diff --git a/samples/csharp/quickstart/chat-with-agent/quickstart-chat-with-agent.cs b/samples/csharp/quickstart/chat-with-agent/quickstart-chat-with-agent.cs
index 05f92b67a..1f6113abf 100644
--- a/samples/csharp/quickstart/chat-with-agent/quickstart-chat-with-agent.cs
+++ b/samples/csharp/quickstart/chat-with-agent/quickstart-chat-with-agent.cs
@@ -1,30 +1,29 @@
+using Azure.Identity;
 using Azure.AI.Projects;
 using Azure.AI.Projects.OpenAI;
-using Azure.Identity;
 using OpenAI.Responses;
 
 #pragma warning disable OPENAI001
 
-string projectEndpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT")
-    ?? throw new InvalidOperationException("Missing environment variable 'PROJECT_ENDPOINT'");
-string modelDeploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME")
-    ?? throw new InvalidOperationException("Missing environment variable 'MODEL_DEPLOYMENT_NAME'");
-string agentName = Environment.GetEnvironmentVariable("AGENT_NAME")
-    ?? throw new InvalidOperationException("Missing environment variable 'AGENT_NAME'");
+// Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+var projectEndpoint = "your_project_endpoint";
+var agentName = "your_agent_name";
 
-AIProjectClient projectClient = new(new Uri(projectEndpoint), new AzureCliCredential());
+// Create project client to call Foundry API
+AIProjectClient projectClient = new(
+    endpoint: new Uri(projectEndpoint),
+    tokenProvider: new DefaultAzureCredential());
 
-// Optional Step: Create a conversation to use with the agent
+// Create a conversation for multi-turn chat
 ProjectConversation conversation = projectClient.OpenAI.Conversations.CreateProjectConversation();
 
+// Chat with the agent to answer questions
 ProjectResponsesClient responsesClient = projectClient.OpenAI.GetProjectResponsesClientForAgent(
     defaultAgent: agentName,
     defaultConversationId: conversation.Id);
-
-// Chat with the agent to answer questions
 ResponseResult response = responsesClient.CreateResponse("What is the size of France in square miles?");
 Console.WriteLine(response.GetOutputText());
 
-// Optional Step: Ask a follow-up question in the same conversation
+// Ask a follow-up question in the same conversation
 response = responsesClient.CreateResponse("And what is the capital city?");
 Console.WriteLine(response.GetOutputText());
\ No newline at end of file
diff --git a/samples/csharp/quickstart/create-agent/quickstart-create-agent.cs b/samples/csharp/quickstart/create-agent/quickstart-create-agent.cs
index dab5d95e2..c4e70e2bd 100644
--- a/samples/csharp/quickstart/create-agent/quickstart-create-agent.cs
+++ b/samples/csharp/quickstart/create-agent/quickstart-create-agent.cs
@@ -1,27 +1,23 @@
+using Azure.Identity;
 using Azure.AI.Projects;
 using Azure.AI.Projects.OpenAI;
-using Azure.Identity;
 
-string projectEndpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT")
-?? throw new InvalidOperationException("Missing environment variable 'PROJECT_ENDPOINT'");
-string modelDeploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME")
-?? throw new InvalidOperationException("Missing environment variable 'MODEL_DEPLOYMENT_NAME'");
-string agentName = Environment.GetEnvironmentVariable("AGENT_NAME")
-?? throw new InvalidOperationException("Missing environment variable 'AGENT_NAME'");
+// Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+var projectEndpoint = "your_project_endpoint";
+var agentName = "your_agent_name";
 
-AIProjectClient projectClient = new(new Uri(projectEndpoint), new AzureCliCredential());
+// Create project client to call Foundry API
+AIProjectClient projectClient = new(
+    endpoint: new Uri(projectEndpoint),
+    tokenProvider: new DefaultAzureCredential());
 
