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https://github.com/github-insight-anz-lab/agentic-aiapp-in-a-day


https://github.com/github-insight-anz-lab/agentic-aiapp-in-a-day

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# Agentic AI App in a Day (Draft)



![Agentic AI App in a Day Cover](res/workshop-cover.png)



## Overview

- Duration: 9am to 4pm

- Demo: Azure Portal & VS Code

- Lab: GitHub Codespaces



### Goal



- Build on the Agentic AI aspects

- Inspire and Motivate 

- Real world ideas for Agentic AI

- Focused on End-to-end building AI-powered applications

- Frictionless learning environment, learn via lab, demo and teaching moments

- Azure AI Protections

- GitHub Copilot Agent Model to accelerate development

- For some people without laptops or limited technical skills, allowing them to watch walkthroughs, whilst others do them



### Audience

- Technical teams

- Senior management like C-levels



### Labs



- Keep lab simple and able to be done end to end

- For experienced developers, share the accelerator repos and let them explore



Note: some of the labs will be adjusted based on the resources and licences available for the participants to use.



## Presentation #1: Morning, Kick-start – 30 min

**Topics:** Basic Concepts and Overview

- Azure AI + Agentic AI overview  

- Agentic AI design patterns (Planning, Tool Use, Reflection, Multi-agent)  

- Agent architectures: ReAct, Chain-of-Thought

- Memory systems for agents (short-term, long-term, episodic)

- Tool integration patterns and API orchestration

- Intelligent data layers (Azure AI Search, RAG)  

- Low/No Code option in Copilot Studio (vs pro-code)



## Demo #1: AI App Demo - 15min

**Showcasing a fun AI App**

- use a Accelerator Repo

- Daniel's LEGO coding chatbot app demo



## Lab #1: AI Foundry Integration & Extension - 50min

**Explore AI Foundry services:**

- Use Playground and Model Catalog 

- Various Azure AI Services

- Customize agent orchestration using no-code / low-code blocks (Functions)

- Connect additional tools and knowledge bases (e.g., a calculator API, web search API)

- Connect Agents



## Demo #2: Complex AI App Demo - 15min

***Demonstrating Advanced AI Solutions**

- use a Accelerator Repo

- refer to the repo list in the end



## Lab #2: Add Intelligent Data Layer - 50min

**Integrate Azure AI Search or Cosmos DB:**

- Ingest doc into Azure AI Search

- Use Document Intelligence Service

- Connect agent to knowledge base

- Demonstrate contextual reasoning

- Build a memory/retrieval plugin with Semantic Kernel

- Advance query, score profile, index, indexer in AI Search



## Presentation #2: After Lunch – 30min

**Topic:** Building Production-Ready AI Apps with Agentic Concepts

- Technical Deep Dive: Advanced reasoning architectures and hybrid - approaches for complex problem-solving

- Platform-First Strategies: Scaling, API management, DevOps, and platform selection best practices

- Practical Considerations: Memory, cost, performance optimization - and error handling strategies

- Enterprise Readiness: Security, evaluation, testing, and compliance frameworks for production deployment

- Real-World Implementation Patterns: Customer service, document processing, developer tools, and multi-modal applications



## Demo #3: GitHub Copilot Coding Assistant for AI App - 15min

**Developer experience showcase:**

- Prompt-driven coding assistant (e.g., auto-generate unit tests, fix bugs)  

- Refactoring, adding comments/images, reformatting examples  

- Show how devs stay in control but move faster



## Lab #3: AI Agent 101 & Semantic Kernel + MCP - 70min

**Build and extend your first agentic AI app:**

- Implement the Prompt → Plan → Act → Reflect loop  

- Use Semantic Kernel for memory, planning, and tool integration  

- Chain outputs between tools and functions

- Build and integrate MCP for advanced orchestration and extensibility

- Experiment with adding new skills,



## Demo #4: Multi-Agent Solution Walkthrough - 15min

**Showcase advanced agent collaboration and orchestration:**

- Demonstrate multi-agent workflows using Azure AI Foundry Services

- Highlight agent collaboration: perception → planning → action loop

- Explore coordination strategies and communication between agents

- Present a real-world scenario (Daniel's agentic LEGO demo) to illustrate practical applications



## Lab #4: AI Integration, Deployment & Productionise - 70min

**Deploy and operationalize your agentic AI app:**

- Containerize the agent app for portability and scalability

- Deploy to Azure using ACA, AKS, or App Service with CI/CD

- Expose APIs securely via Azure API Management (auth, rate limits, monitoring)

- Implement logging, monitoring, and alerting for production readiness

- Apply security best practices and cost controls



## Presentation #3: Afternoon – 30min

**Topic:** Wrap-Up: Responsible AI & Future Considerations

- Responsible AI and Guiderails: Content filtering, prompt injection defense, evaluation, and monitoring

- Observability & Operations: Agent analytics, performance metrics, cost tracking, and debugging

- Advanced Topics & Future Trends: Fine-tuning, multi-modal agents, edge deployment, and emerging frameworks

- Lessons Learned & Best Practices: Common pitfalls, testing strategies, and migration patterns

- Next Steps & Resources: Certification paths, community support, and building your first production agent



## Azure Services to be considered

- **Azure AI Foundry (Model Catalog, Playground)** – To explore and test models  

- **Azure AI Foundry – Agent Service** – For orchestrating multi-agent systems  

- **Azure AI Services** – For integrating vision, speech, etc.  

- **Azure OpenAI** – LLMs for chat, planning, coding, summarization  

- **Azure AI Search** – Intelligent data layer for RAG

- **APIM** – Secure, scalable API layer

- **Azure Functions** – Serverless compute for tool integration

- **Azure Logic Apps** – Workflow automation for tool orchestration

- **App Service / AKS / ACA** – App hosting  

- **Azure DevOps / GitHub Actions** – CI/CD for agent apps

- **Azure Monitor / Application Insights** – Monitoring and logging

- **Azure Key Vault** – Secure secrets management

- **Azure Storage / Cosmos DB** – Data storage for agent state and knowledge



## Dev toolchain to be considered

- **Semantic Kernel** – For agent memory, planning, and tool integration

- **Visual Studio Code** – IDE for development

- **Jupyter Notebooks** – For interactive data exploration and model testing

- **GitHub Codespaces** – Cloud-based dev environment for labs

- **GitHub or Azure DevOps** – Source control and CI/CD pipelines and project management

- **Azure CLI / PowerShell** – Command-line tools for Azure management

- **Bicep** – Infrastructure as Code for Azure resources



## Lab Exercise to be considered



- https://github.com/Azure-Samples/AI-Gateway

- https://github.com/microsoft/AI-For-Beginners

- https://github.com/microsoft/ai-agents-for-beginners



## Accelerator Repo to be considered



- https://github.com/Azure-Samples/get-started-with-ai-chat

- https://github.com/Azure-Samples/get-started-with-ai-agents

- https://github.com/microsoft/Multi-Agent-Custom-Automation-Engine-Solution-Accelerator

- https://github.com/microsoft/content-processing-solution-accelerator

- https://github.com/microsoft/document-generation-solution-accelerator

- https://github.com/microsoft/Build-your-own-copilot-Solution-Accelerator

- https://github.com/microsoft/Modernize-your-code-solution-accelerator

- https://github.com/Azure-Samples/Azure-Language-OpenAI-Conversational-Agent-Accelerator

- https://github.com/microsoft/Conversation-Knowledge-Mining-Solution-Accelerator