Update learn-pr/advocates/introduction-azure-copilot-agents/includes/4-optimization-agent.md

Author: ttorble

learn-pr/advocates/introduction-azure-copilot-agents/includes/4-optimization-agent.md

@@ -8,7 +8,7 @@ The Optimization agent analyzes monitoring data and Azure's built-in recommendat
 - The Optimization agent applies expert rules and AI models to identify inefficiencies. The Optimization agent aggregates and surfaces recommendations from Azure Advisor in natural language, often combining them with context. 
 - The Optimization agent also uses historical usage patterns to find idle periods. For example, the Optimization agent might determine that a development VM is only used between 9am and 5pm weekdays. It might provide a suggestion that you configure scheduling it to shut down during off-hours to save money. Similarly, if the Optimization agent determines a database hasn't been queried in a month, the agent might recommend scaling the database down or even removing it.
 - The Optimization agent can generate the exact Azure CLI or PowerShell commands, or ARM/Terraform code changes, to apply a given recommendation. For example, if it recommends resizing a VM from D4 to D2, it provides the CLI command to change the SKU. 
-- The Optimization agent also integrates with Azure Cost Management and billing data. You can ask the Optimization agent high-level questions like "Why was our Azure bill high last month?". The agent is able to break down the costs and pinpoint unusual increases. The Optimization agent is able to summarize cost drivers and map them to technical causes and potential mitigations.
+- The Optimization agent also integrates with Microsoft Cost Management and billing data. You can ask the Optimization agent high-level questions like "Why was our Azure bill high last month?". The agent is able to break down the costs and pinpoint unusual increases. The Optimization agent is able to summarize cost drivers and map them to technical causes and potential mitigations.
 - The Optimization agent can determine where performance bottlenecks exist. If a certain resource is consistently hitting resource constraints, the Optimization agent flags that as a risk to performance and suggest scaling up or enabling a performance tier that can handle the load. Before recommending that you downsize a resource, the agent checks that such a change won't degrade service health. 
 - The Optimization agent can help plan for growth. For instance, if it notices a trend of increasing load on a service, it could recommend scaling out before it becomes an issue.