-AgentDefinition agentDefinition = new PromptAgentDefinition(modelDeploymentName)
+// Create an agent with a model and instructions
+AgentDefinition agentDefinition = new PromptAgentDefinition("gpt-5-mini")
 {
     Instructions = "You are a helpful assistant that answers general questions",
 };
 
-AgentVersion newAgentVersion = projectClient.Agents.CreateAgentVersion(
+AgentVersion agent = projectClient.Agents.CreateAgentVersion(
     agentName,
     options: new(agentDefinition));
-
-List<AgentVersion> agentVersions = [..projectClient.Agents.GetAgentVersions(agentName)];
-foreach (AgentVersion agentVersion in agentVersions)
-{
-    Console.WriteLine($"Agent: {agentVersion.Id}, Name: {agentVersion.Name}, Version: {agentVersion.Version}");
-}
+Console.WriteLine($"Agent created (id: {agent.Id}, name: {agent.Name}, version: {agent.Version})");
diff --git a/samples/csharp/quickstart/responses/quickstart-responses.cs b/samples/csharp/quickstart/responses/quickstart-responses.cs
index d980fa97d..c8816a37b 100644
--- a/samples/csharp/quickstart/responses/quickstart-responses.cs
+++ b/samples/csharp/quickstart/responses/quickstart-responses.cs
@@ -1,18 +1,20 @@
+using Azure.Identity;
 using Azure.AI.Projects;
 using Azure.AI.Projects.OpenAI;
-using Azure.Identity;
 using OpenAI.Responses;
 
 #pragma warning disable OPENAI001
 
-string projectEndpoint = Environment.GetEnvironmentVariable("PROJECT_ENDPOINT")
-?? throw new InvalidOperationException("Missing environment variable 'PROJECT_ENDPOINT'");
-string modelDeploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME")
-?? throw new InvalidOperationException("Missing environment variable 'MODEL_DEPLOYMENT_NAME'");
-
-AIProjectClient projectClient = new(new Uri(projectEndpoint), new AzureCliCredential());
+// Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+var projectEndpoint = "your_project_endpoint";
 
-ProjectResponsesClient responseClient = projectClient.OpenAI.GetProjectResponsesClientForModel(modelDeploymentName);
-ResponseResult response = await responseClient.CreateResponseAsync("What is the size of France in square miles?");
+// Create project client to call Foundry API
+AIProjectClient projectClient = new(
+    endpoint: new Uri(projectEndpoint),
+    tokenProvider: new DefaultAzureCredential());
 
+// Run a responses API call
+ProjectResponsesClient responseClient = projectClient.OpenAI.GetProjectResponsesClientForModel("gpt-5-mini");
+ResponseResult response = await responseClient.CreateResponseAsync(
+    "What is the size of France in square miles?");
 Console.WriteLine(response.GetOutputText());
diff --git a/samples/java/quickstart/chat-with-agent/src/main/java/com/azure/ai/agents/ChatWithAgent.java b/samples/java/quickstart/chat-with-agent/src/main/java/com/azure/ai/agents/ChatWithAgent.java
index 05bd0340e..73ff32bd9 100644
--- a/samples/java/quickstart/chat-with-agent/src/main/java/com/azure/ai/agents/ChatWithAgent.java
+++ b/samples/java/quickstart/chat-with-agent/src/main/java/com/azure/ai/agents/ChatWithAgent.java
@@ -1,64 +1,33 @@
 package com.azure.ai.agents;
 
