Hotspots run, generated an AI insight, and checked its recommendation against the profile.
 
 You can continue with the [Arm Performix getting-started video](https://youtu.be/_eX8ZpNT0kc) to explore the graphical workflow.