AI Engineering in Practice: From Software Specification to Pull Request with Coding Agents

AI Coding Tools and Coding Agents are changing the way software teams analyze requirements, implement features, review code, and ensure quality. At the same time, they introduce new challenges: How does a rough requirement become a solid software specification? Which tasks are suitable for Coding Agents? Where does the human need to stay deliberately in the loop? And how can testing, review, security, privacy, and governance be integrated meaningfully into the development process?

In this practical workshop, participants will work through a realistic software development scenario. Together, we will build an AI-supported development workflow: from the initial requirement to spec-driven development, task structuring, and prompt-to-PR execution, all the way to review, testing, and quality gates.

The workshop goes beyond individual prompts or tools. It presents a repeatable operating model for software teams that want to use Coding Agents productively without losing control, quality, or accountability.

Participants will receive concrete templates, exercises, and workflow examples that they can transfer to their own projects and teams.

Workshop Agenda
Introduction: AI Engineering and agentic development workflows in software teams
From requirement to actionable software specification
Prompt-to-PR workflow: structuring tasks and using Coding Agents effectively
Human-in-the-loop: review, control, and accountability in the development process
Testing, code review, and quality gates for AI-generated code
Security, intellectual property, privacy, and governance in AI-supported development processes
Summary: roles, team enablement, and practical adoption in organizations
Learning Objectives

After this workshop, participants will be able to:

Turn business and technical requirements into AI-ready software specifications
Structure and scope tasks for Coding Agents effectively
Apply prompt-to-PR workflows in practice
Define human-in-the-loop control points in the development process
Systematically test and review AI-generated code
Design quality gates for AI-supported software development
Consider security, intellectual property, privacy, and governance aspects early in the process
Derive a practical AI Engineering Operating Model for their own team
Target Audience

This workshop is designed for software developers, tech leads, engineering managers, architects, DevOps and platform teams, and technical product owners who want to introduce or professionally use AI Coding Tools and Coding Agents in software teams.

Prerequisites

Basic knowledge of software development, Git, and pull request workflows is helpful. Prior experience with AI Coding Tools is beneficial but not required.

Format

Hands-on workshop with short input sessions, practical exercises, group work, templates, and concrete workflow examples.

Die AI-native Engineering-Organisation: Was sich für CTOs wirklich verändert

AI Coding Assistants und Coding Agents halten zunehmend Einzug in Softwareteams. Doch der Einsatz neuer Tools allein macht noch keine AI-native Engineering-Organisation.

Die eigentliche Veränderung beginnt dann, wenn AI Agents zu regulären Teilnehmern des Entwicklungsprozesses werden: Sie analysieren Anforderungen, unterstützen bei Spezifikationen, erzeugen Code, schreiben Tests, dokumentieren Änderungen und bereiten Pull Requests vor.

Damit verändert sich nicht nur die technische Toolchain. Auch Rollen, Verantwortlichkeiten, Backlogs, Review-Prozesse, Freigaben und Kompetenzprofile müssen neu gedacht werden.

Diese Keynote zeigt, wie kleine und wachsende Produktteams ein AI-gestütztes Engineering-Modell aufbauen können. Im Mittelpunkt stehen der Übergang vom Ticket-Backlog zum Spec-Backlog, AI Agents als ausführende, aber nicht entscheidende Instanz, neue Verantwortlichkeiten für CTOs, Product Owner und Entwickler sowie veränderte Review- und Governance-Prozesse.

Im Zentrum steht die Frage:

Wenn Agents immer mehr Code schreiben, was ist dann eigentlich noch die Aufgabe von Softwareentwicklern?

Die Antwort liegt nicht in weniger Engineering, sondern in einer Verschiebung der Kompetenzen: weg von reiner Codeproduktion, hin zu Systemdenken, Spezifikation, Architektur, Review, Risikobewertung und verantwortlicher Entscheidungsfindung.

