Add next/previous page navigation to lessons

Fixes #102

Add navigation links to each lesson's README file.

* **00-course-setup/README.md**
  - Add a link to the next lesson, "Introduction to AI Agents and Agent Use Cases."

* **01-intro-to-ai-agents/README.md**
  - Add a link to the previous lesson, "Course Setup."
  - Add a link to the next lesson, "Exploring Agentic Frameworks."

* **02-explore-agentic-frameworks/README.md**
  - Add a link to the previous lesson, "Introduction to AI Agents and Agent Use Cases."
  - Add a link to the next lesson, "Understanding Agentic Design Patterns."

* **03-agentic-design-patterns/README.md**
  - Add a link to the previous lesson, "Exploring Agentic Frameworks."
  - Add a link to the next lesson, "Tool Use Design Pattern."

* **04-tool-use/README.md**
  - Add a link to the previous lesson, "Understanding Agentic Design Patterns."
  - Add a link to the next lesson, "Agentic RAG."

* **05-agentic-rag/README.md**
  - Add a link to the previous lesson, "Tool Use Design Pattern."
  - Add a link to the next lesson, "Building Trustworthy AI Agents."

* **06-building-trustworthy-agents/README.md**
  - Add a link to the previous lesson, "Agentic RAG."
  - Add a link to the next lesson, "Planning Design Pattern."

* **07-planning-design/README.md**
  - Add a link to the previous lesson, "Building Trustworthy AI Agents."
  - Add a link to the next lesson, "Multi-Agent Design Pattern."

* **08-multi-agent/README.md**
  - Add a link to the previous lesson, "Planning Design."
  - Add a link to the next lesson, "Metacognition in AI Agents."

* **09-metacognition/README.md**
  - Add a link to the previous lesson, "Multi-Agent Design Pattern."
  - Add a link to the next lesson, "AI Agents in Production."

* **10-ai-agents-production/README.md**
  - Add a link to the previous lesson, "Metacognition Design Pattern."

---

For more details, open the [Copilot Workspace session](https://copilot-workspace.githubnext.com/microsoft/ai-agents-for-beginners/issues/102?shareId=XXXX-XXXX-XXXX-XXXX).

Author: ShivamGoyal03

00-course-setup/README.md

@@ -105,3 +105,7 @@ from azure.identity import DefaultAzureCredential, InteractiveBrowserCredential
 You are now ready to run the code of this course, happy learning more about the world of AI Agents!
 
 If you have any issues running this setup, hop into our <a href="https://discord.gg/kzRShWzttr" target="_blank">Azure AI Community Discord</a> or <a href="https://github.com/microsoft/ai-agents-for-beginners/issues?WT.mc_id=academic-105485-koreyst" target="_blank">create an issue</a>.
+
+## Next Lesson
+
+[Introduction to AI Agents and Agent Use Cases](../01-intro-to-ai-agents/README.md)

01-intro-to-ai-agents/README.md

@@ -95,3 +95,10 @@ Agentic Frameworks allow developers to implement agentic patterns through code.
 
 In this course, we will explore the research-driven AutoGen framework and the production ready Agent framework from Semantic Kernel.
 
+## Previous Lesson
+
+[Course Setup](../00-course-setup/README.md)
+
+## Next Lesson
+
+[Exploring Agentic Frameworks](../02-explore-agentic-frameworks/README.md)

02-explore-agentic-frameworks/README.md

@@ -745,3 +745,11 @@ For AutoGen and Semantic Kernel, you can also integrate with Azure services, but
 - <a href="https://learn.microsoft.com/semantic-kernel/frameworks/agent/?pivots=programming-language-csharp" target="_blank">Semantic Kernel .Net Agent Framework</a>
 - <a href="https://learn.microsoft.com/azure/ai-services/agents/overview" target="_blank">Azure AI Agent service</a>
 - <a href="https://techcommunity.microsoft.com/blog/educatordeveloperblog/using-azure-ai-agent-service-with-autogen--semantic-kernel-to-build-a-multi-agen/4363121" target="_blank">Using Azure AI Agent Service with AutoGen / Semantic Kernel to build a multi-agent's solution</a>
+
+## Previous Lesson
+
+[Introduction to AI Agents and Agent Use Cases](../01-intro-to-ai-agents/README.md)
+
+## Next Lesson
+
+[Understanding Agentic Design Patterns](../03-agentic-design-patterns/README.md)

03-agentic-design-patterns/README.md

@@ -89,3 +89,10 @@ Imagine you are designing a Travel Agent, here is how you could think about usin
 - <a href="https://microsoft.com" target="_blank">The HAX Toolkit Project - Microsoft Research</a>
 - <a href="https://responsibleaitoolbox.ai" target="_blank">Responsible AI Toolbox</a>
 
+## Previous Lesson
+
+[Exploring Agentic Frameworks](../02-explore-agentic-frameworks/README.md)
+
+## Next Lesson
+
+[Tool Use Design Pattern](../04-tool-use/README.md)

