feat: Introduce Sequential Agent tutorial for google ADK

ai_agent_framework_crash_course/google_adk_crash_course/9_multi_agent_patterns/9_1_sequential_agent/.env.example

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+# If using Gemini via Google AI Studio
+GOOGLE_GENAI_USE_VERTEXAI=False
+GOOGLE_API_KEY="your-api-key"

ai_agent_framework_crash_course/google_adk_crash_course/9_multi_agent_patterns/9_1_sequential_agent/README.md

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+# 🎯 Tutorial 9.1: Sequential Agents - Business Implementation Plan Generator
+
+## 🎯 What You'll Learn
+
+- **Sequential Agent Composition**: How to orchestrate multiple specialized agents in sequence
+- **AgentTool Integration**: Wrapping agents as tools for enhanced capabilities
+- **Web Search Integration**: Real-time market intelligence through search agents
+- **Business Analysis Pipeline**: From market research to implementation planning
+- **Streamlit Web Interface**: User-friendly application for business planning
+
+## 🧠 Core Concept: Sequential Agent with Search Capabilities
+
+According to the [ADK workflow agents documentation](https://google.github.io/adk-docs/agents/workflow-agents/), **Sequential Agents** execute sub-agents one after another, in sequence. This tutorial demonstrates a **Business Implementation Plan Generator** that combines web search capabilities with sequential analysis:
+
+```
+Business Topic → SequentialAgent → 4 Sub-agents (Sequential Execution)
+                ↓
+        [Market Research + Web Search] → [SWOT Analysis] → [Strategy] → [Implementation]
+                ↓
+        Complete Business Implementation Plan
+```
+
+**Key Innovation**: The Market Research Agent uses a specialized Search Agent (wrapped as AgentTool) to access real-time web search capabilities for current market intelligence.
+
+## 📁 Project Structure
+
+```
+9_1_sequential_agent/
+├── agent.py              # Business implementation plan generator with search capabilities
+├── app.py                # Streamlit web interface for business planning
+├── requirements.txt      # Python dependencies
+└── README.md            # This documentation
+```
+
+## 🚀 Getting Started
+
+### 1. Install Dependencies
+```bash
+cd 9_1_sequential_agent
+pip install -r requirements.txt
+```
+
+### 2. Set Up Environment
+Create a `.env` file with your Google API key:
+```bash
+echo "GOOGLE_API_KEY=your_ai_studio_key_here" > .env
+```
+
+**Important**: Get your API key from [Google AI Studio](https://aistudio.google.com/)
+
+### 3. Run the Streamlit App
+```bash
+streamlit run app.py
+```
+
+This will launch the **Business Implementation Plan Generator Agent** web interface!
+
+## 🧪 How It Works
+
+### **Business Implementation Plan Generation Pipeline**
+
+The agent processes business opportunities through a sophisticated 4-step sequential workflow:
+
+1. **🔍 Market Analysis** - Uses web search for current market information and competitive research
+2. **📊 SWOT Analysis** - Strategic assessment of strengths, weaknesses, opportunities, and threats
+3. **🎯 Strategy Development** - Strategic objectives and action plans
+4. **📋 Implementation Planning** - Detailed execution roadmap and resource requirements
+
+**Key Innovation**: The Market Analysis Agent has access to a specialized Search Agent (wrapped as AgentTool) that can perform real-time web searches using the `google_search` tool. This provides current market intelligence that feeds into the sequential analysis pipeline.
