diff --git a/docs/advanced/composition.mdx b/docs/advanced/composition.mdx
index 3b5c2680e..42a8b2a7e 100644
--- a/docs/advanced/composition.mdx
+++ b/docs/advanced/composition.mdx
@@ -34,9 +34,10 @@ Chain different workflow patterns together:
 
 ```python
 from mcp_agent.app import MCPApp
-from mcp_agent.workflows import Workflow, WorkflowResult
+from mcp_agent.executor.workflow import Workflow, WorkflowResult
 from mcp_agent.agents.agent import Agent
 from mcp_agent.workflows.llm.augmented_llm_openai import OpenAIAugmentedLLM
+from datetime import datetime
 
 app = MCPApp(name="composed_agent")
 
diff --git a/docs/advanced/monitoring.mdx b/docs/advanced/monitoring.mdx
index dc450e04e..e619be5c9 100644
--- a/docs/advanced/monitoring.mdx
+++ b/docs/advanced/monitoring.mdx
@@ -155,7 +155,7 @@ Integrate observability into your MCP Agent workflows:
 ```python
 # workflows/observable_workflow.py
 from mcp_agent.app import MCPApp
-from mcp_agent.workflows import Workflow, WorkflowResult
+from mcp_agent.executor.workflow import Workflow, WorkflowResult
 from mcp_agent.agents.agent import Agent
 from mcp_agent.workflows.llm.augmented_llm_openai import OpenAIAugmentedLLM
 from opentelemetry import trace, metrics
@@ -1460,7 +1460,7 @@ receivers:
 - name: 'critical-alerts'
   slack_configs:
   - channel: '#critical-alerts'
-    title: '=¨ CRITICAL: MCP Agent Alert'
+    title: '=� CRITICAL: MCP Agent Alert'
     text: |
       {{ range .Alerts }}
       *Alert:* {{ .Annotations.summary }}
@@ -1492,7 +1492,7 @@ receivers:
 - name: 'cost-alerts'
   slack_configs:
   - channel: '#cost-monitoring'
-    title: '=° LLM Cost Alert'
+    title: '=� LLM Cost Alert'
     text: |
       {{ range .Alerts }}
       {{ .Annotations.summary }}
@@ -1633,7 +1633,7 @@ class AlertManager:
             if handler:
                 await handler(alert)
             
-            print(f"=¨ ALERT: {alert.severity.value.upper()} - {alert.message}")
+            print(f"=� ALERT: {alert.severity.value.upper()} - {alert.message}")
     
     async def resolve_alert(self, name: str):
         """Resolve alerts by name."""
diff --git a/docs/advanced/temporal.mdx b/docs/advanced/temporal.mdx
index d167c5827..1888f48b0 100644
--- a/docs/advanced/temporal.mdx
+++ b/docs/advanced/temporal.mdx
@@ -79,7 +79,7 @@ mcp-agent supports both `asyncio` and `temporal` execution engines. While asynci
     ```python worker.py
     import asyncio
     from mcp_agent.app import MCPApp
-    from mcp_agent.workflows import Workflow, WorkflowResult
+    from mcp_agent.executor.workflow import Workflow, WorkflowResult
     from mcp_agent.executor.temporal import create_temporal_worker_for_app
     
     app = MCPApp(name="my_agent")
@@ -484,7 +484,7 @@ Temporal workflows are defined the same way as asyncio workflows:
 
 ```python
 from mcp_agent.app import MCPApp
-from mcp_agent.workflows import Workflow, WorkflowResult
+from mcp_agent.executor.workflow import Workflow, WorkflowResult
 from mcp_agent.agents.agent import Agent
 from mcp_agent.workflows.llm.augmented_llm_openai import OpenAIAugmentedLLM
 
diff --git a/docs/cloud/getting-started.mdx b/docs/cloud/getting-started.mdx
index 2414bc51a..565017f5f 100644
--- a/docs/cloud/getting-started.mdx
+++ b/docs/cloud/getting-started.mdx
@@ -130,7 +130,7 @@ Let's create and deploy a simple agent that can fetch web content and summarize
 import asyncio
 from mcp_agent.app import MCPApp
 from mcp_agent.agents.agent import Agent
-from mcp_agent.workflows import Workflow, WorkflowResult
+from mcp_agent.executor.workflow import Workflow, WorkflowResult
 from mcp_agent.workflows.llm.augmented_llm_openai import OpenAIAugmentedLLM
 
 app = MCPApp(name="web_summarizer")
diff --git a/docs/concepts/workflows.mdx b/docs/concepts/workflows.mdx
index 9817b4f3f..2378545f9 100644
--- a/docs/concepts/workflows.mdx
+++ b/docs/concepts/workflows.mdx
@@ -24,7 +24,7 @@ The `Workflow` class is the foundation for building complex agent behaviors. It
 
 ```python
 from mcp_agent.app import MCPApp
-from mcp_agent.workflows import Workflow, WorkflowResult
+from mcp_agent.executor.workflow import Workflow, WorkflowResult
 
 app = MCPApp(name="my_agent")