diff --git a/dotnet/agent-framework-dotnet.slnx b/dotnet/agent-framework-dotnet.slnx
index 95812435d8..cbda6c2809 100644
--- a/dotnet/agent-framework-dotnet.slnx
+++ b/dotnet/agent-framework-dotnet.slnx
@@ -137,6 +137,7 @@
+
diff --git a/dotnet/samples/Catalog/AgentsInWorkflows/AgentsInWorkflows.csproj b/dotnet/samples/Catalog/AgentsInWorkflows/AgentsInWorkflows.csproj
new file mode 100644
index 0000000000..284ea6ceec
--- /dev/null
+++ b/dotnet/samples/Catalog/AgentsInWorkflows/AgentsInWorkflows.csproj
@@ -0,0 +1,23 @@
+
+
+
+ Exe
+ net9.0
+
+ enable
+ enable
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/dotnet/samples/Catalog/AgentsInWorkflows/Program.cs b/dotnet/samples/Catalog/AgentsInWorkflows/Program.cs
new file mode 100644
index 0000000000..3e01f6e717
--- /dev/null
+++ b/dotnet/samples/Catalog/AgentsInWorkflows/Program.cs
@@ -0,0 +1,48 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to integrate AI agents into a workflow pipeline.
+// Three translation agents are connected sequentially to create a translation chain:
+// English → French → Spanish → English, showing how agents can be composed as workflow executors.
+
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Extensions.AI;
+
+// 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";
+
+IChatClient chatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+ .GetChatClient(deploymentName)
+ .AsIChatClient();
+
+// Create agents
+AIAgent frenchAgent = GetTranslationAgent("French", chatClient);
+AIAgent spanishAgent = GetTranslationAgent("Spanish", chatClient);
+AIAgent englishAgent = GetTranslationAgent("English", chatClient);
+
+// Build the workflow by adding executors and connecting them
+Workflow workflow = new WorkflowBuilder(frenchAgent)
+ .AddEdge(frenchAgent, spanishAgent)
+ .AddEdge(spanishAgent, englishAgent)
+.Build();
+
+// Execute the workflow
+await using StreamingRun run = await InProcessExecution.StreamAsync(workflow, new ChatMessage(ChatRole.User, "Hello World!"));
+
+// Must send the turn token to trigger the agents.
+// The agents are wrapped as executors. When they receive messages,
+// they will cache the messages and only start processing when they receive a TurnToken.
+await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
+await foreach (WorkflowEvent evt in run.WatchStreamAsync())
+{
+ if (evt is AgentRunUpdateEvent executorComplete)
+ {
+ Console.WriteLine($"{executorComplete.ExecutorId}: {executorComplete.Data}");
+ }
+}
+
+static ChatClientAgent GetTranslationAgent(string targetLanguage, IChatClient chatClient) =>
+ new(chatClient, $"You are a translation assistant that translates the provided text to {targetLanguage}.");
diff --git a/dotnet/samples/Catalog/AgentsInWorkflows/README.md b/dotnet/samples/Catalog/AgentsInWorkflows/README.md
new file mode 100644
index 0000000000..a92012157e
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+++ b/dotnet/samples/Catalog/AgentsInWorkflows/README.md
@@ -0,0 +1,26 @@
+# What this sample demonstrates
+
+This sample demonstrates the use of AI agents as executors within a workflow.
+
+This workflow uses three translation agents:
+1. French Agent - translates input text to French
+2. Spanish Agent - translates French text to Spanish
+3. English Agent - translates Spanish text back to English
+
+The agents are connected sequentially, creating a translation chain that demonstrates how AI-powered components can be seamlessly integrated into workflow pipelines.
+
+## Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Azure OpenAI service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini" # Optional, defaults to gpt-4o-mini
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