Die Keynote vermittelt ein praxisnahes Operating Model für Human-Agent-Teams und zeigt, wie Engineering-Führung, Quality Gates, Team Enablement und Produktivitätsmessung in einer AI-native Organisation neu gestaltet werden müssen.

Die Kernbotschaft:

AI reduziert nicht die Bedeutung von Engineering Leadership. Sie macht gute Engineering-Führung noch wichtiger.

When AI Becomes a Team Member: Agentic Software Development with GitHub, Azure and Scrum

Most developers already use AI to generate code.
But what changes when AI moves beyond autocomplete and starts participating in the software development lifecycle?
While developing nVibes, AI agents are used alongside GitHub, Scrum and Azure to analyze tasks, inspect repositories, propose implementations, create changes and support software delivery.
This session explores a new development model in which AI is treated less like a coding assistant and more like a temporary member of the engineering team.
We will examine where agents fit into a Scrum-based workflow, what context they require, which tasks they perform well, and where human review remains essential.
During the live demo, we will give an AI agent a real development task from the nVibes backlog and follow the process from requirement to implementation.
The interesting question is no longer:
“Can AI write code?”
It is:
“How do we design a development process when both humans and AI agents can perform engineering work?”
What attendees will learn
- The difference between AI-assisted coding and agentic development.
- How AI agents can work with repositories, issues and development tasks.
- How agent work can fit into GitHub and Scrum workflows.
- Why context, acceptance criteria and architecture become even more important with AI.
- Where human review, governance and accountability remain essential.
Live Demo
Give the agent a genuine small nVibes Issue.
For example:
Add/modify a small feature or fix a controlled bug.

Then:
Issue → Agent analysis → repository → implementation → diff → tests → PR/review

From Zero to Production: Designing and Running a Modern Azure Platform

A prototype can run almost anywhere.
A production platform needs identity, APIs, data, security, observability, deployment automation, resilience and a clear architecture.
In this session, we will build the architectural picture of a modern Azure application using the real-world nVibes platform as our case study.
Starting from a simple application, we will progressively introduce the components required to operate a real cloud platform: frontend applications, backend APIs, authentication, data services, secure communication, deployment pipelines, monitoring and AI services.
Rather than beginning with a complex architecture diagram, we will build the architecture step by step and explain why each component exists.
The session concludes with a live walkthrough of the running nVibes platform and selected Azure resources behind it.
What attendees will learn
- How a modern Azure application architecture evolves from prototype to production.
- How frontend, APIs, identity and data services fit together.
- Where AI services belong in an application architecture.
- Why observability, security and automated deployment should be architecture concerns.
- How to avoid unnecessary complexity while still designing for growth.
Live Demo
This would work beautifully visually:
Architecture diagram → Azure Portal → GitHub deployment → nVibes production application

From Backlog to Azure: Building Software with Scrum, GitHub and AI Agents

Scrum tells us how to organize product development. GitHub gives us Issues, Projects, Pull Requests and automation. Azure gives us the platform on which our software runs.
But what happens when AI agents become part of the development workflow as well?
In this session, I demonstrate the development workflow used while building nVibes.
We will start with a product idea and turn it into a backlog item. From there we will follow its entire lifecycle:
Product Idea → User Story → GitHub Issue → Sprint → AI-assisted Development → Pull Request → Review → Azure Deployment → Working Feature
GitHub Projects acts as the operational Scrum board while GitHub repositories provide the engineering workflow. Azure provides the runtime environment, and AI development agents such as pi.dev help with implementation, analysis and repetitive development tasks.
The result is a workflow I call Azure Development++: Scrum provides the process, GitHub provides collaboration and traceability, Azure provides the platform, and AI agents accelerate execution.
The complete workflow will be demonstrated live using the real nVibes development environment.
What attendees will learn
- How Scrum can be mapped practically onto GitHub Projects.
- How Issues, Pull Requests and deployments provide end-to-end traceability.
- How AI development agents can participate in a modern development workflow.
- How GitHub and Azure create a continuous path from backlog to production.
- Where humans still need to make the important product and architectural decisions.
Live Demo
This one could be excellent:
Create User Story → GitHub Issue → assign/plan → AI agent works → inspect change → PR → merge → Azure deployment → feature visible in nVibes
That is much stronger than slides explaining Scrum.