-import com.azure.ai.agents.models.AgentReference;
-import com.azure.ai.agents.models.AgentVersionDetails;
-import com.azure.ai.agents.models.PromptAgentDefinition;
-import com.azure.identity.AuthenticationUtil;
 import com.azure.identity.DefaultAzureCredentialBuilder;
-import com.openai.azure.AzureOpenAIServiceVersion;
-import com.openai.azure.AzureUrlPathMode;
-import com.openai.client.OpenAIClient;
-import com.openai.client.okhttp.OpenAIOkHttpClient;
-import com.openai.credential.BearerTokenCredential;
 import com.openai.models.conversations.Conversation;
-import com.openai.models.conversations.items.ItemCreateParams;
-import com.openai.models.responses.EasyInputMessage;
 import com.openai.models.responses.Response;
 import com.openai.models.responses.ResponseCreateParams;
 
 public class ChatWithAgent {
     public static void main(String[] args) {
-        String endpoint = Configuration.getGlobalConfiguration().get("AZURE_AGENTS_ENDPOINT");
-        String agentName = "MyAgent";
-        
-        AgentsClient agentsClient = new AgentsClientBuilder()
-                .credential(new DefaultAzureCredentialBuilder().build())
-                .endpoint(endpoint)
-                .buildAgentsClient();
+        // Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+        String projectEndpoint = "your_project_endpoint";
+        String agentName = "your_agent_name";
 
-        AgentDetails agent = agentsClient.getAgent(agentName);
+        // Create clients to call Foundry API
+        AgentsClientBuilder builder = new AgentsClientBuilder()
+                .credential(new DefaultAzureCredentialBuilder().build())
+                .endpoint(projectEndpoint);
+        ResponsesClient responsesClient = builder.buildResponsesClient();
+        ConversationsClient conversationsClient = builder.buildConversationsClient();
 
+        // Create a conversation for multi-turn chat
         Conversation conversation = conversationsClient.getConversationService().create();
-        conversationsClient.getConversationService().items().create(
-            ItemCreateParams.builder()
-                .conversationId(conversation.id())
-                .addItem(EasyInputMessage.builder()
-                    .role(EasyInputMessage.Role.SYSTEM)
-                    .content("You are a helpful assistant that speaks like a pirate.")
-                    .build()
-                ).addItem(EasyInputMessage.builder()
-                    .role(EasyInputMessage.Role.USER)
-                    .content("Hello, agent!")
-                    .build()
-            ).build()
-        );
-
-        AgentReference agentReference = new AgentReference(agent.getName()).setVersion(agent.getVersion());
-        Response response = responsesClient.createWithAgentConversation(agentReference, conversation.id());
-
-        OpenAIClient client = OpenAIOkHttpClient.builder()
-            .baseUrl(endpoint.endsWith("/") ? endpoint + "openai" : endpoint + "/openai")
-            .azureUrlPathMode(AzureUrlPathMode.UNIFIED)
-            .credential(BearerTokenCredential.create(AuthenticationUtil.getBearerTokenSupplier(
-                    new DefaultAzureCredentialBuilder().build(), "https://ai.azure.com/.default")))
-            .azureServiceVersion(AzureOpenAIServiceVersion.fromString("2025-11-15-preview"))
-            .build();
 
+        // TODO: Java SDK does not yet support passing conversation ID or agent reference
+        // to ResponseCreateParams. Update once the SDK adds agent+conversation support.
+        // Chat with the agent to answer questions
         ResponseCreateParams responseRequest = new ResponseCreateParams.Builder()
-            .input("Hello, how can you help me?")
-            .model(model)
-            .build();
-
-        Response result = client.responses().create(responseRequest);
+                .input("What is the size of France in square miles?")
+                .build();
+        Response response = responsesClient.getResponseService().create(responseRequest);
+        System.out.println(response.output());
     }
 }
\ No newline at end of file
diff --git a/samples/java/quickstart/create-agent/src/main/java/com/azure/ai/agents/CreateAgent.java b/samples/java/quickstart/create-agent/src/main/java/com/azure/ai/agents/CreateAgent.java
index 6b81d2341..da3997c95 100644
--- a/samples/java/quickstart/create-agent/src/main/java/com/azure/ai/agents/CreateAgent.java
+++ b/samples/java/quickstart/create-agent/src/main/java/com/azure/ai/agents/CreateAgent.java
@@ -2,21 +2,23 @@
 
