.NET: Address Feedback on StateBag feature branch PR (#3910 )

* Address Feedback on statebag feature branch PR * Update dotnet/src/Microsoft.Agents.AI.DurableTask/CHANGELOG.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Address PR comments --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Merge branch 'main' into feature-session-statebag
2026-06-16 21:04:09 +08:00 · 2026-02-13 11:01:06 +00:00 · 2026-02-12 19:57:40 +00:00 · 2026-02-12 19:30:29 +00:00 · 2026-02-12 18:31:20 +00:00 · 2026-02-12 17:36:36 +00:00
919 changed files with 18517 additions and 10661 deletions
@@ -30,9 +30,11 @@ from dataclasses import dataclass
 # =============================================================================
 ENFORCED_MODULES: set[str] = {
    "packages.azure-ai.agent_framework_azure_ai",
+    "packages.core.agent_framework",
+    "packages.core.agent_framework._workflows",
+    "packages.purview.agent_framework_purview",
    # Add more modules here as coverage improves:
-    # "packages.core.agent_framework",
-    # "packages.core.agent_framework._workflows",
+    # "packages.azure-ai-search.agent_framework_azure_ai_search",
    # "packages.anthropic.agent_framework_anthropic",
 }

@@ -53,7 +53,7 @@ Still have questions? Join our [weekly office hours](./COMMUNITY.md#public-commu
 ### ✨ **Highlights**

 - **Graph-based Workflows**: Connect agents and deterministic functions using data flows with streaming, checkpointing, human-in-the-loop, and time-travel capabilities
-  - [Python workflows](./python/samples/getting_started/workflows/) | [.NET workflows](./dotnet/samples/GettingStarted/Workflows/)
+  - [Python workflows](./python/samples/03-workflows/) | [.NET workflows](./dotnet/samples/GettingStarted/Workflows/)
 - **AF Labs**: Experimental packages for cutting-edge features including benchmarking, reinforcement learning, and research initiatives
  - [Labs directory](./python/packages/lab/)
 - **DevUI**: Interactive developer UI for agent development, testing, and debugging workflows
@@ -73,11 +73,11 @@ Still have questions? Join our [weekly office hours](./COMMUNITY.md#public-commu
 - **Python and C#/.NET Support**: Full framework support for both Python and C#/.NET implementations with consistent APIs
  - [Python packages](./python/packages/) | [.NET source](./dotnet/src/)
 - **Observability**: Built-in OpenTelemetry integration for distributed tracing, monitoring, and debugging
-  - [Python observability](./python/samples/getting_started/observability/) | [.NET telemetry](./dotnet/samples/GettingStarted/AgentOpenTelemetry/)
+  - [Python observability](./python/samples/02-agents/observability/) | [.NET telemetry](./dotnet/samples/GettingStarted/AgentOpenTelemetry/)
 - **Multiple Agent Provider Support**: Support for various LLM providers with more being added continuously
-  - [Python examples](./python/samples/getting_started/agents/) | [.NET examples](./dotnet/samples/GettingStarted/AgentProviders/)
+  - [Python examples](./python/samples/02-agents/providers/) | [.NET examples](./dotnet/samples/GettingStarted/AgentProviders/)
 - **Middleware**: Flexible middleware system for request/response processing, exception handling, and custom pipelines
-  - [Python middleware](./python/samples/getting_started/middleware/) | [.NET middleware](./dotnet/samples/GettingStarted/Agents/Agent_Step14_Middleware/)
+  - [Python middleware](./python/samples/02-agents/middleware/) | [.NET middleware](./dotnet/samples/GettingStarted/Agents/Agent_Step14_Middleware/)

 ### 💬 **We want your feedback!**

@@ -159,9 +159,9 @@ Console.WriteLine(await agent.RunAsync("Write a haiku about Microsoft Agent Fram

 ### Python

- [Getting Started with Agents](./python/samples/getting_started/agents): basic agent creation and tool usage
- [Chat Client Examples](./python/samples/getting_started/chat_client): direct chat client usage patterns
- [Getting Started with Workflows](./python/samples/getting_started/workflows): basic workflow creation and integration with agents
+- [Getting Started with Agents](./python/samples/01-get-started): progressive tutorial from hello-world to hosting
+- [Agent Concepts](./python/samples/02-agents): deep-dive samples by topic (tools, middleware, providers, etc.)
+- [Getting Started with Workflows](./python/samples/03-workflows): workflow creation and integration with agents

 ### .NET

@@ -1,3 +1,3 @@
 # Declarative Agents

-This folder contains sample agent definitions that can be run using the declarative agent support, for python see the [declarative agent python sample folder](../python/samples/getting_started/declarative/).
+This folder contains sample agent definitions that can be run using the declarative agent support, for python see the [declarative agent python sample folder](../python/samples/02-agents/declarative/).
@@ -126,4 +126,4 @@ response = await client.get_response(

 Chosen option: **"Option 2: TypedDict with Generic Type Parameters"**, because it provides full type safety, excellent IDE support with autocompletion, and allows users to extend provider-specific options for their use cases. Extended this Generic to ChatAgents in order to also properly type the options used in agent construction and run methods.

-See [typed_options.py](../../python/samples/concepts/typed_options.py) for a complete example demonstrating the usage of typed options with custom extensions.
+See [typed_options.py](../../python/samples/02-agents/typed_options.py) for a complete example demonstrating the usage of typed options with custom extensions.
@@ -33,18 +33,18 @@
    <!-- Newtonsoft.Json -->
    <PackageVersion Include="Newtonsoft.Json" Version="13.0.4" />
    <!-- System.* -->
-    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.2" />
+    <PackageVersion Include="Microsoft.Bcl.AsyncInterfaces" Version="10.0.3" />
    <PackageVersion Include="Microsoft.Bcl.HashCode" Version="6.0.0" />
    <PackageVersion Include="System.ClientModel" Version="1.8.1" />
    <PackageVersion Include="System.CodeDom" Version="10.0.0" />
    <PackageVersion Include="System.Collections.Immutable" Version="10.0.1" />
    <PackageVersion Include="System.CommandLine" Version="2.0.0-rc.2.25502.107" />
-    <PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.2" />
+    <PackageVersion Include="System.Diagnostics.DiagnosticSource" Version="10.0.3" />
    <PackageVersion Include="System.Linq.AsyncEnumerable" Version="10.0.0" />
    <PackageVersion Include="System.Net.Http.Json" Version="10.0.0" />
    <PackageVersion Include="System.Net.ServerSentEvents" Version="10.0.1" />
-    <PackageVersion Include="System.Text.Json" Version="10.0.2" />
-    <PackageVersion Include="System.Threading.Channels" Version="10.0.2" />
+    <PackageVersion Include="System.Text.Json" Version="10.0.3" />
+    <PackageVersion Include="System.Threading.Channels" Version="10.0.3" />
    <PackageVersion Include="System.Threading.Tasks.Extensions" Version="4.6.3" />
    <PackageVersion Include="System.Net.Security" Version="4.3.2" />
    <!-- OpenTelemetry -->
@@ -61,9 +61,9 @@
    <PackageVersion Include="Microsoft.AspNetCore.OpenApi" Version="10.0.0" />
    <PackageVersion Include="Swashbuckle.AspNetCore.SwaggerUI" Version="10.0.0" />
    <!-- Microsoft.Extensions.* -->
-    <PackageVersion Include="Microsoft.Extensions.AI" Version="10.2.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.2.0" />
-    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.2.0-preview.1.26063.2" />
+    <PackageVersion Include="Microsoft.Extensions.AI" Version="10.3.0" />
+    <PackageVersion Include="Microsoft.Extensions.AI.Abstractions" Version="10.3.0" />
+    <PackageVersion Include="Microsoft.Extensions.AI.OpenAI" Version="10.3.0" />
    <PackageVersion Include="Microsoft.Extensions.Caching.Memory" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.Configuration" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.Configuration.Binder" Version="10.0.0" />
@@ -71,11 +71,11 @@
    <PackageVersion Include="Microsoft.Extensions.Configuration.Json" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.Configuration.UserSecrets" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.DependencyInjection" Version="10.0.0" />
-    <PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.2" />
+    <PackageVersion Include="Microsoft.Extensions.DependencyInjection.Abstractions" Version="10.0.3" />
    <PackageVersion Include="Microsoft.Extensions.Hosting" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.Http.Resilience" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.Logging" Version="10.0.0" />
-    <PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.2" />
+    <PackageVersion Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.3" />
    <PackageVersion Include="Microsoft.Extensions.Logging.Console" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.ServiceDiscovery" Version="10.0.0" />
    <PackageVersion Include="Microsoft.Extensions.VectorData.Abstractions" Version="9.7.0" />
@@ -89,7 +89,7 @@
    <PackageVersion Include="Microsoft.SemanticKernel.Agents.AzureAI" Version="1.67.0-preview" />
    <PackageVersion Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.67.0" />
    <!-- Agent SDKs -->
-    <PackageVersion Include="GitHub.Copilot.SDK" Version="0.1.18" />
+    <PackageVersion Include="GitHub.Copilot.SDK" Version="0.1.23" />
    <PackageVersion Include="Microsoft.Agents.CopilotStudio.Client" Version="1.3.171-beta" />
    <!-- M365 Agents SDK -->
    <PackageVersion Include="AdaptiveCards" Version="3.1.0" />
@@ -25,6 +25,7 @@
      "src\\Microsoft.Agents.AI.Purview\\Microsoft.Agents.AI.Purview.csproj",
      "src\\Microsoft.Agents.AI.Workflows.Declarative.AzureAI\\Microsoft.Agents.AI.Workflows.Declarative.AzureAI.csproj",
      "src\\Microsoft.Agents.AI.Workflows.Declarative\\Microsoft.Agents.AI.Workflows.Declarative.csproj",
+      "src\\Microsoft.Agents.AI.Workflows.Generators\\Microsoft.Agents.AI.Workflows.Generators.csproj",
      "src\\Microsoft.Agents.AI.Workflows\\Microsoft.Agents.AI.Workflows.csproj",
      "src\\Microsoft.Agents.AI\\Microsoft.Agents.AI.csproj"
    ]
@@ -2,9 +2,9 @@
  <PropertyGroup>
    <!-- Central version prefix - applies to all nuget packages. -->
    <VersionPrefix>1.0.0</VersionPrefix>
-    <PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260209.1</PackageVersion>
-    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260209.1</PackageVersion>
-    <GitTag>1.0.0-preview.260209.1</GitTag>
+    <PackageVersion Condition="'$(VersionSuffix)' != ''">$(VersionPrefix)-$(VersionSuffix).260212.1</PackageVersion>
+    <PackageVersion Condition="'$(VersionSuffix)' == ''">$(VersionPrefix)-preview.260212.1</PackageVersion>
+    <GitTag>1.0.0-preview.260212.1</GitTag>