Building Your Own Tech Company: From Idea to a Real Product on Azure

What does it actually take to turn an idea into a real technology company?
In this session, I share the journey of building nVibes, a European social platform developed on Microsoft Azure. Instead of focusing on startup theory, we will walk through the practical decisions that transform an idea into a working product: defining the product vision, choosing a cloud architecture, building the first application, organizing development, dealing with security and privacy, and preparing a platform for real users.
Using nVibes as a real-world case study, I will show how Azure, GitHub and modern AI-assisted development can help a small team build technology that would traditionally require a much larger organization.
The session also includes a live demonstration of the running platform and its Azure-based architecture.
This is not a story about having the perfect startup plan. It is about learning, iterating and building.
What attendees will learn
- How to turn a technology idea into a practical product roadmap.
- How cloud platforms such as Azure reduce the infrastructure barrier for startups.
- How GitHub, AI-assisted development and automation can enable very small teams.
- Which technical and organizational decisions matter early in a startup.
- Lessons learned from building a real European technology company.
Live Demo
Idea → GitHub → Azure → running nVibes platform
I would actually make this your most accessible talk. No deep Azure knowledge required.

Building a European AI Platform: Data, Agents, Privacy and Responsible AI on Azure

Adding AI to an application is easy.
Building an AI platform that has to operate with real users, personal data, identity, recommendations, privacy requirements and European regulatory expectations is much harder.
This session uses nVibes, a European social platform, as a real-world case study for designing an AI-enabled platform on Microsoft Azure.
We will explore how application data, user context and AI services can be combined to create personalized experiences while maintaining clear boundaries around identity, privacy, security and responsible AI.
The architecture covers the journey from application data through contextual AI processing and agent-based workflows to user-facing recommendations.
We will also discuss an important architectural question:
How much context should an AI system actually know about a user?
Rather than presenting a theoretical reference architecture, I will show architectural decisions, trade-offs and lessons learned while building the platform.
A live demonstration will show the architecture working through the nVibes application and its AI-powered recommendation experience.
What attendees will learn
- How to structure an AI-enabled application architecture on Azure.
- How application data can become contextual input for AI systems.
- How agents and recommendation systems can interact with application services.
- How identity, security and privacy boundaries affect AI architecture.
- How Responsible AI principles influence actual engineering decisions.
- Which architectural trade-offs appear when AI reaches production.
Live Demo
User interaction → application context → AI → recommendation → resulting action inside nVibes
And then show the corresponding Azure architecture.

Beyond Vibe Coding: How Agentic AI Becomes a Real Member of Your Scrum Team

AI coding tools can produce an astonishing amount of code in very little time. But speed alone does not make software development better.

As AI agents become more autonomous, many experienced developers are facing a new problem: they feel they are losing control over their own codebase. Tasks happen across multiple files, agents make architectural decisions, documentation becomes outdated, and "vibe coding" can quickly turn into an unstructured development process.

There is another way.

In this session, I will show how we integrate an AI development agent into a real Scrum-based development workflow using GitHub, VS Code and Pi.dev.

The key idea is simple: the AI agent is not replacing the developer. It becomes another development team member working inside clearly defined engineering boundaries.

We will look at how backlog items, project goals, architecture documentation, GitHub issues, branches, pull requests, coding standards and Definition of Done can become the operating framework for an autonomous AI agent.

Instead of prompting an AI with "build this feature", we give it the same structured context and responsibilities we would expect from a professional developer.

The session includes a live demonstration of an agent working on a real software project:

nVibes — a social media platform made in Germany for Europe.

You will see how a development task moves from a Scrum backlog through GitHub into an autonomous AI development workflow, while the experienced developer remains responsible for architecture, review, governance and final approval.