 import com.azure.ai.agents.models.AgentVersionDetails;
 import com.azure.ai.agents.models.PromptAgentDefinition;
-import com.azure.core.util.Configuration;
 import com.azure.identity.DefaultAzureCredentialBuilder;
 
 public class CreateAgent {
     public static void main(String[] args) {
-        String endpoint = Configuration.getGlobalConfiguration().get("PROJECT_ENDPOINT");
-        String model = Configuration.getGlobalConfiguration().get("MODEL_DEPLOYMENT_NAME");
-        // Code sample for creating an agent
+        // Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+        String projectEndpoint = "your_project_endpoint";
+        String agentName = "your_agent_name";
+
+        // Create agents client to call Foundry API
         AgentsClient agentsClient = new AgentsClientBuilder()
                 .credential(new DefaultAzureCredentialBuilder().build())
-                .endpoint(endpoint)
+                .endpoint(projectEndpoint)
                 .buildAgentsClient();
 
-        PromptAgentDefinition request = new PromptAgentDefinition(model);
-        AgentVersionDetails agent = agentsClient.createAgentVersion("MyAgent", request);
+        // Create an agent with a model and instructions
+        PromptAgentDefinition request = new PromptAgentDefinition("gpt-5-mini");
+        AgentVersionDetails agent = agentsClient.createAgentVersion(agentName, request);
 
         System.out.println("Agent ID: " + agent.getId());
         System.out.println("Agent Name: " + agent.getName());
diff --git a/samples/java/quickstart/responses/src/main/java/com/azure/ai/agents/CreateResponse.java b/samples/java/quickstart/responses/src/main/java/com/azure/ai/agents/CreateResponse.java
index 12188eb50..b96906413 100644
--- a/samples/java/quickstart/responses/src/main/java/com/azure/ai/agents/CreateResponse.java
+++ b/samples/java/quickstart/responses/src/main/java/com/azure/ai/agents/CreateResponse.java
@@ -1,31 +1,26 @@
 package com.azure.ai.agents;
 
-import com.azure.core.util.Configuration;
 import com.azure.identity.DefaultAzureCredentialBuilder;
 import com.openai.models.responses.Response;
 import com.openai.models.responses.ResponseCreateParams;
 
 public class CreateResponse {
     public static void main(String[] args) {
-        String endpoint = Configuration.getGlobalConfiguration().get("PROJECT_ENDPOINT");
-        String model = Configuration.getGlobalConfiguration().get("MODEL_DEPLOYMENT_NAME");
-        // Code sample for creating a response
+        // Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+        String projectEndpoint = "your_project_endpoint";
+
+        // Create responses client to call Foundry API
         ResponsesClient responsesClient = new AgentsClientBuilder()
                 .credential(new DefaultAzureCredentialBuilder().build())
-                .endpoint(endpoint)
-                .serviceVersion(AgentsServiceVersion.V2025_11_15_PREVIEW)
+                .endpoint(projectEndpoint)
                 .buildResponsesClient();
 
+        // Run a responses API call
         ResponseCreateParams responseRequest = new ResponseCreateParams.Builder()
-                .input("Hello, how can you help me?")
-                .model(model)
+                .input("What is the size of France in square miles?")
+                .model("gpt-5-mini")  // supports all Foundry direct models
                 .build();
-
         Response response = responsesClient.getResponseService().create(responseRequest);
-
-        System.out.println("Response ID: " + response.id());
-        System.out.println("Response Model: " + response.model());
-        System.out.println("Response Created At: " + response.createdAt());
-        System.out.println("Response Output: " + response.output());
+        System.out.println(response.output());
     }
 }
\ No newline at end of file
diff --git a/samples/python/quickstart/quickstart-chat-with-agent.py b/samples/python/quickstart/quickstart-chat-with-agent.py
index 4d70ac4af..e5239c532 100644
--- a/samples/python/quickstart/quickstart-chat-with-agent.py
+++ b/samples/python/quickstart/quickstart-chat-with-agent.py
@@ -1,34 +1,32 @@
-import os
-from dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 
-load_dotenv()
+# Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+FOUNDRY_PROJECT_ENDPOINT = "your_project_endpoint"
+AGENT_NAME = "your_agent_name"
 