04-tool-use/README.md

@@ -312,3 +312,11 @@ Running the app in a secure environment further enhances protection. In enterpri
 - <a href="https://learn.microsoft.com/semantic-kernel/concepts/ai-services/chat-completion/function-calling/?pivots=programming-language-python#1-serializing-the-functions" target="_blank">Semantic Kernel Function Calling Tutorial</a>
 - <a href="https://github.com/microsoft/semantic-kernel/blob/main/python/samples/getting_started_with_agents/openai_assistant/step3_assistant_tool_code_interpreter.py" target="_blank">Semantic Kernel Code Interpreter</a>
 - <a href="https://microsoft.github.io/autogen/dev/user-guide/core-user-guide/components/tools.html" target="_blank">Autogen Tools</a>
+
+## Previous Lesson
+
+[Understanding Agentic Design Patterns](../03-agentic-design-patterns/README.md)
+
+## Next Lesson
+
+[Agentic RAG](../05-agentic-rag/README.md)

05-agentic-rag/README.md

@@ -130,3 +130,11 @@ Agentic RAG represents a natural evolution in how AI systems handle complex, dat
 - <a href="https://arxiv.org/abs/2303.11366" target="_blank">2303.11366 Reflexion: Language Agents with Verbal Reinforcement Learning</a>
 - <a href="https://arxiv.org/abs/2305.11738" target="_blank">2305.11738 CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing</a>
 - <a href="https://arxiv.org/abs/2501.09136" target="_blank">2501.09136 Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG</a>
+
+## Previous Lesson
+
+[Tool Use Design Pattern](../04-tool-use/README.md)
+
+## Next Lesson
+
+[Building Trustworthy AI Agents](../06-building-trustworthy-agents/README.md)

06-building-trustworthy-agents/README.md

@@ -187,3 +187,11 @@ Building trustworthy AI agents requires careful design, robust security measures
 - <a href="https://learn.microsoft.com/azure/ai-studio/concepts/evaluation-approach-gen-ai" target="_blank">Evaluation of generative AI models and AI applications</a>
 - <a href="https://learn.microsoft.com/azure/ai-services/openai/concepts/system-message?context=%2Fazure%2Fai-studio%2Fcontext%2Fcontext&tabs=top-techniques" target="_blank">Safety system messages</a>
 - <a href="https://blogs.microsoft.com/wp-content/uploads/prod/sites/5/2022/06/Microsoft-RAI-Impact-Assessment-Template.pdf?culture=en-us&country=us" target="_blank">Risk Assessment Template</a>
+
+## Previous Lesson
+
+[Agentic RAG](../05-agentic-rag/README.md)
+
+## Next Lesson
+
+[Planning Design Pattern](../07-planning-design/README.md)

07-planning-design/README.md

@@ -288,3 +288,11 @@ In this article we have looked at an example of how we can create a planner that
 ## Additional Resources
 
 * AutoGen Magentic One - A Generalist multi-agent system for solving complex tasks and has achieved impressive results on multiple challenging agentic benchmarks. Reference: <a href="https://github.com/microsoft/autogen/tree/main/python/packages/autogen-magentic-one" target="_blank">autogen-magentic-one</a>. In this implementation the orchestrator create task specific plan and delegates these tasks to the available agents. In addition to planning the orchestrator also employs a tracking mechanism to monitor the progress of the task and re-plans as required.
+
+## Previous Lesson
+
+[Building Trustworthy AI Agents](../06-building-trustworthy-agents/README.md)
+
+## Next Lesson
+
+[Multi-Agent Design Pattern](../08-multi-agent/README.md)

08-multi-agent/README.md

@@ -163,11 +163,10 @@ Question: When should you consider using multi-agents?
 
 [Solution quiz](./solution/solution-quiz.md)
 
-## Summary
+## Previous Lesson
 
-In this lesson, we've looked at the multi-agent design pattern, including the scenarios where multi-agents are applicable, the advantages of using multi-agents over a singular agent, the building blocks of implementing the multi-agent design pattern, and how to have visibility into how the multiple agents are interacting with each other.
+[Planning Design](../07-planning-design/README.md)
 
-## Additional resources
+## Next Lesson
 
-- <a href="https://microsoft.github.io/autogen/stable/user-guide/core-user-guide/design-patterns/intro.html" target="_blank">AutoGen design patterns</a>
-- <a href="https://www.analyticsvidhya.com/blog/2024/10/agentic-design-patterns/" target="_blank">Agentic design patterns</a>
+[Metacognition in AI Agents](../09-metacognition/README.md)

09-metacognition/README.md

@@ -1417,3 +1417,11 @@ This is a simple form of metacognition where the system is capable of adjusting
 ### Conclusion
 
 Metacognition is a powerful tool that can significantly enhance the capabilities of AI agents. By incorporating metacognitive processes, you can design agents that are more intelligent, adaptable, and efficient. Use the additional resources to further explore the fascinating world of metacognition in AI agents.
+
+## Previous Lesson
+
+[Multi-Agent Design Pattern](../08-multi-agent/README.md)
+
+## Next Lesson
+
+[AI Agents in Production](../10-ai-agents-production/README.md)

10-ai-agents-production/README.md

@@ -63,3 +63,7 @@ If you want to continue your learning and building with AI Agents, join the <a h
 We host workshops, community roundtables and "ask me anything" sessions there.
 
 We also have a Learn collection of additional materials that can help you start building AI Agents in production.
+
+## Previous Lesson
+
+[Metacognition Design Pattern](../09-metacognition/README.md)