We will also discuss where agentic development currently fails, what should never be delegated blindly, and why experienced software engineers may become even more important in AI-driven development.

What you will learn

How to integrate AI coding agents into an existing Scrum workflow instead of creating a parallel "AI workflow"

How GitHub issues, project boards, branches and pull requests can provide governance for autonomous development

How project documentation and architecture decisions can become persistent context for AI agents

How to define boundaries between human engineering responsibility and autonomous agent execution

How to avoid the loss of control often associated with vibe coding

How an AI agent can practically operate as a development team member

Why code review, architecture and engineering experience remain critical in an agentic development environment

Live Demo

During the session I will demonstrate a real development task using:

Scrum
GitHub
GitHub Projects
VS Code
Pi.dev
AI coding agents
Pull Requests
Architecture and project documentation

The demonstration will use nVibes, a real European social-media platform developed in Germany, as the example codebase.

The goal is not to show how much code an AI can generate.

The goal is to show how professional developers can let AI agents work autonomously without giving up control of the software engineering process.

Transformation ist kein Projekt: Was der Aufbau von nVibes über kontinuierlichen Wandel lehrt

Eine Social Platform von Grund auf neu zu entwickeln bedeutet nicht, einen fertigen Plan abzuarbeiten. Technologie verändert sich, Anforderungen verändern sich, Menschen reagieren anders als erwartet – und manchmal stellt sich eine vermeintlich gute Idee schlicht als falsch heraus.

Am Beispiel von nVibes, einer europäischen Social Platform für reale menschliche Verbindungen, zeige ich, wie aus Produktentwicklung ein kontinuierlicher Transformationsprozess wird.

Dabei geht es nicht um eine Hochglanz-Startup-Story. Ich zeige Entscheidungen, die wir revidieren mussten, den Einfluss von KI auf Produkt und Organisation und die Frage, wie man trotz permanenter Veränderung eine klare Vision behält.

Welche Teile einer Vision müssen stabil bleiben? Wo muss eine Organisation bereit sein, bisherige Annahmen aufzugeben? Und wie erkennt man den Unterschied zwischen notwendiger Beharrlichkeit und dem Festhalten an einer falschen Entscheidung?

Die Session verbindet konkrete Erfahrungen aus dem Aufbau einer neuen Social Platform mit übertragbaren Prinzipien für Transformation, Innovation und Produktentwicklung.

What We Got Wrong Building AI into nVibes — Lessons from a Real European Social Platform

AI architecture diagrams always look clean. Real products rarely are.

In this session, I will share the architecture decisions, experiments and mistakes behind integrating AI capabilities into nVibes, a European social platform designed around real-world human connection.

Instead of presenting a perfect reference architecture, we will look at the uncomfortable questions that appear once AI meets a real product: Which features actually benefit from AI? Where does an agent create unnecessary complexity? How do you keep AI services observable and affordable? How do privacy, identity and trust requirements change the architecture? And when should you simply not use AI at all?

I will walk through decisions that worked, approaches that had to be reconsidered, and the engineering principles that emerged from those lessons.

This is a practitioner session about building under real constraints — architecture, cost, regulation, security and product value — rather than another polished AI demo.

From Social Platform to Agentic Platform: Building nVibes with Azure, AI Agents and Trust by Design

Social platforms are traditionally built around feeds, profiles, messaging and recommendations. But what happens when AI agents become active participants in the platform architecture?

In this session, I will use nVibes, a European social platform focused on real-world human connection, as a practical architecture case study. We will explore how agentic capabilities can be introduced without turning the platform into an uncontrolled collection of AI features.

We will look at architecture patterns for Azure-based AI services, agent orchestration, identity boundaries, APIs, observability and responsible AI controls. I will also discuss where agents make sense, where deterministic services are still the better choice, and why trust boundaries become more important when autonomous systems interact with user data.

This is not a polished product demo. It is an architecture walkthrough of the decisions, trade-offs and constraints involved in evolving a real social platform toward an agentic architecture.