    <Configurations>Debug;Release;Publish</Configurations>
    <IsPackable>true</IsPackable>
@@ -14,7 +14,10 @@ internal static class HostAgentFactory
 {
    internal static async Task<(AIAgent, AgentCard)> CreateFoundryHostAgentAsync(string agentType, string model, string endpoint, string assistantId, IList<AITool>? tools = null)
    {
-        var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());
        PersistentAgent persistentAgent = await persistentAgentsClient.Administration.GetAgentAsync(assistantId);

        AIAgent agent = await persistentAgentsClient
@@ -24,6 +24,9 @@ internal static class ChatClientAgentFactory
        string endpoint = configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        s_deploymentName = configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");

+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
        s_azureOpenAIClient = new AzureOpenAIClient(
            new Uri(endpoint),
            new DefaultAzureCredential());
@@ -19,6 +19,9 @@ string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new In
 string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");

 // Create the AI agent with tools
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 var agent = new AzureOpenAIClient(
        new Uri(endpoint),
        new DefaultAzureCredential())
@@ -19,6 +19,9 @@ string endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new In
 string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");

 // Create the AI agent
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient azureOpenAIClient = new(
    new Uri(endpoint),
    new DefaultAzureCredential());
@@ -19,9 +19,12 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYM

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Set up an AI agent following the standard Microsoft Agent Framework pattern.
 const string JokerName = "Joker";
@@ -19,9 +19,12 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYM

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Single agent used by the orchestration to demonstrate sequential calls on the same session.
 const string WriterName = "WriterAgent";
@@ -19,9 +19,12 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYM

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Two agents used by the orchestration to demonstrate concurrent execution.
 const string PhysicistName = "PhysicistAgent";
@@ -19,9 +19,12 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYM

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Two agents used by the orchestration to demonstrate conditional logic.
 const string SpamDetectionName = "SpamDetectionAgent";
@@ -19,9 +19,12 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYM

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Single agent used by the orchestration to demonstrate human-in-the-loop workflow.
 const string WriterName = "WriterAgent";
@@ -23,9 +23,12 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYM

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Agent used by the orchestration to write content.
 const string WriterAgentName = "Writer";
@@ -25,9 +25,12 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYM

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Define three AI agents we are going to use in this application.
 AIAgent agent1 = client.GetChatClient(deploymentName).AsAIAgent("You are good at telling jokes.", "Joker");
@@ -40,9 +40,12 @@ int redisStreamTtlMinutes = int.TryParse(

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Travel Planner agent instructions - designed to produce longer responses for demonstrating streaming.
 const string TravelPlannerName = "TravelPlanner";
@@ -25,9 +25,12 @@ string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SC

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Set up an AI agent following the standard Microsoft Agent Framework pattern.
 const string JokerName = "Joker";
@@ -29,9 +29,12 @@ string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SC

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Single agent used by the orchestration to demonstrate sequential calls on the same session.
 const string WriterName = "WriterAgent";
@@ -29,9 +29,12 @@ string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SC

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Two agents used by the orchestration to demonstrate concurrent execution.
 const string PhysicistName = "PhysicistAgent";
@@ -28,9 +28,12 @@ string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SC

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Spam detection agent
 const string SpamDetectionAgentName = "SpamDetectionAgent";
@@ -29,9 +29,12 @@ string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SC

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Single agent used by the orchestration to demonstrate human-in-the-loop workflow.
 const string WriterName = "WriterAgent";
@@ -30,9 +30,12 @@ string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SC

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Agent used by the orchestration to write content.
 const string WriterAgentName = "Writer";
@@ -38,9 +38,12 @@ string dtsConnectionString = Environment.GetEnvironmentVariable("DURABLE_TASK_SC

 // Use Azure Key Credential if provided, otherwise use Azure CLI Credential.
 string? azureOpenAiKey = Environment.GetEnvironmentVariable("AZURE_OPENAI_KEY");
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient client = !string.IsNullOrEmpty(azureOpenAiKey)
    ? new AzureOpenAIClient(new Uri(endpoint), new AzureKeyCredential(azureOpenAiKey))
-    : new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential());
+    : new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential());

 // Travel Planner agent instructions - designed to produce longer responses for demonstrating streaming.
 const string TravelPlannerName = "TravelPlanner";
@@ -26,9 +26,12 @@ AgentCard agentCard = await agentCardResolver.GetAgentCardAsync();
 AIAgent a2aAgent = agentCard.AsAIAgent();

 // Create the main agent, and provide the a2a agent skills as a function tools.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(
        instructions: "You are a helpful assistant that helps people with travel planning.",
@@ -19,6 +19,9 @@ string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"]
    ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");

 // Create the AI agent
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 ChatClient chatClient = new AzureOpenAIClient(
        new Uri(endpoint),
        new DefaultAzureCredential())
@@ -74,6 +74,9 @@ AITool[] tools =
 ];

 // Create the AI agent with tools
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 ChatClient chatClient = new AzureOpenAIClient(
        new Uri(endpoint),
        new DefaultAzureCredential())
@@ -19,6 +19,9 @@ string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"]
    ?? throw new InvalidOperationException("AZURE_OPENAI_DEPLOYMENT_NAME is not set.");

 // Create the AI agent
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 ChatClient chatClient = new AzureOpenAIClient(
        new Uri(endpoint),
        new DefaultAzureCredential())
@@ -52,6 +52,9 @@ AITool[] tools = [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(Approv
 #pragma warning restore MEAI001

 // Create base agent
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 ChatClient openAIChatClient = new AzureOpenAIClient(
        new Uri(endpoint),
        new DefaultAzureCredential())
@@ -29,6 +29,9 @@ string deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"]
 var jsonOptions = app.Services.GetRequiredService<IOptions<Microsoft.AspNetCore.Http.Json.JsonOptions>>().Value;

 // Create base agent
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 ChatClient chatClient = new AzureOpenAIClient(
        new Uri(endpoint),
        new DefaultAzureCredential())
@@ -110,7 +110,10 @@ static async Task<string> GetWeatherAsync([Description("The location to get the
    return $"The weather in {location} is cloudy with a high of 15°C.";
 }

-using var instrumentedChatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+using var instrumentedChatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
    .GetChatClient(deploymentName)
        .AsIChatClient() // Converts a native OpenAI SDK ChatClient into a Microsoft.Extensions.AI.IChatClient
        .AsBuilder()
@@ -17,11 +17,14 @@ string? apiKey = Environment.GetEnvironmentVariable("ANTHROPIC_API_KEY");
 const string JokerInstructions = "You are good at telling jokes.";
 const string JokerName = "JokerAgent";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 using AnthropicClient client = (resource is null)
    ? new AnthropicClient() { ApiKey = apiKey ?? throw new InvalidOperationException("ANTHROPIC_API_KEY is required when no ANTHROPIC_RESOURCE is provided") }  // If no resource is provided, use Anthropic public API
    : (apiKey is not null)
        ? new AnthropicFoundryClient(new AnthropicFoundryApiKeyCredentials(apiKey, resource)) // If an apiKey is provided, use Foundry with ApiKey authentication
-        : new AnthropicFoundryClient(new AnthropicFoundryIdentityTokenCredentials(new AzureCliCredential(), resource, ["https://ai.azure.com/.default"])); // Otherwise, use Foundry with Azure TokenCredential authentication
+        : new AnthropicFoundryClient(new AnthropicFoundryIdentityTokenCredentials(new DefaultAzureCredential(), resource, ["https://ai.azure.com/.default"])); // Otherwise, use Foundry with Azure TokenCredential authentication

 AIAgent agent = client.AsAIAgent(model: deploymentName, instructions: JokerInstructions, name: JokerName);

@@ -13,7 +13,10 @@ const string JokerName = "Joker";
 const string JokerInstructions = "You are good at telling jokes.";

 // Get a client to create/retrieve server side agents with.
-var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());

 // You can create a server side persistent agent with the Azure.AI.Agents.Persistent SDK.
 var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
@@ -13,7 +13,10 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_D
 const string JokerName = "JokerAgent";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-var aiProjectClient = new AIProjectClient(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+var aiProjectClient = new AIProjectClient(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent you want to create. (Prompt Agent in this case)
 var agentVersionCreationOptions = new AgentVersionCreationOptions(new PromptAgentDefinition(model: deploymentName) { Instructions = "You are good at telling jokes." });
@@ -19,8 +19,11 @@ var model = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_MODEL_DEPLOYMENT")
 var clientOptions = new OpenAIClientOptions() { Endpoint = new Uri(endpoint) };

 // Create the OpenAI client with either an API key or Azure CLI credential.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 OpenAIClient client = string.IsNullOrWhiteSpace(apiKey)
-    ? new OpenAIClient(new BearerTokenPolicy(new AzureCliCredential(), "https://ai.azure.com/.default"), clientOptions)
+    ? new OpenAIClient(new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"), clientOptions)
    : new OpenAIClient(new ApiKeyCredential(apiKey), clientOptions);

 AIAgent agent = client
@@ -10,9 +10,12 @@ using OpenAI.Chat;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetChatClient(deploymentName)
     .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

@@ -10,9 +10,12 @@ using OpenAI.Responses;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetResponsesClient(deploymentName)
     .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