-project_client = AIProjectClient(
-    endpoint=os.environ["PROJECT_ENDPOINT"],
+# Create project and openai clients to call Foundry API
+project = AIProjectClient(
+    endpoint=FOUNDRY_PROJECT_ENDPOINT,
     credential=DefaultAzureCredential(),
 )
+openai = project.get_openai_client()
 
-agent_name = os.environ["AGENT_NAME"]
-openai_client = project_client.get_openai_client()
-
-# Optional Step: Create a conversation to use with the agent
-conversation = openai_client.conversations.create()
-print(f"Created conversation (id: {conversation.id})")
+# Create a conversation for multi-turn chat
+conversation = openai.conversations.create()
 
 # Chat with the agent to answer questions
-response = openai_client.responses.create(
-    conversation=conversation.id, #Optional conversation context for multi-turn
-    extra_body={"agent": {"name": agent_name, "type": "agent_reference"}},
+response = openai.responses.create(
+    conversation=conversation.id,
+    extra_body={"agent": {"name": AGENT_NAME, "type": "agent_reference"}},
     input="What is the size of France in square miles?",
 )
-print(f"Response output: {response.output_text}")
+print(response.output_text)
 
-# Optional Step: Ask a follow-up question in the same conversation
-response = openai_client.responses.create(
+# Ask a follow-up question in the same conversation
+response = openai.responses.create(
     conversation=conversation.id,
-    extra_body={"agent": {"name": agent_name, "type": "agent_reference"}},
+    extra_body={"agent": {"name": AGENT_NAME, "type": "agent_reference"}},
     input="And what is the capital city?",
 )
-print(f"Response output: {response.output_text}")
+print(response.output_text)
diff --git a/samples/python/quickstart/quickstart-create-agent.py b/samples/python/quickstart/quickstart-create-agent.py
index bf3eca8ac..a1ea18fb2 100644
--- a/samples/python/quickstart/quickstart-create-agent.py
+++ b/samples/python/quickstart/quickstart-create-agent.py
@@ -1,20 +1,22 @@
-import os
-from dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 from azure.ai.projects.models import PromptAgentDefinition
 
-load_dotenv()
+# Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+FOUNDRY_PROJECT_ENDPOINT = "your_project_endpoint"
+AGENT_NAME = "your_agent_name"
 
-project_client = AIProjectClient(
-    endpoint=os.environ["PROJECT_ENDPOINT"],
+# Create project client to call Foundry API
+project = AIProjectClient(
+    endpoint=FOUNDRY_PROJECT_ENDPOINT,
     credential=DefaultAzureCredential(),
 )
 
-agent = project_client.agents.create_version(
-    agent_name=os.environ["AGENT_NAME"],
+# Create an agent with a model and instructions
+agent = project.agents.create_version(
+    agent_name=AGENT_NAME,
     definition=PromptAgentDefinition(
-        model=os.environ["MODEL_DEPLOYMENT_NAME"],
+        model="gpt-5-mini",  # supports all Foundry direct models
         instructions="You are a helpful assistant that answers general questions",
     ),
 )
diff --git a/samples/python/quickstart/quickstart-responses.py b/samples/python/quickstart/quickstart-responses.py
index 75bdc0ada..396ff22b7 100644
--- a/samples/python/quickstart/quickstart-responses.py
+++ b/samples/python/quickstart/quickstart-responses.py
@@ -1,22 +1,19 @@
-import os
-from dotenv import load_dotenv
 from azure.identity import DefaultAzureCredential
 from azure.ai.projects import AIProjectClient
 
-load_dotenv()
+# Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+FOUNDRY_PROJECT_ENDPOINT = "your_project_endpoint"
 