Attendees will leave with practical patterns for designing agentic systems that remain observable, governable and trustworthy.

From Cloud Architect to AI Architect: How Agentic Engineering Is Changing Our Jobs

For years, cloud architects learned how to design applications, infrastructure, identity, security and governance. Agentic AI changes the architecture — but it also changes the architect.

When AI systems can plan, call tools, generate code and operate across business processes, the role of developers, architects and consultants starts to shift. Technical knowledge remains essential, but skills such as system thinking, governance, verification, communication and human oversight become increasingly important.

Drawing from three decades in software architecture and my current work building nVibes, I will discuss how the transition from cloud engineering to agentic engineering changes everyday technical roles.

We will look at which skills remain valuable, which new ones are emerging, how coding agents change development workflows, and why architects may become even more important rather than less.

This session is aimed at developers, architects, consultants and IT professionals asking a simple question: where do I fit in an agentic future?

EU AI Act Meets Social Platforms: Governing Responsible AI in nVibes

The EU AI Act is often discussed as a legal framework. For architects and technology leaders, however, the harder question is much more practical: how do you translate regulation into architecture, governance and engineering decisions?

This session uses nVibes, a privacy-first European social platform, as a real-world case study for Responsible AI governance.

We will map AI use cases such as recommendations, content assistance, trust mechanisms and intelligent community features to governance requirements and risk categories. From there, we will examine practical controls around human oversight, data protection, transparency, model usage, documentation and operational accountability.

The focus is not on reading legislation slide by slide. Instead, I will show how teams can turn regulatory requirements into architecture decisions, engineering guardrails and repeatable governance processes.

Attendees will leave with a practical framework for connecting the EU AI Act, privacy-by-design and Responsible AI with real product development on the Microsoft Cloud.

Responsible AI for Business Central ISVs: Privacy, Trust, and Governance by Design

AI features are becoming a competitive requirement for Business Central ISVs, but adding AI to business applications also introduces new responsibilities. Customers will increasingly ask how their data is used, where decisions come from, who remains in control, and how AI behavior can be explained or audited.

This session provides a practical responsible AI framework for ISVs and partners building AI-enhanced Business Central extensions, integrations, or companion applications. We will cover core design principles such as data minimization, user consent, human oversight, logging, role-based access, explainability, and safe fallback behavior.

The focus is not legal theory, but implementation-oriented governance. Attendees will learn which questions to ask before building AI features, how to document design decisions, how to identify risk areas early, and how to communicate AI capabilities transparently to customers. The session helps partners build AI solutions that are not only innovative, but also trustworthy and enterprise-ready.

From Business Central to Agentic AI: Designing Secure AI Assistants for SMB Processes

Business Central partners are increasingly asked how AI can support sales, finance, service, operations, and customer communication without creating security, privacy, or governance risks. This session shows how to design practical AI assistants around Business Central processes using Azure, Microsoft 365, and responsible architecture principles.

We will walk through a reference architecture for agentic AI in an SMB context: how to connect business data safely, how to separate user intent from system actions, how to design approval workflows, how to avoid uncontrolled automation, and how to prepare customers for AI-assisted processes without losing trust or compliance.

The session is aimed at partners who want to move beyond “AI demos” and start designing real, customer-ready AI scenarios. Attendees will leave with architectural patterns, decision points, anti-patterns, and a pragmatic checklist for building secure, explainable, and useful AI assistants around Business Central ecosystems.

Building an AI-Ready Azure Architecture for Business Central Partner Solutions

AI-enabled partner solutions require more than a prompt and an API call. They need secure identity, reliable integration, data boundaries, observability, cost control, and a clear operating model. This technical deep dive shows how to design an AI-ready Azure architecture for Business Central partner solutions.

We will explore a practical architecture blueprint covering identity and access, API boundaries, data ingestion, event-driven integration, retrieval-augmented generation patterns, audit logging, monitoring, deployment, and operational safeguards. The session also discusses common failure modes: exposing too much data, mixing customer tenants, missing approval flows, weak prompt boundaries, and unmonitored AI costs.