@@ -6,6 +6,7 @@

 using System.Runtime.CompilerServices;
 using System.Text.Json;
+using System.Text.Json.Serialization;
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 using SampleApp;
@@ -28,21 +29,23 @@ namespace SampleApp
    {
        public override string? Name => "UpperCaseParrotAgent";

+        public readonly ChatHistoryProvider ChatHistoryProvider = new InMemoryChatHistoryProvider();
+
        protected override ValueTask<AgentSession> CreateSessionCoreAsync(CancellationToken cancellationToken = default)
            => new(new CustomAgentSession());

-        protected override JsonElement SerializeSessionCore(AgentSession session, JsonSerializerOptions? jsonSerializerOptions = null)
+        protected override ValueTask<JsonElement> SerializeSessionCoreAsync(AgentSession session, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
        {
            if (session is not CustomAgentSession typedSession)
            {
                throw new ArgumentException($"The provided session is not of type {nameof(CustomAgentSession)}.", nameof(session));
            }

-            return typedSession.Serialize(jsonSerializerOptions);
+            return new(JsonSerializer.SerializeToElement(typedSession, jsonSerializerOptions));
        }

        protected override ValueTask<AgentSession> DeserializeSessionCoreAsync(JsonElement serializedState, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
-            => new(new CustomAgentSession(serializedState, jsonSerializerOptions));
+            => new(serializedState.Deserialize<CustomAgentSession>(jsonSerializerOptions)!);

        protected override async Task<AgentResponse> RunCoreAsync(IEnumerable<ChatMessage> messages, AgentSession? session = null, AgentRunOptions? options = null, CancellationToken cancellationToken = default)
        {
@@ -56,17 +59,14 @@ namespace SampleApp

            // Get existing messages from the store
            var invokingContext = new ChatHistoryProvider.InvokingContext(this, session, messages);
-            var storeMessages = await typedSession.ChatHistoryProvider.InvokingAsync(invokingContext, cancellationToken);
+            var userAndChatHistoryMessages = await this.ChatHistoryProvider.InvokingAsync(invokingContext, cancellationToken);

            // Clone the input messages and turn them into response messages with upper case text.
            List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.Name).ToList();

            // Notify the session of the input and output messages.
-            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, messages)
-            {
-                ResponseMessages = responseMessages
-            };
-            await typedSession.ChatHistoryProvider.InvokedAsync(invokedContext, cancellationToken);
+            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, userAndChatHistoryMessages, responseMessages);
+            await this.ChatHistoryProvider.InvokedAsync(invokedContext, cancellationToken);

            return new AgentResponse
            {
@@ -88,17 +88,14 @@ namespace SampleApp

            // Get existing messages from the store
            var invokingContext = new ChatHistoryProvider.InvokingContext(this, session, messages);
-            var storeMessages = await typedSession.ChatHistoryProvider.InvokingAsync(invokingContext, cancellationToken);
+            var userAndChatHistoryMessages = await this.ChatHistoryProvider.InvokingAsync(invokingContext, cancellationToken);

            // Clone the input messages and turn them into response messages with upper case text.
            List<ChatMessage> responseMessages = CloneAndToUpperCase(messages, this.Name).ToList();

            // Notify the session of the input and output messages.
-            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, messages)
-            {
-                ResponseMessages = responseMessages
-            };
-            await typedSession.ChatHistoryProvider.InvokedAsync(invokedContext, cancellationToken);
+            var invokedContext = new ChatHistoryProvider.InvokedContext(this, session, userAndChatHistoryMessages, responseMessages);
+            await this.ChatHistoryProvider.InvokedAsync(invokedContext, cancellationToken);

            foreach (var message in responseMessages)
            {
@@ -140,15 +137,16 @@ namespace SampleApp
        /// <summary>
        /// A session type for our custom agent that only supports in memory storage of messages.
        /// </summary>
-        internal sealed class CustomAgentSession : InMemoryAgentSession
+        internal sealed class CustomAgentSession : AgentSession
        {
-            internal CustomAgentSession() { }
+            internal CustomAgentSession()
+            {
+            }

-            internal CustomAgentSession(JsonElement serializedSessionState, JsonSerializerOptions? jsonSerializerOptions = null)
-                : base(serializedSessionState, jsonSerializerOptions) { }
-
-            internal new JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null)
-                => base.Serialize(jsonSerializerOptions);
+            [JsonConstructor]
+            internal CustomAgentSession(AgentSessionStateBag stateBag) : base(stateBag)
+            {
+            }
        }
    }
 }
@@ -20,7 +20,10 @@ var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_E
 // Replace this with a vector store implementation of your choice that can persist the chat history long term.
 VectorStore vectorStore = new InMemoryVectorStore(new InMemoryVectorStoreOptions()
 {
-    EmbeddingGenerator = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+    // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+    // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+    // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+    EmbeddingGenerator = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
        .GetEmbeddingClient(embeddingDeploymentName)
        .AsIEmbeddingGenerator()
 });
@@ -28,22 +31,27 @@ VectorStore vectorStore = new InMemoryVectorStore(new InMemoryVectorStoreOptions
 // Create the agent and add the ChatHistoryMemoryProvider to store chat messages in the vector store.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new ChatHistoryMemoryProvider(
+        AIContextProviders = [new ChatHistoryMemoryProvider(
            vectorStore,
            collectionName: "chathistory",
            vectorDimensions: 3072,
-            // Configure the scope values under which chat messages will be stored.
-            // In this case, we are using a fixed user ID and a unique session ID for each new session.
-            storageScope: new() { UserId = "UID1", SessionId = Guid.NewGuid().ToString() },
-            // Configure the scope which would be used to search for relevant prior messages.
-            // In this case, we are searching for any messages for the user across all sessions.
-            searchScope: new() { UserId = "UID1" }))
+            // Callback to configure the initial state of the ChatHistoryMemoryProvider.
+            // The ChatHistoryMemoryProvider stores its state in the AgentSession and this callback
+            // will be called whenever the ChatHistoryMemoryProvider cannot find existing state in the session,
+            // typically the first time it is used with a new session.
+            session => new ChatHistoryMemoryProvider.State(
+                // Configure the scope values under which chat messages will be stored.
+                // In this case, we are using a fixed user ID and a unique session ID for each new session.
+                storageScope: new() { UserId = "UID1", SessionId = Guid.NewGuid().ToString() },
+                // Configure the scope which would be used to search for relevant prior messages.
+                // In this case, we are searching for any messages for the user across all sessions.
+                searchScope: new() { UserId = "UID1" }))]
    });

 // Start a new session for the agent conversation.
@@ -24,27 +24,31 @@ using HttpClient mem0HttpClient = new();
 mem0HttpClient.BaseAddress = new Uri(mem0ServiceUri);
 mem0HttpClient.DefaultRequestHeaders.Authorization = new AuthenticationHeaderValue("Token", mem0ApiKey);

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(new ChatClientAgentOptions()
    {
        ChatOptions = new() { Instructions = "You are a friendly travel assistant. Use known memories about the user when responding, and do not invent details." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(ctx.SerializedState.ValueKind is not JsonValueKind.Null and not JsonValueKind.Undefined
-            // If each session should have its own Mem0 scope, you can create a new id per session here:
-            // ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ThreadId = Guid.NewGuid().ToString() })
-            // In this case we are storing memories scoped by application and user instead so that memories are retained across threads.
-            ? new Mem0Provider(mem0HttpClient, new Mem0ProviderScope() { ApplicationId = "getting-started-agents", UserId = "sample-user" })
-            // For cases where we are restoring from serialized state:
-            : new Mem0Provider(mem0HttpClient, ctx.SerializedState, ctx.JsonSerializerOptions))
+        // The stateInitializer can be used to customize the Mem0 scope per session and it will be called each time a session
+        // is encountered by the Mem0Provider that does not already have Mem0Provider state stored on the session.
+        // If each session should have its own Mem0 scope, you can create a new id per session via the stateInitializer, e.g.:
+        // new Mem0Provider(mem0HttpClient, stateInitializer: _ => new(new Mem0ProviderScope() { ThreadId = Guid.NewGuid().ToString() }))
+        // In our case we are storing memories scoped by application and user instead so that memories are retained across threads.
+        AIContextProviders = [new Mem0Provider(mem0HttpClient, stateInitializer: _ => new(new Mem0ProviderScope() { ApplicationId = "getting-started-agents", UserId = "sample-user" }))]
    });

 AgentSession session = await agent.CreateSessionAsync();

 // Clear any existing memories for this scope to demonstrate fresh behavior.
-Mem0Provider mem0Provider = session.GetService<Mem0Provider>()!;
-await mem0Provider.ClearStoredMemoriesAsync();
+// Note that the ClearStoredMemoriesAsync method will clear memories
+// using the scope stored in the session, or provided via the stateInitializer.
+Mem0Provider mem0Provider = agent.GetService<Mem0Provider>()!;
+await mem0Provider.ClearStoredMemoriesAsync(session);

 Console.WriteLine(await agent.RunAsync("Hi there! My name is Taylor and I'm planning a hiking trip to Patagonia in November.", session));
 Console.WriteLine(await agent.RunAsync("I'm travelling with my sister and we love finding scenic viewpoints.", session));
@@ -55,7 +59,7 @@ await Task.Delay(TimeSpan.FromSeconds(2));
 Console.WriteLine(await agent.RunAsync("What do you already know about my upcoming trip?", session));

 Console.WriteLine("\n>> Serialize and deserialize the session to demonstrate persisted state\n");
-JsonElement serializedSession = agent.SerializeSession(session);
+JsonElement serializedSession = await agent.SerializeSessionAsync(session);
 AgentSession restoredSession = await agent.DeserializeSessionAsync(serializedSession);
 Console.WriteLine(await agent.RunAsync("Can you recap the personal details you remember?", restoredSession));

@@ -18,9 +18,12 @@ using SampleApp;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 ChatClient chatClient = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName);

 // Create the agent and provide a factory to add our custom memory component to
@@ -33,7 +36,7 @@ ChatClient chatClient = new AzureOpenAIClient(
 AIAgent agent = chatClient.AsAIAgent(new ChatClientAgentOptions()
 {
    ChatOptions = new() { Instructions = "You are a friendly assistant. Always address the user by their name." },
-    AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new UserInfoMemory(chatClient.AsIChatClient(), ctx.SerializedState, ctx.JsonSerializerOptions))
+    AIContextProviders = [new UserInfoMemory(chatClient.AsIChatClient())]
 });