+
+The `SequentialAgent` ensures each step builds upon the previous step's output, creating a comprehensive business implementation plan ready for execution.
+
+**Result**: A complete business implementation plan with market research, strategic analysis, and execution roadmap.
+
+## 🔧 ADK Concepts Demonstrated
+
+### **1. SequentialAgent Pattern**
+The core workflow orchestrator that executes sub-agents in sequence, ensuring each step builds upon the previous step's output.
+
+### **2. AgentTool Integration**
+Advanced pattern where one agent (Search Agent) is wrapped as a tool and used by another agent (Market Researcher) to enhance capabilities.
+
+### **3. Web Search Capabilities**
+Real-time market intelligence through integrated search functionality, providing current data rather than relying on training data.
+
+### **4. Sub-agent Specialization**
+Each sub-agent specializes in a specific business analysis phase, creating a modular and maintainable system.
+
+### **5. Session Management**
+Maintains conversation state across the entire analysis pipeline, ensuring context flows between agents.
+
+### **6. Runner Execution**
+Processes the complete business implementation workflow with proper error handling and response management.
+
+## 🧪 Sample Topics to Try
+
+- **Electric vehicle charging stations** in urban areas
+- **AI-powered healthcare diagnostics** and patient care
+- **Sustainable food delivery** services and packaging
+- **Remote work collaboration** tools and platforms
+- **Renewable energy storage** solutions
+
+## 📊 Expected Output
+
+The sequential agent will provide:
+1. **Market Research**: Competitive analysis and market trends
+2. **SWOT Analysis**: Strategic assessment with actionable insights
+3. **Strategy Plan**: Clear objectives and implementation steps
+4. **Implementation Roadmap**: Practical execution guidance
+
+## 🎯 Learning Objectives
+
+- ✅ Understand how `SequentialAgent` orchestrates sub-agents
+- ✅ Learn to execute sequential agents with Runner and Session management
+- ✅ See how sub-agents can build upon each other's output
+- ✅ Experience a working, executable sequential workflow
+- ✅ Understand AgentTool integration for enhanced capabilities
+
+## 🚀 Next Steps
+
+- Try different business topics to see the sequential workflow in action
+- Experiment with reordering the sub-agents
+- Add more specialized agents to the pipeline
+- Explore other ADK workflow patterns (Parallel, Branching)
+
+## 🔧 Troubleshooting
+
+**Common Issues:**
+- **API Key Error**: Ensure `GOOGLE_API_KEY` is set in `.env`
+- **Import Errors**: Make sure you're in the correct directory
+- **Search Tool Errors**: Verify your API key has access to search capabilities
+
+**Pro Tips:**
+- Start with simple topics to understand the flow
+- Use the Streamlit app for easy testing and visualization
+- The sequential pattern is great for predictable, step-by-step processes
+- Web search integration provides real-time market intelligence
+
+## 📚 Key Takeaways
+
+- **SequentialAgent** is perfect for workflows that must happen in order
+- **AgentTool integration** allows agents to enhance each other's capabilities
+- **Web search capabilities** provide current market intelligence
+- **Sub-agents** can be simple `LlmAgent` instances or complex tool-enabled agents
+- **Clean, readable code** makes it easy to understand and modify
+- **Streamlit interface** provides user-friendly access to complex agent workflows