Attendees should already understand cloud architecture basics and want a deeper view of how AI capabilities can be integrated responsibly into Business Central-adjacent solutions. The goal is to give developers and architects a reusable mental model for building secure, scalable, and maintainable AI-enabled solutions in the Microsoft ecosystem.

AI Readiness for Business Central Partners: From Hype to Customer-Ready Offerings

Many SMB customers are interested in AI, but they often struggle to identify where AI creates measurable business value and where it creates unnecessary complexity or risk. This session helps Business Central partners turn AI conversations into structured, customer-ready offerings.

We will explore how partners can assess AI readiness, identify high-value use cases, define responsible adoption paths, and position AI services without overpromising. The session connects business strategy with practical architecture: data quality, process ownership, privacy, user adoption, governance, and change management.

Attendees will learn how to build an AI opportunity framework for Business Central customers, how to qualify use cases, how to separate automation from augmentation, and how to create offerings that are realistic, trustworthy, and repeatable. The goal is to help partners move from AI hype to sustainable services that customers can understand, buy, and adopt.

The Next Web Will Be Trustworthy: Building Human-Centered AI Platforms in the Age of Agents

AI is changing the web again. We are moving from static websites and social feeds to AI-augmented digital ecosystems where agents understand context, support decisions, interact with services, and shape user experiences in real time.

But the defining question of this next web is not only what AI can do. It is who we trust, which data we share, who stays in control, and how digital platforms must be designed when intelligent systems become part of everyday interaction.

In this keynote-style session, Christian Alexander Schreiber uses nVibes as a real-world scenario to explore how human-centered AI platforms can be built with trust, privacy, sovereignty, and security at their core. Instead of presenting Azure as the main story, the talk shows how cloud architecture, identity, responsible AI, data boundaries, and platform design come together to enable trustworthy digital ecosystems.

Attendees will leave with a strategic mental model for the age of agents: AI should augment people, not replace their agency; platforms should earn trust, not demand it; and architecture must protect human control, privacy, and digital sovereignty from the beginning.

Azure Architecture for Responsible AI: Building nVibes as a Sovereign Social Platform

nVibes is a real-world case study for building a modern, AI-enabled social platform on Azure with sovereignty, privacy, and security at its core.

In this session, Christian Alexander Schreiber, CEO & Founder and Lead Architect of nVibes, walks through the architectural decisions behind a production-adjacent Azure platform: Cloudflare Edge in front of Azure, Azure Standard Load Balancer, Frontend VM Scale Set, dedicated API and database tiers, a private AI VM, Azure Private DNS, Network Security Groups, Managed Identity, and a self-hosted LLM approach.

The talk focuses on one central question: how can we integrate responsible AI into a digital platform without giving models direct access to databases, secrets, internal services, or uncontrolled user data?

Attendees will learn how nVibes separates frontend, API, database, and AI runtime responsibilities; how private networking and controlled backend authorization reduce risk; and how MVP infrastructure can evolve toward hardened, reproducible, least-privilege cloud architecture.

This is not a theoretical cloud diagram session. It is a practical architecture story about building, securing, and scaling a real platform where Azure, AI, privacy, and European digital sovereignty must work together.

Beyond Likes and Logins: Building Real-World Trust into a Next-Generation Social Platform

This session takes the audience behind the scenes of nVibes, a next-generation social platform designed around real-world trust, privacy and responsible digital interaction.

Instead of treating every follow, like or connection as equal, nVibes explores how verified real-world encounters can become a stronger foundation for digital relationships. Using the MeetNow architecture as a concrete example, we will look at how QR-based interaction, short-lived sessions, geo-consent, server-side distance validation, device context and privacy-by-design can work together to create a “Real Friend” trust signal without turning the system into a tracking machine.