 // Create a new session for the conversation.
@@ -47,7 +50,7 @@ Console.WriteLine(await agent.RunAsync("My name is Ruaidhrí", session));
 Console.WriteLine(await agent.RunAsync("I am 20 years old", session));

 // We can serialize the session. The serialized state will include the state of the memory component.
-JsonElement sesionElement = agent.SerializeSession(session);
+JsonElement sesionElement = await agent.SerializeSessionAsync(session);

 Console.WriteLine("\n>> Use deserialized session with previously created memories\n");

@@ -55,10 +58,10 @@ Console.WriteLine("\n>> Use deserialized session with previously created memorie
 var deserializedSession = await agent.DeserializeSessionAsync(sesionElement);
 Console.WriteLine(await agent.RunAsync("What is my name and age?", deserializedSession));

-Console.WriteLine("\n>> Read memories from memory component\n");
+Console.WriteLine("\n>> Read memories using memory component\n");

-// It's possible to access the memory component via the session's GetService method.
-var userInfo = deserializedSession.GetService<UserInfoMemory>()?.UserInfo;
+// It's possible to access the memory component via the agent's GetService method.
+var userInfo = agent.GetService<UserInfoMemory>()?.GetUserInfo(deserializedSession);

 // Output the user info that was captured by the memory component.
 Console.WriteLine($"MEMORY - User Name: {userInfo?.UserName}");
@@ -66,12 +69,12 @@ Console.WriteLine($"MEMORY - User Age: {userInfo?.UserAge}");

 Console.WriteLine("\n>> Use new session with previously created memories\n");

-// It is also possible to set the memories in a memory component on an individual session.
+// It is also possible to set the memories using a memory component on an individual session.
 // This is useful if we want to start a new session, but have it share the same memories as a previous session.
 var newSession = await agent.CreateSessionAsync();
-if (userInfo is not null && newSession.GetService<UserInfoMemory>() is UserInfoMemory newSessionMemory)
+if (userInfo is not null && agent.GetService<UserInfoMemory>() is UserInfoMemory newSessionMemory)
 {
-    newSessionMemory.UserInfo = userInfo;
+    newSessionMemory.SetUserInfo(newSession, userInfo);
 }

 // Invoke the agent and output the text result.
@@ -86,28 +89,27 @@ namespace SampleApp
    internal sealed class UserInfoMemory : AIContextProvider
    {
        private readonly IChatClient _chatClient;
+        private readonly Func<AgentSession?, UserInfo> _stateInitializer;

-        public UserInfoMemory(IChatClient chatClient, UserInfo? userInfo = null)
+        public UserInfoMemory(IChatClient chatClient, Func<AgentSession?, UserInfo>? stateInitializer = null)
        {
            this._chatClient = chatClient;
-            this.UserInfo = userInfo ?? new UserInfo();
+            this._stateInitializer = stateInitializer ?? (_ => new UserInfo());
        }

-        public UserInfoMemory(IChatClient chatClient, JsonElement serializedState, JsonSerializerOptions? jsonSerializerOptions = null)
-        {
-            this._chatClient = chatClient;
+        public UserInfo GetUserInfo(AgentSession session)
+            => session.StateBag.GetValue<UserInfo>(nameof(UserInfoMemory)) ?? new UserInfo();

-            this.UserInfo = serializedState.ValueKind == JsonValueKind.Object ?
-                serializedState.Deserialize<UserInfo>(jsonSerializerOptions)! :
-                new UserInfo();
-        }
-
-        public UserInfo UserInfo { get; set; }
+        public void SetUserInfo(AgentSession session, UserInfo userInfo)
+            => session.StateBag.SetValue(nameof(UserInfoMemory), userInfo);

        protected override async ValueTask InvokedCoreAsync(InvokedContext context, CancellationToken cancellationToken = default)
        {
+            var userInfo = context.Session?.StateBag.GetValue<UserInfo>(nameof(UserInfoMemory))
+                ?? this._stateInitializer.Invoke(context.Session);
+
            // Try and extract the user name and age from the message if we don't have it already and it's a user message.
-            if ((this.UserInfo.UserName is null || this.UserInfo.UserAge is null) && context.RequestMessages.Any(x => x.Role == ChatRole.User))
+            if ((userInfo.UserName is null || userInfo.UserAge is null) && context.RequestMessages.Any(x => x.Role == ChatRole.User))
            {
                var result = await this._chatClient.GetResponseAsync<UserInfo>(
                    context.RequestMessages,
@@ -117,36 +119,43 @@ namespace SampleApp
                    },
                    cancellationToken: cancellationToken);

-                this.UserInfo.UserName ??= result.Result.UserName;
-                this.UserInfo.UserAge ??= result.Result.UserAge;
+                userInfo.UserName ??= result.Result.UserName;
+                userInfo.UserAge ??= result.Result.UserAge;
            }
+
+            context.Session?.StateBag.SetValue(nameof(UserInfoMemory), userInfo);
        }

        protected override ValueTask<AIContext> InvokingCoreAsync(InvokingContext context, CancellationToken cancellationToken = default)
        {
+            var inputContext = context.AIContext;
+            var userInfo = context.Session?.StateBag.GetValue<UserInfo>(nameof(UserInfoMemory))
+                ?? this._stateInitializer.Invoke(context.Session);
+
            StringBuilder instructions = new();
+            if (!string.IsNullOrEmpty(inputContext.Instructions))
+            {
+                instructions.AppendLine(inputContext.Instructions);
+            }

            // If we don't already know the user's name and age, add instructions to ask for them, otherwise just provide what we have to the context.
            instructions
                .AppendLine(
-                    this.UserInfo.UserName is null ?
+                    userInfo.UserName is null ?
                        "Ask the user for their name and politely decline to answer any questions until they provide it." :
-                        $"The user's name is {this.UserInfo.UserName}.")
+                        $"The user's name is {userInfo.UserName}.")
                .AppendLine(
-                    this.UserInfo.UserAge is null ?
+                    userInfo.UserAge is null ?
                        "Ask the user for their age and politely decline to answer any questions until they provide it." :
-                        $"The user's age is {this.UserInfo.UserAge}.");
+                        $"The user's age is {userInfo.UserAge}.");

            return new ValueTask<AIContext>(new AIContext
            {
-                Instructions = instructions.ToString()
+                Instructions = instructions.ToString(),
+                Messages = inputContext.Messages,
+                Tools = inputContext.Tools
            });
        }
-
-        public override JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null)
-        {
-            return JsonSerializer.SerializeToElement(this.UserInfo, jsonSerializerOptions);
-        }
    }

    internal sealed class UserInfo
@@ -5,7 +5,6 @@
 using Microsoft.Agents.AI;
 using Microsoft.Extensions.AI;
 using OpenAI;
-using OpenAI.Responses;

 var apiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY") ?? throw new InvalidOperationException("OPENAI_API_KEY is not set.");
 var model = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-5";
@@ -15,14 +14,10 @@ var client = new OpenAIClient(apiKey)
        .AsIChatClient().AsBuilder()
        .ConfigureOptions(o =>
        {
-            o.RawRepresentationFactory = _ => new CreateResponseOptions()
+            o.Reasoning = new()
            {
-                ReasoningOptions = new()
-                {
-                    ReasoningEffortLevel = ResponseReasoningEffortLevel.Medium,
-                    // Verbosity requires OpenAI verified Organization
-                    ReasoningSummaryVerbosity = ResponseReasoningSummaryVerbosity.Detailed
-                }
+                Effort = ReasoningEffort.Medium,
+                Output = ReasoningOutput.Full,
            };
        }).Build();

@@ -18,9 +18,12 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
 var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME") ?? "text-embedding-3-large";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient azureOpenAIClient = new(
    new Uri(endpoint),
-    new AzureCliCredential());
+    new DefaultAzureCredential());

 // Create an In-Memory vector store that uses the Azure OpenAI embedding model to generate embeddings.
 VectorStore vectorStore = new InMemoryVectorStore(new()
@@ -62,12 +65,16 @@ AIAgent agent = azureOpenAIClient
    .AsAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions)),
-        // Since we are using ChatCompletion which stores chat history locally, we can also add a message removal policy
+        AIContextProviders = [new TextSearchProvider(SearchAdapter, textSearchOptions)],
+        // Since we are using ChatCompletion which stores chat history locally, we can also add a message filter
        // that removes messages produced by the TextSearchProvider before they are added to the chat history, so that
        // we don't bloat chat history with all the search result messages.
-        ChatHistoryProviderFactory = (ctx, ct) => new ValueTask<ChatHistoryProvider>(new InMemoryChatHistoryProvider(ctx.SerializedState, ctx.JsonSerializerOptions)
-            .WithAIContextProviderMessageRemoval()),
+        // By default the chat history provider will store all messages, except for those that came from chat history in the first place.
+        // We also want to maintain that exclusion here.
+        ChatHistoryProvider = new InMemoryChatHistoryProvider(new InMemoryChatHistoryProviderOptions
+        {
+            StorageInputMessageFilter = messages => messages.Where(m => m.GetAgentRequestMessageSourceType() != AgentRequestMessageSourceType.AIContextProvider && m.GetAgentRequestMessageSourceType() != AgentRequestMessageSourceType.ChatHistory)
+        }),
    });

 AgentSession session = await agent.CreateSessionAsync();
@@ -19,9 +19,12 @@ var embeddingDeploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_E
 var afOverviewUrl = "https://github.com/MicrosoftDocs/semantic-kernel-docs/blob/main/agent-framework/overview/agent-framework-overview.md";
 var afMigrationUrl = "https://raw.githubusercontent.com/MicrosoftDocs/semantic-kernel-docs/refs/heads/main/agent-framework/migration-guide/from-semantic-kernel/index.md";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AzureOpenAIClient azureOpenAIClient = new(
    new Uri(endpoint),
-    new AzureCliCredential());
+    new DefaultAzureCredential());