-print(f"Using PROJECT_ENDPOINT: {os.environ['PROJECT_ENDPOINT']}")
-print(f"Using MODEL_DEPLOYMENT_NAME: {os.environ['MODEL_DEPLOYMENT_NAME']}")
-
-project_client = AIProjectClient(
-    endpoint=os.environ["PROJECT_ENDPOINT"],
+# Create project and openai clients to call Foundry API
+project = AIProjectClient(
+    endpoint=FOUNDRY_PROJECT_ENDPOINT,
     credential=DefaultAzureCredential(),
 )
+openai = project.get_openai_client()
 
-openai_client = project_client.get_openai_client()
-
-response = openai_client.responses.create(
-    model=os.environ["MODEL_DEPLOYMENT_NAME"],
+# Run a responses API call
+response = openai.responses.create(
+    model="gpt-5-mini",  # supports all Foundry direct models
     input="What is the size of France in square miles?",
 )
 print(f"Response output: {response.output_text}")
\ No newline at end of file
diff --git a/samples/typescript/quickstart/chat-with-agent/src/quickstart-chat-with-agent.ts b/samples/typescript/quickstart/chat-with-agent/src/quickstart-chat-with-agent.ts
index f6818fc3d..5f178bd52 100644
--- a/samples/typescript/quickstart/chat-with-agent/src/quickstart-chat-with-agent.ts
+++ b/samples/typescript/quickstart/chat-with-agent/src/quickstart-chat-with-agent.ts
@@ -1,52 +1,41 @@
 import { DefaultAzureCredential } from "@azure/identity";
 import { AIProjectClient } from "@azure/ai-projects";
-import "dotenv/config";
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project endpoint>";
-const deploymentName = process.env["MODEL_DEPLOYMENT_NAME"] || "<model deployment name>";
+// Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+const PROJECT_ENDPOINT = "your_project_endpoint";
+const AGENT_NAME = "your_agent_name";
 
 async function main(): Promise<void> {
-    const project = new AIProjectClient(projectEndpoint, new DefaultAzureCredential());
-    const openAIClient = project.getOpenAIClient();
-    
-    // Create agent
-    console.log("Creating agent...");
-    const agent = await project.agents.createVersion("my-agent-basic", {
-        kind: "prompt",
-        model: deploymentName,
-        instructions: "You are a helpful assistant that answers general questions",
-    });
-    console.log(`Agent created (id: ${agent.id}, name: ${agent.name}, version: ${agent.version})`);
-    
-    // Create conversation with initial user message
-    // You can save the conversation ID to database to retrieve later
-    console.log("\nCreating conversation with initial user message...");
-    const conversation = await openAIClient.conversations.create({
-        items: [
-            { type: "message", role: "user", content: "What is the size of France in square miles?" },
-        ],
-    });
-    console.log(`Created conversation with initial user message (id: ${conversation.id})`);
+    // Create project and openai clients to call Foundry API
+    const project = new AIProjectClient(PROJECT_ENDPOINT, new DefaultAzureCredential());
+    const openai = await project.getOpenAIClient();
 
-    // Generate response using the agent
-    console.log("\nGenerating response...");
-    const response = await openAIClient.responses.create(
+    // Create a conversation for multi-turn chat
+    const conversation = await openai.conversations.create();
+
+    // Chat with the agent to answer questions
+    const response = await openai.responses.create(
         {
             conversation: conversation.id,
+            input: "What is the size of France in square miles?",
         },
         {
-            body: { agent: { name: agent.name, type: "agent_reference" } },
+            body: { agent: { name: AGENT_NAME, type: "agent_reference" } },
         },
     );
-    console.log(`Response output: ${response.output_text}`);
-
-     // Clean up
-    console.log("\nCleaning up resources...");
-    await openAIClient.conversations.delete(conversation.id);
-    console.log("Conversation deleted");
+    console.log(response.output_text);
 