The talk also discusses the next architectural step: ephemeral trust exchange patterns, why secrets should not live inside QR payloads, how public material can be fetched safely through APIs and why standard cryptographic primitives and external review matter when designing security-sensitive social features.

Attendees will leave with practical architecture patterns for building trust-centric features, handling privacy and security trade-offs, and designing modern social platforms that are more human-centered, sovereign and resilient.

Converse with your dataverse data: Retrieving Data with Natural Language and Power Platform CoPilot

Join me for a 100% hands-on session that will enable you to harness the potential of Natural Language and Power Platform CoPilot to build powerful applications and streamline your business processes. I will walk you through creating an application, developing a flow with Power Automate and CoPilot, and seamlessly retrieving data in Dataverse using only Natural Language and CoPilot.

Key Highlights:

I'll begin by introducing you to the Power Platform CoPilot, demonstrating its capabilities and potential to simplify your interactions with data in the Dataverse.
Learn how to quickly build an application using CoPilot, making it easier than ever to develop user-friendly interfaces that increase your productivity.
Discover the power of automation as we walk you through the process of creating a flow using Power Automate and CoPilot. See how you can automate tasks and integrate different processes effortlessly.
Experience the magic of retrieving data in Dataverse using natural language commands and CoPilot. I'll share real-world scenarios and demonstrate how CoPilot can save you time and effort.

I'll leave time for your questions, so you'll leave with a clear understanding of how to use these tools effectively.

Expert Circle: Expertenrunde zum Thema MS CoPilot

Efficient Software Delivery: Power Platform loves Azure DevOps

If you are involved in building Power Apps and automation flows, you need to deliver software faster, more reliably, and with higher quality by integrating development, testing, and operations into a seamless process. You also need to ensure that the software development lifecycle is fully managed, from planning to deployment and maintenance.

In my session, I will set up an entire Azure DevOps project and cover how to export your Power Platform Apps, Flows, and Connectors from a development environment to test and production environments using pipelines, triggers, CI/CD, Microsoft Teams approvals, and release management.

You will have the opportunity to work on real-world scenarios and apply the concepts to your own projects. By the end of the session, you will have a solid understanding of how to implement agile development using the Power Platform and Azure DevOps, and you will be able to start applying these practices in your organization.

Building a Power Virtual Agent with CoPilot: Empowering Automation

Join us in this session as we embark on a journey to create a powerful Power Platform Virtual Agent using the groundbreaking capabilities of CoPilot. Discover how to leverage CoPilot's AI assistance to build an intelligent and interactive virtual agent that operates within Microsoft Teams.

We will dive into the seamless integration between the PVA and Power Automate. Explore how you can trigger Power Automate flows directly from the virtual agent, enabling streamlined automation and effortless data retrieval.

Through hands-on demonstrations, I will guide you in constructing a PVA that interacts with users, understands their inquiries, and effectively executes flows to fetch data.

By leveraging Co-Pilot's intelligent suggestions and coding assistance, you will gain valuable insights into how to optimize the development process and accelerate the deployment of your Power Platform Virtual Agent. Learn how to harness the power of AI to enhance automation, improve customer experiences, and drive productivity within your organization.

Efficient Software Delivery: Power Platform, Azure DevOps, and Business Central Integration

If you are involved in building Power Apps and automation flows for Business Central, you need to deliver software faster, more reliably, and with higher quality by integrating development, testing, and operations into a seamless process. You also need to ensure that the software development lifecycle is fully managed, from planning to deployment and maintenance.

In my session, I will set up an entire Azure DevOps project and cover how to export your Business Central Power Platform Apps, Flows, and Connectors from a development environment to test and production environments using pipelines, triggers, CI/CD, Microsoft Teams approvals, and release management.

You will have the opportunity to work on real-world scenarios and apply the concepts to your own projects. By the end of the session, you will have a solid understanding of how to implement agile development for Dynamics 365 BC using the Power Platform and Azure DevOps, and you will be able to start applying these practices in your organization.