 // Create a Qdrant vector store that uses the Azure OpenAI embedding model to generate embeddings.
 QdrantClient client = new("localhost");
@@ -71,7 +74,7 @@ AIAgent agent = azureOpenAIClient
    .AsAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are a helpful support specialist for the Microsoft Agent Framework. Answer questions using the provided context and cite the source document when available. Keep responses brief." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(SearchAdapter, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions))
+        AIContextProviders = [new TextSearchProvider(SearchAdapter, textSearchOptions)]
    });

 AgentSession session = await agent.CreateSessionAsync();
@@ -22,14 +22,17 @@ TextSearchProviderOptions textSearchOptions = new()
    RecentMessageMemoryLimit = 6,
 };

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are a helpful support specialist for Contoso Outdoors. Answer questions using the provided context and cite the source document when available." },
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new TextSearchProvider(MockSearchAsync, ctx.SerializedState, ctx.JsonSerializerOptions, textSearchOptions))
+        AIContextProviders = [new TextSearchProvider(MockSearchAsync, textSearchOptions)]
    });

 AgentSession session = await agent.CreateSessionAsync();
@@ -15,9 +15,12 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOIN
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create an AI Project client and get an OpenAI client that works with the foundry service.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIProjectClient aiProjectClient = new(
    new Uri(endpoint),
-    new AzureCliCredential());
+    new DefaultAzureCredential());
 OpenAIClient openAIClient = aiProjectClient.GetProjectOpenAIClient();

 // Upload the file that contains the data to be used for RAG to the Foundry service.
@@ -10,9 +10,12 @@ using OpenAI.Chat;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

@@ -10,9 +10,12 @@ using OpenAI.Chat;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

@@ -18,9 +18,12 @@ static string GetWeather([Description("The location to get the weather for.")] s
    => $"The weather in {location} is cloudy with a high of 15°C.";

 // Create the chat client and agent, and provide the function tool to the agent.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(instructions: "You are a helpful assistant", tools: [AIFunctionFactory.Create(GetWeather)]);

@@ -23,9 +23,12 @@ static string GetWeather([Description("The location to get the weather for.")] s

 // Create the chat client and agent.
 // Note that we are wrapping the function tool with ApprovalRequiredAIFunction to require user approval before invoking it.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(instructions: "You are a helpful assistant", tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]);

@@ -15,9 +15,12 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create chat client to be used by chat client agents.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 ChatClient chatClient = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
        .GetChatClient(deploymentName);

 // Create the ChatClientAgent with the specified name and instructions.
@@ -12,9 +12,12 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create the agent
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

@@ -25,7 +28,7 @@ AgentSession session = await agent.CreateSessionAsync();
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session));

 // Serialize the session state to a JsonElement, so it can be stored for later use.
-JsonElement serializedSession = agent.SerializeSession(session);
+JsonElement serializedSession = await agent.SerializeSessionAsync(session);

 // Save the serialized session to a temporary file (for demonstration purposes).
 string tempFilePath = Path.GetTempFileName();
@@ -3,7 +3,7 @@
 #pragma warning disable CA1869 // Cache and reuse 'JsonSerializerOptions' instances

 // This sample shows how to create and use a simple AI agent with custom ChatHistoryProvider that stores chat history in a custom storage location.
-// The state of the custom ChatHistoryProvider (SessionDbKey) is stored with the agent session, so that when the session is resumed later,
+// The state of the custom ChatHistoryProvider (SessionDbKey) is stored in the AgentSession's StateBag, so that when the session is resumed later,
 // the chat history can be retrieved from the custom storage location.

 using System.Text.Json;
@@ -25,19 +25,19 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT
 VectorStore vectorStore = new InMemoryVectorStore();

 // Create the agent
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
-        ChatHistoryProviderFactory = (ctx, ct) => new ValueTask<ChatHistoryProvider>(
-            // Create a new ChatHistoryProvider for this agent that stores chat history in a vector store.
-            // Each session must get its own copy of the VectorChatHistoryProvider, since the provider
-            // also contains the id that the chat history is stored under.
-            new VectorChatHistoryProvider(vectorStore, ctx.SerializedState, ctx.JsonSerializerOptions))
+        // Create a new ChatHistoryProvider for this agent that stores chat history in a vector store.
+        ChatHistoryProvider = new VectorChatHistoryProvider(vectorStore)
    });

 // Start a new session for the agent conversation.
@@ -49,7 +49,7 @@ Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session
 // Serialize the session state, so it can be stored for later use.
 // Since the chat history is stored in the vector store, the serialized session
 // only contains the guid that the messages are stored under in the vector store.
-JsonElement serializedSession = agent.SerializeSession(session);
+JsonElement serializedSession = await agent.SerializeSessionAsync(session);

 Console.WriteLine("\n--- Serialized session ---\n");
 Console.WriteLine(JsonSerializer.Serialize(serializedSession, new JsonSerializerOptions { WriteIndented = true }));
@@ -63,48 +63,75 @@ AgentSession resumedSession = await agent.DeserializeSessionAsync(serializedSess
 // Run the agent with the session that stores chat history in the vector store a second time.
 Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedSession));

-// We can access the VectorChatHistoryProvider via the session's GetService method if we need to read the key under which chat history is stored.
-var chatHistoryProvider = resumedSession.GetService<VectorChatHistoryProvider>()!;
-Console.WriteLine($"\nSession is stored in vector store under key: {chatHistoryProvider.SessionDbKey}");
+// We can access the VectorChatHistoryProvider via the agent's GetService method
+// if we need to read the key under which chat history is stored. The key is stored
+// in the session state, and therefore we need to provide the session when reading it.
+var chatHistoryProvider = agent.GetService<VectorChatHistoryProvider>()!;
+Console.WriteLine($"\nSession is stored in vector store under key: {chatHistoryProvider.GetSessionDbKey(resumedSession)}");

 namespace SampleApp
 {
    /// <summary>
    /// A sample implementation of <see cref="ChatHistoryProvider"/> that stores chat history in a vector store.
+    /// State (the session DB key) is stored in the <see cref="AgentSession.StateBag"/> so it roundtrips
+    /// automatically with session serialization.
    /// </summary>
    internal sealed class VectorChatHistoryProvider : ChatHistoryProvider
    {
        private readonly VectorStore _vectorStore;
+        private readonly Func<AgentSession?, State> _stateInitializer;
+        private readonly string _stateKey;

-        public VectorChatHistoryProvider(VectorStore vectorStore, JsonElement serializedState, JsonSerializerOptions? jsonSerializerOptions = null)
+        /// <inheritdoc />
+        public override string StateKey => this._stateKey;
+
+        public VectorChatHistoryProvider(
+            VectorStore vectorStore,
+            Func<AgentSession?, State>? stateInitializer = null,
+            string? stateKey = null)
        {
            this._vectorStore = vectorStore ?? throw new ArgumentNullException(nameof(vectorStore));
-
-            if (serializedState.ValueKind is JsonValueKind.String)
-            {
-                // Here we can deserialize the session id so that we can access the same messages as before the suspension.
-                this.SessionDbKey = serializedState.Deserialize<string>();
-            }
+            this._stateInitializer = stateInitializer ?? (_ => new State(Guid.NewGuid().ToString("N")));
+            this._stateKey = stateKey ?? base.StateKey;
        }

-        public string? SessionDbKey { get; private set; }
+        public string GetSessionDbKey(AgentSession session)
+            => this.GetOrInitializeState(session).SessionDbKey;
+
+        private State GetOrInitializeState(AgentSession? session)
+        {
+            if (session?.StateBag.TryGetValue<State>(this._stateKey, out var state) is true && state is not null)
+            {
+                return state;
+            }
+
+            state = this._stateInitializer(session);
+            if (session is not null)
+            {
+                session.StateBag.SetValue(this._stateKey, state);
+            }
+
+            return state;
+        }

        protected override async ValueTask<IEnumerable<ChatMessage>> InvokingCoreAsync(InvokingContext context, CancellationToken cancellationToken = default)
        {
+            var state = this.GetOrInitializeState(context.Session);
            var collection = this._vectorStore.GetCollection<string, ChatHistoryItem>("ChatHistory");
            await collection.EnsureCollectionExistsAsync(cancellationToken);

            var records = await collection
                .GetAsync(
-                    x => x.SessionId == this.SessionDbKey, 10,
+                    x => x.SessionId == state.SessionDbKey, 10,
                    new() { OrderBy = x => x.Descending(y => y.Timestamp) },
                    cancellationToken)
                .ToListAsync(cancellationToken);

-            var messages = records.ConvertAll(x => JsonSerializer.Deserialize<ChatMessage>(x.SerializedMessage!)!)
-;
+            var messages = records.ConvertAll(x => JsonSerializer.Deserialize<ChatMessage>(x.SerializedMessage!)!);
            messages.Reverse();
-            return messages;
+            return messages
+                .Select(message => message.WithAgentRequestMessageSource(AgentRequestMessageSourceType.ChatHistory, this.GetType().FullName!))
+                .Concat(context.RequestMessages);
        }

        protected override async ValueTask InvokedCoreAsync(InvokedContext context, CancellationToken cancellationToken = default)
@@ -115,28 +142,39 @@ namespace SampleApp
                return;
            }

-            this.SessionDbKey ??= Guid.NewGuid().ToString("N");
+            var state = this.GetOrInitializeState(context.Session);

            var collection = this._vectorStore.GetCollection<string, ChatHistoryItem>("ChatHistory");
            await collection.EnsureCollectionExistsAsync(cancellationToken);

-            // Add both request and response messages to the store
+            // Add both request and response messages to the store, excluding messages that came from chat history.
            // Optionally messages produced by the AIContextProvider can also be persisted (not shown).
-            var allNewMessages = context.RequestMessages.Concat(context.ResponseMessages ?? []);
+            var allNewMessages = context.RequestMessages
+                .Where(m => m.GetAgentRequestMessageSourceType() != AgentRequestMessageSourceType.ChatHistory)
+                .Concat(context.ResponseMessages ?? []);

            await collection.UpsertAsync(allNewMessages.Select(x => new ChatHistoryItem()
            {
-                Key = this.SessionDbKey + x.MessageId,
+                Key = state.SessionDbKey + x.MessageId,
                Timestamp = DateTimeOffset.UtcNow,
-                SessionId = this.SessionDbKey,
+                SessionId = state.SessionDbKey,
                SerializedMessage = JsonSerializer.Serialize(x),
                MessageText = x.Text
            }), cancellationToken);
        }