-    await project.agents.deleteVersion(agent.name, agent.version);
-    console.log("Agent deleted");
+    // Ask a follow-up question in the same conversation
+    const response2 = await openai.responses.create(
+        {
+            conversation: conversation.id,
+            input: "And what is the capital city?",
+        },
+        {
+            body: { agent: { name: AGENT_NAME, type: "agent_reference" } },
+        },
+    );
+    console.log(response2.output_text);
 }
 
 main().catch(console.error);
\ No newline at end of file
diff --git a/samples/typescript/quickstart/create-agent/src/quickstart-create-agent.ts b/samples/typescript/quickstart/create-agent/src/quickstart-create-agent.ts
index 120ce8f23..8df6e7095 100644
--- a/samples/typescript/quickstart/create-agent/src/quickstart-create-agent.ts
+++ b/samples/typescript/quickstart/create-agent/src/quickstart-create-agent.ts
@@ -1,18 +1,21 @@
 import { DefaultAzureCredential } from "@azure/identity";
 import { AIProjectClient } from "@azure/ai-projects";
-import "dotenv/config";
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project endpoint>";
-const deploymentName = process.env["MODEL_DEPLOYMENT_NAME"] || "<model deployment name>";
+// Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+const PROJECT_ENDPOINT = "your_project_endpoint";
+const AGENT_NAME = "your_agent_name";
 
 async function main(): Promise<void> {
-    const project = new AIProjectClient(projectEndpoint, new DefaultAzureCredential());
-    const agent = await project.agents.createVersion("my-agent-basic", {
+    // Create project client to call Foundry API
+    const project = new AIProjectClient(PROJECT_ENDPOINT, new DefaultAzureCredential());
+
+    // Create an agent with a model and instructions
+    const agent = await project.agents.createVersion(AGENT_NAME, {
         kind: "prompt",
-        model: deploymentName,
+        model: "gpt-5-mini",  // supports all Foundry direct models
         instructions: "You are a helpful assistant that answers general questions",
-  });
-  console.log(`Agent created (id: ${agent.id}, name: ${agent.name}, version: ${agent.version})`);
+    });
+    console.log(`Agent created (id: ${agent.id}, name: ${agent.name}, version: ${agent.version})`);
 }
 
 main().catch(console.error);
\ No newline at end of file
diff --git a/samples/typescript/quickstart/responses/src/quickstart-responses.ts b/samples/typescript/quickstart/responses/src/quickstart-responses.ts
index ad68301a1..9120ae67e 100644
--- a/samples/typescript/quickstart/responses/src/quickstart-responses.ts
+++ b/samples/typescript/quickstart/responses/src/quickstart-responses.ts
@@ -1,15 +1,17 @@
 import { DefaultAzureCredential } from "@azure/identity";
 import { AIProjectClient } from "@azure/ai-projects";
-import "dotenv/config";
 
-const projectEndpoint = process.env["PROJECT_ENDPOINT"] || "<project endpoint>";
-const deploymentName = process.env["MODEL_DEPLOYMENT_NAME"] || "<model deployment name>";
+// Format: "https://resource_name.ai.azure.com/api/projects/project_name"
+const PROJECT_ENDPOINT = "your_project_endpoint";
 
 async function main(): Promise<void> {
-    const project = new AIProjectClient(projectEndpoint, new DefaultAzureCredential());
-    const openAIClient = project.getOpenAIClient();
-    const response = await openAIClient.responses.create({
-        model: deploymentName,
+    // Create project and openai clients to call Foundry API
+    const project = new AIProjectClient(PROJECT_ENDPOINT, new DefaultAzureCredential());
+    const openai = await project.getOpenAIClient();
+
+    // Run a responses API call
+    const response = await openai.responses.create({
+        model: "gpt-5-mini",  // supports all Foundry direct models
         input: "What is the size of France in square miles?",
     });
     console.log(`Response output: ${response.output_text}`);