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AgentCon Accra: Ctrl + Alt + Assist: AI Agents ...

AgentCon Accra: Ctrl + Alt + Assist: AI Agents Edition

In this keynote, we’ll explore the rise of AI agents:

- What exactly are Agents? Are they just smarter bots or a new paradigm in AI?
- What kinds of Agents exist today, from low-code Copilot Studio flows to full-fledged multi-agent systems powered by Azure AI Foundry and running on the edge?
- How you can build, deploy, and extend agents today using Microsoft’s ecosystem, from templates to custom orchestration with your own data to using mcp.

Along the way, we’ll highlight real-world use cases, edge-ready deployments, and the principles of building responsible, trustworthy AI systems that continue to work even offline.

You’ll walk away with a fresh perspective on AI agents: not just as the future of AI, but as teammates ready to transform how you work.

Avatar for Bethany Jepchumba

Bethany Jepchumba

October 09, 2025
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  1. • Cloud Advocate (DevRel) at Microsoft • Works with NGOs

    & Communities, currently ICT Director at TOFA • I am a hobbist, I enjoy trying out new hobbies Today’s session: https://bethany-jep.com/events/agentcon-accra-2025/ Bethany Jepchumba Microsoft confidential 2
  2. How language models work Natural language input Model Tokens Probability

    distribution Natural language output Decoding + Post-processing Get results Pre-processing
  3. What is an AI agent? LLM Instructions Tools Agent +

    + An AI agent is a micro-service that takes unstructured messages, optionally invokes other APIs and returns messages/action 1 2 3 Input System events User messages Agent messages 1 Tool calls Knowledge Actions Memory 2 Output Agent messages Tool results 3
  4. Foundry Local Design, customize and manage AI applications and agents

    on-device Preview Microsoft confidential 12 Installation Privacy and Security Latency Cost Efficient Low Bandwidth
  5. What is Model Context Protocol (MCP)? Ship once – reach

    every MCP-enabled client in your organization A secure, open standard that lets AI agents access tools, APIs, and data through a consistent interface — without custom integrations. In Azure AI Foundry Agent Service, MCP connects agents to your enterprise and external systems with a single, reusable protocol — secured, governed, and observable by Azure. Clients • Foundry Agents • Copilot Studio • GitHub Copilot • VS Code Servers/ Tools • Azure Services (Search, Cosmos DB, Power Platform, etc.) • Third-party APIs (Salesforce, ServiceNow, REST APIs) • On-prem data MCP Protocol • One standard interface • Security: Entra ID • Observability: Azure Monitor
  6. MCP Model Context Protocol - Easier to give context to

    models - Optimized communication between LLMs, external tools, data sources and applications - Uses a client-server model for interactions
  7. Model Context Protocol At Microsoft Model Context Protocol MCP enables

    seamless integration between LLM Apps and external data sources Azure API Management Build Local & Remote MCPs MCP SDK Microsoft Connectors Azure Functions Tools Etc. … Community Windows Registry VS Code BYO Enterprise or MCP Clients & Host Copilot Studio Foundry agents Visual Studio Windows VS Code GitHub Copilot Entra ID
  8. Enhancing Security for MCP Servers Use credential manager to authorize

    access to your backend MCP servers Protect your remote MCP servers with OAuth 2.0 and API Management Blog aka.ms/remote-mcp-apim-auth-blog Generally Available Azure API Management Safety Policies Azure OpenAI MCP enabled Tools Azure Monitor Logs & Metrics … Credential Manager Agents …
  9. Azure AI Foundry Security • Identity • Management Foundry Models

    Foundry Agent Service Azure AI Search Foundry Observability Azure AI Services Azure Machine Learning Azure AI Content Safety Copilot Studio Visual Studio GitHub Foundry SDK Serverless Control Azure Kubernetes Service Azure Container Apps Azure App Service Azure Functions Cloud Azure Azure Arc Foundry Local Edge
  10. Generative AI Development Lifecycle Hypo thesis Find LLMs Try prompts

    Manage Customize Design Managing PREPARE FOR APP DEPLOYMENT ADVANCE PROJECT BUSINESS NEED Deploy LLM App/UI Quo ta and cost management REVERT PROJECT C ontent Filtering M onitoring SEND FEEDBACK Prompt Engine ering or Fine-tuning Evalua tion Exceptio n Handling Retrieval Augmente d Generation Prote ct & govern
  11. • Violence • Sexual • Self-harm • Hate and Unfairness

    • Ungrounded Attributes • Code Vulnerability • Protected Materials • Content Safety Evaluators in Azure AI Foundry Safety & Security • Fluency • QA • Coherence • Intent Resolution • Task Adherence • Tool call accuracy General Purpose • Retrieval • Document Retrieval • Groundedness • Relevance • Response Completeness RAG Agents
  12. Evaluate agentic workflows User query “Weather tomorrow.” Intent resolution User

    wants to know the local weather and the time to forecast. Tool calls Call location and time API Call weather API Final response “The temperature will be 30 degrees. Rain will…” Intent resolution evaluation • User intent identification • Clarification for ambiguity Tool call accuracy evaluation • Correct tool call selection • Correct parameter extraction Final response evaluation • Task adherence • Response completeness Quality and Safety evaluation • RAG quality (Groundedness/Relevance/Retrieval) • Risk and Safety (Jailbreak/Code Vulnerabilities/Ungrounded Attributes
  13. AI Agent workflows can enhance efficiency, accuracy, and customer satisfaction

    Key Use Cases Across Industries • Assists employees in booking business trips • Integrates with Tripadvisor, Outlook, and SharePoint • Books via Teams chat or email • Uses OCR to gather receipts • Automates expense report submission and tracking Travel Booking & Expense Management • Personalized onboarding assistant for new hires • Uses LLMs grounded in HR data from SharePoint • Provide relevant training materials • Schedule orientations and set up software accounts • Monitor task completion and ensure efficient onboarding Employee Onboarding • Diagnoses issues by referencing history and product manuals • Provides tailored solutions or escalates through automated workflows • Creates tickets and schedules follow-ups • Updates CRM records, enhancing future support Personalized Customer Support • Analytics data from data lake and data warehouse • Responds to user requests in natural language • Generates insights, visualization, and sends via Teams or email • Automates data handling for real-time, effortless decision-making Data Analytics and Reporting
  14. Resources - Learning resources on GenAI, agents and MCP -

    Getting started with Azure AI - Links to the different tools – foundry local, ai toolkit on VSCode, GitHub Models and GitHub Copilot https://bethany- jep.com/events/agentcon-accra-2025/