-        public override JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null) =>
-            // We have to serialize the session id, so that on deserialization we can retrieve the messages using the same session id.
-            JsonSerializer.SerializeToElement(this.SessionDbKey);
+        /// <summary>
+        /// Represents the per-session state stored in the <see cref="AgentSession.StateBag"/>.
+        /// </summary>
+        public sealed class State
+        {
+            public State(string sessionDbKey)
+            {
+                this.SessionDbKey = sessionDbKey ?? throw new ArgumentNullException(nameof(sessionDbKey));
+            }
+
+            public string SessionDbKey { get; }
+        }

        /// <summary>
        /// The data structure used to store chat history items in the vector store.
@@ -27,7 +27,10 @@ if (!string.IsNullOrWhiteSpace(applicationInsightsConnectionString))
 using var tracerProvider = tracerProviderBuilder.Build();

 // Create the agent, and enable OpenTelemetry instrumentation.
-AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIAgent agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker")
    .AsBuilder()
@@ -21,9 +21,12 @@ HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);
 builder.Services.AddSingleton(new ChatClientAgentOptions() { Name = "Joker", ChatOptions = new() { Instructions = "You are good at telling jokes." } });

 // Add a chat client to the service collection.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 builder.Services.AddKeyedChatClient("AzureOpenAI", (sp) => new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
        .GetChatClient(deploymentName)
        .AsIChatClient());

@@ -12,7 +12,10 @@ using ModelContextProtocol.Server;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

-var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());

 // Create a server side persistent agent
 var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
@@ -11,7 +11,10 @@ using ChatMessage = Microsoft.Extensions.AI.ChatMessage;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o";

-var agent = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+var agent = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(
        name: "VisionAgent",
@@ -17,9 +17,12 @@ static string GetWeather([Description("The location to get the weather for.")] s
    => $"The weather in {location} is cloudy with a high of 15°C.";

 // Create the chat client and agent, and provide the function tool to the agent.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent weatherAgent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetChatClient(deploymentName)
     .AsAIAgent(
        instructions: "You answer questions about the weather.",
@@ -30,7 +33,7 @@ AIAgent weatherAgent = new AzureOpenAIClient(
 // Create the main agent, and provide the weather agent as a function tool.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(instructions: "You are a helpful assistant who responds in French.", tools: [weatherAgent.AsAIFunction()]);

@@ -19,9 +19,12 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT

 var stateStore = new Dictionary<string, JsonElement?>();

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetResponsesClient(deploymentName)
     .AsAIAgent(
        name: "SpaceNovelWriter",
@@ -40,7 +43,7 @@ AgentResponse response = await agent.RunAsync("Write a very long novel about a t
 // Poll for background responses until complete.
 while (response.ContinuationToken is not null)
 {
-    PersistAgentState(agent, session, response.ContinuationToken);
+    await PersistAgentState(agent, session, response.ContinuationToken);

    await Task.Delay(TimeSpan.FromSeconds(10));

@@ -52,9 +55,9 @@ while (response.ContinuationToken is not null)

 Console.WriteLine(response.Text);

-void PersistAgentState(AIAgent agent, AgentSession? session, ResponseContinuationToken? continuationToken)
+async Task PersistAgentState(AIAgent agent, AgentSession? session, ResponseContinuationToken? continuationToken)
 {
-    stateStore["session"] = agent.SerializeSession(session!);
+    stateStore["session"] = await agent.SerializeSessionAsync(session!);
    stateStore["continuationToken"] = JsonSerializer.SerializeToElement(continuationToken, AgentAbstractionsJsonUtilities.DefaultOptions.GetTypeInfo(typeof(ResponseContinuationToken)));
 }

@@ -17,7 +17,10 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var deploymentName = System.Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o";

 // Get a client to create/retrieve server side agents with
-var azureOpenAIClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+var azureOpenAIClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
    .GetChatClient(deploymentName);

 [Description("Get the weather for a given location.")]
@@ -7,7 +7,7 @@ This sample demonstrates how to add middleware to intercept:

 ## What This Sample Shows

-1. Azure OpenAI integration via `AzureOpenAIClient` and `AzureCliCredential`
+1. Azure OpenAI integration via `AzureOpenAIClient` and `DefaultAzureCredential`
 2. Chat client middleware using `ChatClientBuilder.Use(...)`
 3. Agent run middleware (PII redaction and wording guardrails)
 4. Function invocation middleware (logging and overriding a tool result)
@@ -27,9 +27,12 @@ services.AddSingleton<AgentPlugin>(); // The plugin depends on WeatherProvider a

 IServiceProvider serviceProvider = services.BuildServiceProvider();

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(
        instructions: "You are a helpful assistant that helps people find information.",
@@ -16,15 +16,18 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Construct the agent, and provide a factory to create an in-memory chat message store with a reducer that keeps only the last 2 non-system messages.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(new ChatClientAgentOptions
    {
        ChatOptions = new() { Instructions = "You are good at telling jokes." },
        Name = "Joker",
-        ChatHistoryProviderFactory = (ctx, ct) => new ValueTask<ChatHistoryProvider>(new InMemoryChatHistoryProvider(new MessageCountingChatReducer(2), ctx.SerializedState, ctx.JsonSerializerOptions))
+        ChatHistoryProvider = new InMemoryChatHistoryProvider(new() { ChatReducer = new MessageCountingChatReducer(2) })
    });

 AgentSession session = await agent.CreateSessionAsync();
@@ -33,7 +36,10 @@ AgentSession session = await agent.CreateSessionAsync();
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session));

 // Get the chat history to see how many messages are stored.
-IList<ChatMessage>? chatHistory = session.GetService<IList<ChatMessage>>();
+// We can use the ChatHistoryProvider, that is also used by the agent, to read the
+// chat history from the session state, and see how the reducer is affecting the stored messages.
+var provider = agent.GetService<InMemoryChatHistoryProvider>();
+List<ChatMessage>? chatHistory = provider?.GetMessages(session);
 Console.WriteLine($"\nChat history has {chatHistory?.Count} messages.\n");

 // Invoke the agent a few more times.
@@ -10,9 +10,12 @@ using OpenAI.Responses;
 var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetResponsesClient(deploymentName)
     .AsAIAgent();

@@ -16,7 +16,10 @@ PersistentAgentsAdministrationClientOptions persistentAgentsClientOptions = new(
 persistentAgentsClientOptions.Retry.NetworkTimeout = TimeSpan.FromMinutes(20);

 // Get a client to create/retrieve server side agents with.
-PersistentAgentsClient persistentAgentsClient = new(endpoint, new AzureCliCredential(), persistentAgentsClientOptions);
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+PersistentAgentsClient persistentAgentsClient = new(endpoint, new DefaultAzureCredential(), persistentAgentsClientOptions);

 // Define and configure the Deep Research tool.
 DeepResearchToolDefinition deepResearchTool = new(new DeepResearchDetails(
@@ -11,9 +11,12 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create the chat client
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 IChatClient chatClient = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetChatClient(deploymentName)
     .AsIChatClient();

@@ -1,13 +1,12 @@
 // Copyright (c) Microsoft. All rights reserved.

-// This sample shows how to inject additional AI context into a ChatClientAgent using a custom AIContextProvider component that is attached to the agent.
-// The sample also shows how to combine the results from multiple providers into a single class, in order to attach multiple of these to an agent.
+// This sample shows how to inject additional AI context into a ChatClientAgent using custom AIContextProvider components that are attached to the agent.
+// Multiple providers can be attached to an agent, and they will be called in sequence, each receiving the accumulated context from the previous one.
 // This mechanism can be used for various purposes, such as injecting RAG search results or memories into the agent's context.
 // Also note that Agent Framework already provides built-in AIContextProviders for many of these scenarios.

 #pragma warning disable CA1869 // Cache and reuse 'JsonSerializerOptions' instances

-using System.ComponentModel;
 using System.Text;
 using System.Text.Json;
 using Azure.AI.OpenAI;
@@ -34,9 +33,12 @@ Func<Task<string[]>> loadNextThreeCalendarEvents = async () =>
 };

 // Create an agent with an AI context provider attached that aggregates two other providers:
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetChatClient(deploymentName)
    .AsAIAgent(new ChatClientAgentOptions()
    {
@@ -45,16 +47,20 @@ AIAgent agent = new AzureOpenAIClient(
        You manage a TODO list for the user. When the user has completed one of the tasks it can be removed from the TODO list. Only provide the list of TODO items if asked.
        You remind users of upcoming calendar events when the user interacts with you.
        """ },
-        ChatHistoryProviderFactory = (ctx, ct) => new ValueTask<ChatHistoryProvider>(new InMemoryChatHistoryProvider()
-            // Use WithAIContextProviderMessageRemoval, so that we don't store the messages from the AI context provider in the chat history.
+        ChatHistoryProvider = new InMemoryChatHistoryProvider(new InMemoryChatHistoryProviderOptions
+        {
+            // Use StorageInputMessageFilter to provide a custom filter for messages stored in chat history.
+            // By default the chat history provider will store all messages, except for those that came from chat history in the first place.
+            // In this case, we want to also exclude messages that came from AI context providers.
            // You may want to store these messages, depending on their content and your requirements.
-            .WithAIContextProviderMessageRemoval()),
-        // Add an AI context provider that maintains a todo list for the agent and one that provides upcoming calendar entries.
-        // Wrap these in an AI context provider that aggregates the other two.
-        AIContextProviderFactory = (ctx, ct) => new ValueTask<AIContextProvider>(new AggregatingAIContextProvider([
-            AggregatingAIContextProvider.CreateFactory((jsonElement, jsonSerializerOptions) => new TodoListAIContextProvider(jsonElement, jsonSerializerOptions)),
-            AggregatingAIContextProvider.CreateFactory((_, _) => new CalendarSearchAIContextProvider(loadNextThreeCalendarEvents))
-        ], ctx.SerializedState, ctx.JsonSerializerOptions)),
+            StorageInputMessageFilter = messages => messages.Where(m => m.GetAgentRequestMessageSourceType() != AgentRequestMessageSourceType.AIContextProvider && m.GetAgentRequestMessageSourceType() != AgentRequestMessageSourceType.ChatHistory)
+        }),
+        // Add multiple AI context providers: one that maintains a todo list and one that provides upcoming calendar entries.
+        // The agent will call each provider in sequence, accumulating context from each.
+        AIContextProviders = [
+            new TodoListAIContextProvider(),
+            new CalendarSearchAIContextProvider(loadNextThreeCalendarEvents)
+        ],
    });