ai_agent_framework_crash_course/google_adk_crash_course/9_multi_agent_patterns/9_1_sequential_agent/agent.py

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+import os
+import asyncio
+from dotenv import load_dotenv
+from google.adk.agents import LlmAgent, SequentialAgent
+from google.adk.tools import google_search
+from google.adk.tools.agent_tool import AgentTool
+from google.adk.sessions import InMemorySessionService
+from google.adk.runners import Runner
+from google.genai import types
+
+# Load environment variables
+load_dotenv()
+
+# --- Search Agent (Wrapped as AgentTool) ---
+search_agent = LlmAgent(
+    name="search_agent",
+    model="gemini-2.0-flash",
+    description="Conducts web search for current market information and competitive analysis",
+    instruction=(
+        "You are a web search specialist. When given a business topic:\n"
+        "1. Use web search to find current market information\n"
+        "2. Identify key competitors and their market position\n"
+        "3. Gather recent industry trends and market data\n"
+        "4. Find market size estimates and growth projections\n"
+        "5. Provide comprehensive, up-to-date market analysis\n\n"
+        "Always use web search to get the most current information available."
+    ),
+    tools=[google_search]
+)
+
+# --- Simple Sub-agents ---
+market_researcher = LlmAgent(
+    name="market_researcher",
+    model="gemini-2.5-flash",
+    description="Conducts market research and competitive analysis using search capabilities",
+    instruction=(
+        "You are a market research specialist. Given a business topic:\n"
+        "1. Use the search_agent to gather current market information\n"
+        "2. Identify key competitors and their market position\n"
+        "3. Analyze current market trends and opportunities\n"
+        "4. Provide industry insights and market size estimates\n"
+        "5. Synthesize search results into comprehensive market analysis\n\n"
+        "Provide a comprehensive analysis in clear, structured format based on current web research."
+    ),
+    tools=[AgentTool(search_agent)]
+)
+
+swot_analyzer = LlmAgent(
+    name="swot_analyzer",
+    model="gemini-2.5-flash",
+    description="Performs SWOT analysis based on market research",
+    instruction=(
+        "You are a strategic analyst. Given market research findings:\n"
+        "1. Identify internal strengths and competitive advantages\n"
+        "2. Assess internal weaknesses and limitations\n"
+        "3. Identify external opportunities in the market\n"
+        "4. Evaluate external threats and challenges\n\n"
+        "Provide a clear SWOT analysis with actionable insights."
+    )
+)
+
+strategy_formulator = LlmAgent(
+    name="strategy_formulator",
+    model="gemini-2.5-flash",
+    description="Develops strategic objectives and action plans",
+    instruction=(
+        "You are a strategic planner. Given SWOT analysis results:\n"
+        "1. Define 3-5 key strategic objectives\n"
+        "2. Create specific action items for each objective\n"
+        "3. Recommend realistic timeline for implementation\n"
+        "4. Define success metrics and KPIs to track\n\n"
+        "Provide a clear strategic plan with actionable steps."
+    )
+)
+
+implementation_planner = LlmAgent(
+    name="implementation_planner",
+    model="gemini-2.5-flash",
+    description="Creates detailed implementation roadmap",
+    instruction=(
+        "You are an implementation specialist. Given the strategy plan:\n"
+        "1. Identify required resources (human, financial, technical)\n"
+        "2. Define key milestones and checkpoints\n"
+        "3. Develop risk mitigation strategies\n"
+        "4. Provide final recommendations with confidence level\n\n"
+        "Create a practical implementation roadmap."
+    )
+)
+
+# --- Sequential Agent (Pure Sequential Pattern) ---
+business_intelligence_team = SequentialAgent(
+    name="business_intelligence_team",
+    description="Sequentially processes business intelligence through research, analysis, strategy, and planning",
+    sub_agents=[
+        market_researcher,      # Step 1: Market research (with search capabilities)
+        swot_analyzer,          # Step 2: SWOT analysis
+        strategy_formulator,    # Step 3: Strategy development
+        implementation_planner  # Step 4: Implementation planning
+    ]
+)
+
+# --- Runner Setup for Execution ---
+session_service = InMemorySessionService()
+runner = Runner(
+    agent=business_intelligence_team,
+    app_name="business_intelligence",
+    session_service=session_service
+)
+
+# --- Simple Execution Function ---
+async def analyze_business_intelligence(user_id: str, business_topic: str) -> str:
+    """Process business intelligence through the sequential pipeline"""
+    session_id = f"bi_session_{user_id}"
+    
+    # Create or get session
+    session = await session_service.get_session(
+        app_name="business_intelligence",
+        user_id=user_id,
+        session_id=session_id
+    )
+    if not session:
+        session = await session_service.create_session(
+            app_name="business_intelligence",
+            user_id=user_id,
+            session_id=session_id,
+            state={"business_topic": business_topic, "conversation_history": []}
+        )
+    
+    # Create user content
+    user_content = types.Content(
+        role='user',
+        parts=[types.Part(text=f"Please analyze this business topic: {business_topic}")]
+    )
+    
+    # Run the sequential pipeline
+    response_text = ""
+    async for event in runner.run_async(
+        user_id=user_id,
+        session_id=session_id,
+        new_message=user_content
+    ):
+        if event.is_final_response():
+            if event.content and event.content.parts:
+                response_text = event.content.parts[0].text
+    
+    return response_text

ai_agent_framework_crash_course/google_adk_crash_course/9_multi_agent_patterns/9_1_sequential_agent/app.py