 // Invoke the agent and output the text result.
@@ -65,7 +71,7 @@ Console.WriteLine(await agent.RunAsync("I need to make a dentist appointment for
 Console.WriteLine(await agent.RunAsync("I've taken Sally to soccer practice.", session) + "\n");

 // We can serialize the session, and it will contain both the chat history and the data that each AI context provider serialized.
-JsonElement serializedSession = agent.SerializeSession(session);
+JsonElement serializedSession = await agent.SerializeSessionAsync(session);
 // Let's print it to console to show the contents.
 Console.WriteLine(JsonSerializer.Serialize(serializedSession, options: new JsonSerializerOptions() { WriteIndented = true, IndentSize = 2 }) + "\n");
 // The serialized session can be stored long term in a persistent store, but in this case we will just deserialize again and continue the conversation.
@@ -80,51 +86,67 @@ namespace SampleApp
    /// </summary>
    internal sealed class TodoListAIContextProvider : AIContextProvider
    {
-        private readonly List<string> _todoItems = new();
+        private static List<string> GetTodoItems(AgentSession? session)
+            => session?.StateBag.GetValue<List<string>>(nameof(TodoListAIContextProvider)) ?? new List<string>();

-        public TodoListAIContextProvider(JsonElement jsonElement, JsonSerializerOptions? jsonSerializerOptions = null)
-        {
-            // Only try and restore the state if we got an array, since any other json would be invalid or undefined/null meaning
-            // it's the first time we are running.
-            if (jsonElement.ValueKind == JsonValueKind.Array)
-            {
-                this._todoItems = JsonSerializer.Deserialize<List<string>>(jsonElement.GetRawText(), jsonSerializerOptions) ?? new List<string>();
-            }
-        }
+        private static void SetTodoItems(AgentSession? session, List<string> items)
+            => session?.StateBag.SetValue(nameof(TodoListAIContextProvider), items);

        protected override ValueTask<AIContext> InvokingCoreAsync(InvokingContext context, CancellationToken cancellationToken = default)
        {
+            var inputContext = context.AIContext;
+            var todoItems = GetTodoItems(context.Session);
+
            StringBuilder outputMessageBuilder = new();
            outputMessageBuilder.AppendLine("Your todo list contains the following items:");

-            if (this._todoItems.Count == 0)
+            if (todoItems.Count == 0)
            {
                outputMessageBuilder.AppendLine("  (no items)");
            }
            else
            {
-                for (int i = 0; i < this._todoItems.Count; i++)
+                for (int i = 0; i < todoItems.Count; i++)
                {
-                    outputMessageBuilder.AppendLine($"{i}. {this._todoItems[i]}");
+                    outputMessageBuilder.AppendLine($"{i}. {todoItems[i]}");
                }
            }

            return new ValueTask<AIContext>(new AIContext
            {
-                Tools = [AIFunctionFactory.Create(this.AddTodoItem), AIFunctionFactory.Create(this.RemoveTodoItem)],
-                Messages = [new MEAI.ChatMessage(ChatRole.User, outputMessageBuilder.ToString())]
+                Instructions = inputContext.Instructions,
+                Tools = (inputContext.Tools ?? []).Concat(new AITool[]
+                {
+                    AIFunctionFactory.Create((string item) => AddTodoItem(context.Session, item), "AddTodoItem", "Adds an item to the todo list."),
+                    AIFunctionFactory.Create((int index) => RemoveTodoItem(context.Session, index), "RemoveTodoItem", "Removes an item from the todo list. Index is zero based.")
+                }),
+                Messages =
+                    (inputContext.Messages ?? [])
+                    .Concat(
+                    [
+                        new MEAI.ChatMessage(ChatRole.User, outputMessageBuilder.ToString()).WithAgentRequestMessageSource(AgentRequestMessageSourceType.AIContextProvider, this.GetType().FullName!)
+                    ])
            });
        }

-        [Description("Adds an item to the todo list. Index is zero based.")]
-        private void RemoveTodoItem(int index) =>
-            this._todoItems.RemoveAt(index);
+        private static void RemoveTodoItem(AgentSession? session, int index)
+        {
+            var items = GetTodoItems(session);
+            items.RemoveAt(index);
+            SetTodoItems(session, items);
+        }

-        private void AddTodoItem(string item) =>
-            this._todoItems.Add(string.IsNullOrWhiteSpace(item) ? throw new ArgumentException("Item must have a value") : item);
+        private static void AddTodoItem(AgentSession? session, string item)
+        {
+            if (string.IsNullOrWhiteSpace(item))
+            {
+                throw new ArgumentException("Item must have a value");
+            }

-        public override JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null) =>
-            JsonSerializer.SerializeToElement(this._todoItems, jsonSerializerOptions);
+            var items = GetTodoItems(session);
+            items.Add(item);
+            SetTodoItems(session, items);
+        }
    }

    /// <summary>
@@ -134,6 +156,7 @@ namespace SampleApp
    {
        protected override async ValueTask<AIContext> InvokingCoreAsync(InvokingContext context, CancellationToken cancellationToken = default)
        {
+            var inputContext = context.AIContext;
            var events = await loadNextThreeCalendarEvents();

            StringBuilder outputMessageBuilder = new();
@@ -145,84 +168,16 @@ namespace SampleApp

            return new()
            {
+                Instructions = inputContext.Instructions,
                Messages =
-                [
-                    new MEAI.ChatMessage(ChatRole.User, outputMessageBuilder.ToString()),
-                ]
+                    (inputContext.Messages ?? [])
+                    .Concat(
+                    [
+                        new MEAI.ChatMessage(ChatRole.User, outputMessageBuilder.ToString()).WithAgentRequestMessageSource(AgentRequestMessageSourceType.AIContextProvider, this.GetType().FullName!)
+                    ])
+                    .ToList(),
+                Tools = inputContext.Tools
            };
        }
    }
-
-    /// <summary>
-    /// An <see cref="AIContextProvider"/> which aggregates multiple AI context providers into one.
-    /// Serialized state for the different providers are stored under their type name.
-    /// Tools and messages from all providers are combined, and instructions are concatenated.
-    /// </summary>
-    internal sealed class AggregatingAIContextProvider : AIContextProvider
-    {
-        private readonly List<AIContextProvider> _providers = new();
-
-        public AggregatingAIContextProvider(ProviderFactory[] providerFactories, JsonElement jsonElement, JsonSerializerOptions? jsonSerializerOptions)
-        {
-            // We received a json object, so let's check if it has some previously serialized state that we can use.
-            if (jsonElement.ValueKind == JsonValueKind.Object)
-            {
-                this._providers = providerFactories
-                    .Select(factory => factory.FactoryMethod(jsonElement.TryGetProperty(factory.ProviderType.Name, out var prop) ? prop : default, jsonSerializerOptions))
-                    .ToList();
-                return;
-            }
-
-            // We didn't receive any valid json, so we can just construct fresh providers.
-            this._providers = providerFactories
-                .Select(factory => factory.FactoryMethod(default, jsonSerializerOptions))
-                .ToList();
-        }
-
-        protected override async ValueTask<AIContext> InvokingCoreAsync(InvokingContext context, CancellationToken cancellationToken = default)
-        {
-            // Invoke all the sub providers.
-            var tasks = this._providers.Select(provider => provider.InvokingAsync(context, cancellationToken).AsTask());
-            var results = await Task.WhenAll(tasks);
-
-            // Combine the results from each sub provider.
-            return new AIContext
-            {
-                Tools = results.SelectMany(r => r.Tools ?? []).ToList(),
-                Messages = results.SelectMany(r => r.Messages ?? []).ToList(),
-                Instructions = string.Join("\n", results.Select(r => r.Instructions).Where(s => !string.IsNullOrEmpty(s)))
-            };
-        }
-
-        public override JsonElement Serialize(JsonSerializerOptions? jsonSerializerOptions = null)
-        {
-            Dictionary<string, JsonElement> elements = new();
-            foreach (var provider in this._providers)
-            {
-                JsonElement element = provider.Serialize(jsonSerializerOptions);
-
-                // Don't try to store state for any providers that aren't producing any.
-                if (element.ValueKind != JsonValueKind.Undefined && element.ValueKind != JsonValueKind.Null)
-                {
-                    elements[provider.GetType().Name] = element;
-                }
-            }
-
-            return JsonSerializer.SerializeToElement(elements, jsonSerializerOptions);
-        }
-
-        public static ProviderFactory CreateFactory<TProviderType>(Func<JsonElement, JsonSerializerOptions?, TProviderType> factoryMethod)
-            where TProviderType : AIContextProvider => new()
-            {
-                FactoryMethod = (jsonElement, jsonSerializerOptions) => factoryMethod(jsonElement, jsonSerializerOptions),
-                ProviderType = typeof(TProviderType)
-            };
-
-        public readonly struct ProviderFactory
-        {
-            public Func<JsonElement, JsonSerializerOptions?, AIContextProvider> FactoryMethod { get; init; }
-
-            public Type ProviderType { get; init; }
-        }
-    }
 }
@@ -12,9 +12,12 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? th
 var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

 // Create the chat client
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 IChatClient chatClient = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetChatClient(deploymentName)
     .AsIChatClient();

@@ -46,7 +46,10 @@ internal static class Program
        var endpoint = builder.Configuration["AZURE_OPENAI_ENDPOINT"] ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        var deploymentName = builder.Configuration["AZURE_OPENAI_DEPLOYMENT_NAME"] ?? "gpt-4o-mini";

-        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
            .GetChatClient(deploymentName)
            .AsIChatClient();

@@ -13,7 +13,10 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJEC
 const string JokerName = "JokerAgent";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent you want to create. (Prompt Agent in this case)
 AgentVersionCreationOptions options = new(new PromptAgentDefinition(model: deploymentName) { Instructions = "You are good at telling jokes." });
@@ -14,7 +14,10 @@ const string JokerInstructions = "You are good at telling jokes.";
 const string JokerName = "JokerAgent";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent you want to create. (Prompt Agent in this case)
 AgentVersionCreationOptions options = new(new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions });
@@ -14,7 +14,10 @@ const string JokerInstructions = "You are good at telling jokes.";
 const string JokerName = "JokerAgent";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent you want to create. (Prompt Agent in this case)
 AgentVersionCreationOptions options = new(new PromptAgentDefinition(model: deploymentName) { Instructions = JokerInstructions });
@@ -20,7 +20,10 @@ const string AssistantInstructions = "You are a helpful assistant that can get w
 const string AssistantName = "WeatherAssistant";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent with function tools.
 AITool tool = AIFunctionFactory.Create(GetWeather);
@@ -23,7 +23,10 @@ const string AssistantInstructions = "You are a helpful assistant that can get w
 const string AssistantName = "WeatherAssistant";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 ApprovalRequiredAIFunction approvalTool = new(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)));

@@ -19,7 +19,10 @@ const string AssistantInstructions = "You are a helpful assistant that extracts
 const string AssistantName = "StructuredOutputAssistant";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Create ChatClientAgent directly
 ChatClientAgent agent = await aiProjectClient.CreateAIAgentAsync(
@@ -14,7 +14,10 @@ const string JokerInstructions = "You are good at telling jokes.";
 const string JokerName = "JokerAgent";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 AIAgent agent = await aiProjectClient.CreateAIAgentAsync(name: JokerName, model: deploymentName, instructions: JokerInstructions);

@@ -25,7 +28,7 @@ AgentSession session = await agent.CreateSessionAsync();
 Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", session));

 // Serialize the session state to a JsonElement, so it can be stored for later use.
-JsonElement serializedSession = agent.SerializeSession(session);
+JsonElement serializedSession = await agent.SerializeSessionAsync(session);

 // Save the serialized session to a temporary file (for demonstration purposes).
 string tempFilePath = Path.GetTempFileName();
@@ -29,7 +29,10 @@ if (!string.IsNullOrWhiteSpace(applicationInsightsConnectionString))
 using var tracerProvider = tracerProviderBuilder.Build();

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent you want to create. (Prompt Agent in this case)
 AIAgent agent = (await aiProjectClient.CreateAIAgentAsync(name: JokerName, model: deploymentName, instructions: JokerInstructions))
@@ -15,7 +15,10 @@ string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJEC
 const string JokerInstructions = "You are good at telling jokes.";
 const string JokerName = "JokerAgent";

-AIProjectClient aIProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aIProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Create a new agent if one doesn't exist already.
 ChatClientAgent agent;
@@ -25,7 +25,10 @@ await using var mcpClient = await McpClient.CreateAsync(new StdioClientTransport
 IList<McpClientTool> mcpTools = await mcpClient.ListToolsAsync();
 string agentName = "AgentWithMCP";
 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 Console.WriteLine($"Creating the agent '{agentName}' ...");

@@ -14,14 +14,17 @@ const string VisionInstructions = "You are a helpful agent that can analyze imag
 const string VisionName = "VisionAgent";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent you want to create. (Prompt Agent in this case)
 AIAgent agent = await aiProjectClient.CreateAIAgentAsync(name: VisionName, model: deploymentName, instructions: VisionInstructions);

 ChatMessage message = new(ChatRole.User, [
    new TextContent("What do you see in this image?"),
-    new DataContent(File.ReadAllBytes("assets/walkway.jpg"), "image/jpeg")
+    await DataContent.LoadFromAsync("assets/walkway.jpg"),
 ]);

 AgentSession session = await agent.CreateSessionAsync();
@@ -21,7 +21,10 @@ static string GetWeather([Description("The location to get the weather for.")] s
    => $"The weather in {location} is cloudy with a high of 15°C.";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Create the weather agent with function tools.
 AITool weatherTool = AIFunctionFactory.Create(GetWeather);
@@ -20,7 +20,10 @@ const string AssistantInstructions = "You are an AI assistant that helps people
 const string AssistantName = "InformationAssistant";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 [Description("Get the weather for a given location.")]
 static string GetWeather([Description("The location to get the weather for.")] string location)
@@ -4,7 +4,7 @@ This sample demonstrates how to add middleware to intercept agent runs and funct

 ## What This Sample Shows

-1. Azure Foundry Agents integration via `AIProjectClient` and `AzureCliCredential`
+1. Azure Foundry Agents integration via `AIProjectClient` and `DefaultAzureCredential`
 2. Agent run middleware (logging and monitoring)
 3. Function invocation middleware (logging and overriding tool results)
 4. Per-request agent run middleware
@@ -30,7 +30,10 @@ services.AddSingleton<AgentPlugin>(); // The plugin depends on WeatherProvider a
 IServiceProvider serviceProvider = services.BuildServiceProvider();

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Define the agent with plugin tools
 // Define the agent you want to create. (Prompt Agent in this case)
@@ -19,7 +19,10 @@ const string AgentNameMEAI = "CoderAgent-MEAI";
 const string AgentNameNative = "CoderAgent-NATIVE";

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Option 1 - Using HostedCodeInterpreterTool + AgentOptions (MEAI + AgentFramework)
 // Create the server side agent version
@@ -18,8 +18,11 @@ internal sealed class Program
        string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
        string deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "computer-use-preview";

+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
        // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-        AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+        AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
        const string AgentInstructions = @"
                    You are a computer automation assistant. 
                    
@@ -35,7 +35,10 @@ Console.WriteLine($"MCP tools available: {string.Join(", ", mcpTools.Select(t =>
 List<AITool> wrappedTools = mcpTools.Select(tool => (AITool)new LoggingMcpTool(tool)).ToList();

 // Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
-AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());

 // Create the agent with the locally-resolved MCP tools.
 AIAgent agent = await aiProjectClient.CreateAIAgentAsync(
@@ -23,9 +23,12 @@ await using var mcpClient = await McpClient.CreateAsync(new StdioClientTransport
 // Retrieve the list of tools available on the GitHub server
 var mcpTools = await mcpClient.ListToolsAsync().ConfigureAwait(false);

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetChatClient(deploymentName)
     .AsAIAgent(instructions: "You answer questions related to GitHub repositories only.", tools: [.. mcpTools.Cast<AITool>()]);

@@ -46,9 +46,12 @@ await using var mcpClient = await McpClient.CreateAsync(transport, loggerFactory
 // Retrieve the list of tools available on the GitHub server
 var mcpTools = await mcpClient.ListToolsAsync().ConfigureAwait(false);

+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetChatClient(deploymentName)
     .AsAIAgent(instructions: "You answer questions related to the weather.", tools: [.. mcpTools]);

@@ -13,7 +13,10 @@ var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOIN
 var model = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4.1-mini";

 // Get a client to create/retrieve server side agents with.
-var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());

 // **** MCP Tool with Auto Approval ****
 // *************************************
@@ -27,9 +27,12 @@ var mcpTool = new HostedMcpServerTool(
 };

 // Create an agent based on Azure OpenAI Responses as the backend.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
 AIAgent agent = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
     .GetResponsesClient(deploymentName)
     .AsAIAgent(
        instructions: "You answer questions by searching the Microsoft Learn content only.",
@@ -56,7 +59,7 @@ var mcpToolWithApproval = new HostedMcpServerTool(
 // Create an agent based on Azure OpenAI Responses as the backend.
 AIAgent agentWithRequiredApproval = new AzureOpenAIClient(
    new Uri(endpoint),
-    new AzureCliCredential())
+    new DefaultAzureCredential())
    .GetResponsesClient(deploymentName)
    .AsAIAgent(
        instructions: "You answer questions by searching the Microsoft Learn content only.",
@@ -34,7 +34,10 @@ public static class Program
        // Set up the Azure OpenAI client
        var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();

        // Create the executors
        var sloganWriter = new SloganWriterExecutor("SloganWriter", chatClient);
@@ -24,7 +24,10 @@ public static class Program
        var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT")
            ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
        var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-        var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var persistentAgentsClient = new PersistentAgentsClient(endpoint, new DefaultAzureCredential());

        // Create agents
        AIAgent frenchAgent = await GetTranslationAgentAsync("French", persistentAgentsClient, deploymentName);
@@ -45,8 +45,11 @@ public static class Program
        var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";

+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
        // 1. Create AI client
-        IChatClient client = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+        IChatClient client = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
            .GetChatClient(deploymentName)
            .AsIChatClient();

@@ -32,7 +32,10 @@ public static class Program
        // Set up the Azure OpenAI client
        var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();

        // Create the workflow and turn it into an agent
        var workflow = WorkflowFactory.BuildWorkflow(chatClient);
@@ -34,7 +34,10 @@ public static class Program
        // Set up the Azure OpenAI client
        var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();

        // Create the executors
        ChatClientAgent physicist = new(
@@ -37,7 +37,10 @@ public static class Program
        // Set up the Azure OpenAI client
        var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();

        // Create agents
        AIAgent spamDetectionAgent = GetSpamDetectionAgent(chatClient);
@@ -38,7 +38,10 @@ public static class Program
        // Set up the Azure OpenAI client
        var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
        var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
-        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential()).GetChatClient(deploymentName).AsIChatClient();
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        var chatClient = new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential()).GetChatClient(deploymentName).AsIChatClient();

        // Create agents
        AIAgent spamDetectionAgent = GetSpamDetectionAgent(chatClient);
--- a/Show More
+++ b/Show More