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+import streamlit as st
+import asyncio
+from agent import business_intelligence_team, analyze_business_intelligence
+
+# Page configuration
+st.set_page_config(
+    page_title="Sequential Agent Demo",
+    page_icon=":arrow_right:",
+    layout="wide"
+)
+
+# Title and description
+st.title("🚀 Business Implementation Plan Generator Agent")
+st.markdown("""
+This **Business Implementation Plan Generator Agent** analyzes business opportunities through a comprehensive 4-step process:
+
+1. **🔍 Market Analysis** - Researches market, competitors, and trends using web search
+2. **📊 SWOT Analysis** - Identifies strengths, weaknesses, opportunities, and threats  
+3. **🎯 Strategy Development** - Creates strategic objectives and action plans
+4. **📋 Implementation Planning** - Generates detailed business implementation roadmap
+
+**Result**: A complete business implementation plan ready for execution.
+""")
+
+# This is a placeholder user_id for demo purposes.
+# In a real app, you might use authentication or session state to set this.
+user_id = "demo_user"
+
+# Sample business topics
+sample_topics = [
+    "Electric vehicle charging stations in urban areas",
+    "AI-powered healthcare diagnostics",
+    "Sustainable food delivery services",
+    "Remote work collaboration tools",
+    "Renewable energy storage solutions"
+]
+
+# Main content
+st.header("Generate Your Business Implementation Plan")
+
+# Topic input
+business_topic = st.text_area(
+    "Enter a business opportunity to analyze:",
+    value=sample_topics[0],
+    height=100,
+    placeholder="Describe a business opportunity, industry, or market you'd like to analyze for implementation planning..."
+)
+
+# Sample topics
+st.subheader("Or choose from sample business opportunities:")
+cols = st.columns(len(sample_topics))
+for i, topic in enumerate(sample_topics):
+    if cols[i].button(topic, key=f"topic_{i}"):
+        business_topic = topic
+        st.rerun()
+
+# Analysis button
+if st.button("🚀 Generate Business Implementation Plan", type="primary"):
+    if business_topic.strip():
+        st.info("🚀 Starting business analysis... This will research the market, perform SWOT analysis, develop strategy, and create an implementation plan.")
+        
+        # Display the workflow
+        st.subheader("Business Analysis Workflow")
+        col1, col2, col3, col4 = st.columns(4)
+        
+        with col1:
+            st.markdown("**1. Market Analysis**")
+            st.markdown("🔍 Web search + competitive research")
+        
+        with col2:
+            st.markdown("**2. SWOT Analysis**")
+            st.markdown("📊 Strengths, Weaknesses, Opportunities, Threats")
+        
+        with col3:
+            st.markdown("**3. Strategy Development**")
+            st.markdown("🎯 Strategic objectives and action plans")
+        
+        with col4:
+            st.markdown("**4. Implementation Planning**")
+            st.markdown("📋 Detailed roadmap and execution plan")
+        
+        # Run the actual analysis
+        with st.spinner("Generating comprehensive business implementation plan..."):
+            try:
+                result = asyncio.run(analyze_business_intelligence(user_id, business_topic))
+                
+                st.success("✅ Business Implementation Plan Generated!")
+                st.subheader("Your Business Implementation Plan")
+                st.markdown(result)
+                
+            except Exception as e:
+                st.error(f"❌ Error during analysis: {str(e)}")
+                st.info("Make sure you have set up your GOOGLE_API_KEY in the .env file")
+        
+    else:
+        st.error("Please enter a business opportunity to analyze.")
+
+# How it works (in sidebar)
+with st.sidebar:
+    st.header("How It Works")
+    st.markdown("""
+    The **Business Implementation Plan Generator Agent** uses a sophisticated sequential workflow to create comprehensive business plans:
+
+    1. **🔍 Market Analysis Agent**: Uses web search to research current market conditions, competitors, and trends
+    2. **📊 SWOT Analysis Agent**: Analyzes the market research to identify strategic insights  
+    3. **🎯 Strategy Development Agent**: Creates strategic objectives and action plans based on SWOT analysis
+    4. **📋 Implementation Planning Agent**: Develops detailed execution roadmaps and resource requirements
+
+    **Key Innovation**: The Market Analysis Agent has access to a specialized Search Agent (wrapped as AgentTool) that can perform real-time web searches for current market intelligence.
+
+    Each agent builds upon the previous agent's output, creating a comprehensive business implementation plan ready for execution.
+    """)

ai_agent_framework_crash_course/google_adk_crash_course/9_multi_agent_patterns/9_1_sequential_agent/requirements.txt

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+google-adk>=1.9.0
+streamlit>=1.28.0
+python-dotenv>=1.1.1
+pydantic>=2.0.0

ai_agent_framework_crash_course/google_adk_crash_course/README.md

@@ -54,7 +54,14 @@ This crash course covers the essential concepts of Google ADK through hands-on t
    - Error handling and logging
    - Usage analytics and monitoring
 
-8. **More tutorials coming soon!**
+8. **[8_simple_multi_agent](./8_simple_multi_agent/README.md)** - Multi-agent orchestration
+   - **[8.1 Multi-Agent Researcher](./8_simple_multi_agent/multi_agent_researcher/README.md)** - Research pipeline with specialized agents
+   - Coordinator agent with sub-agents
+   - Sequential workflow: Research → Summarize → Critique
+   - Web search integration and comprehensive analysis
+
+9. **[9_multi_agent_patterns](./9_multi_agent_patterns/README.md)** - Multi-Agent Patterns
+   - **[9.1 Sequential Agent](./9_multi_agent_patterns/9_1_sequential_agent/README.md)** — Deterministic pipeline of sub-agents (e.g., Draft → Critique → Improve)
 
 ## 🛠️ Prerequisites