CoPilot in Power Platform: Revolutionizing Application & Flow Development for Business Central

In this session, we will explore the exciting potential of CoPilot in the context of building Power Apps and flows for Business Central. Co-Pilot, an AI-powered coding assistant, has revolutionized the development process by providing intelligent suggestions, generating code snippets, and offering valuable insights.

Join us as we delve into how CoPilot can streamline your development. I will demonstrate how AI can assist you in writing code more efficiently, reducing errors, and accelerating the overall development cycle. Discover how CoPilot's contextual understanding and code generation capabilities can enhance your productivity and help you build robust solutions.

Gain insights into the evolving role of AI and how it can contribute to creating smarter, more intelligent Power Apps and flows.

Building a Solid Foundation: Governance and Compliance in Power Platform & Business Central

In this session, we will dive into the crucial aspects of Data Loss Prevention, Governance, and Power Platform Environment Management for Apps built for Dynamics 365 Business Central.
As organizations increasingly rely on the Power Platform to build and deploy apps, it becomes essential to implement effective measures to prevent data loss, ensure proper governance, and manage Power Platform environments efficiently.
During this session, we will explore best practices and practical strategies to safeguard your data and maintain control over your Power Platform ecosystem.

I will discuss the importance of establishing data loss prevention policies, implementing governance frameworks, and leveraging the power of Power Platform Environment Management to streamline app development and deployment processes.

You will gain insights into how to protect sensitive information, establish role-based access controls, and enforce data compliance regulations within your Power Apps for Dynamics 365 Business Central. Additionally, we will explore various techniques and tools for managing Power Platform environments, enabling you to create, configure, and administer environments effectively.

Building a Power Virtual Agent with CoPilot: Empowering Automation with BC integration

Join us in this session as we embark on a journey to create a powerful Power Platform Virtual Agent using the groundbreaking capabilities of CoPilot. Discover how to leverage CoPilot's AI assistance to build an intelligent and interactive virtual agent that operates within Microsoft Teams.

We will dive into the seamless integration between the PVA and Power Automate. Explore how you can trigger Power Automate flows directly from the virtual agent, enabling streamlined automation and effortless data retrieval from Business Central.

Through hands-on demonstrations, I will guide you in constructing a PVA that interacts with users, understands their inquiries, and effectively executes flows to fetch data from Business Central.

By leveraging Co-Pilot's intelligent suggestions and coding assistance, you will gain valuable insights into how to optimize the development process and accelerate the deployment of your Power Platform Virtual Agent. Learn how to harness the power of AI to enhance automation, improve customer experiences, and drive productivity within your organization.

Enhancing Data Security and Compliance with Double Key Encryption

In this session, we will be discussing Double Key Encryption (DKE) as part of Azure Purview, a security technology developed by Microsoft that uses two keys to access protected content. One key is stored in Microsoft Azure, while the other is held by the user, giving them complete control over their data. We will cover the benefits and limitations of using DKE, including its relevance for highly regulated industries such as finance and healthcare, and the specific scenarios in which it is recommended to use this solution. Additionally, we will go through the necessary steps to deploy DKE, including installing software prerequisites, creating sensitivity labels, and enabling DKE in your client. This session will be useful for anyone looking to enhance their data security and compliance measures, especially those who handle highly sensitive information.

Unleashing the Power of Hybrid with Azure Arc-enabled servers

With Azure Arc-enabled servers, you can manage Windows and Linux physical servers and virtual machines hosted outside of Azure, on your corporate network, or on another cloud provider. For the purposes of Azure Arc, these non-Azure hosted machines are considered hybrid machines. The management of hybrid machines in Azure Arc is designed to be consistent with how you manage native Azure virtual machines, using standard Azure constructs such as Azure policies and applying tags. When a hybrid machine is connected to Azure, it becomes a connected machine and is treated as a resource in Azure.
In my 30 min. session, I will show you how to connect hybrid (Windows and Linux) machines to Azure using the Azure Connected Machine agent on each machine, and review and customise the pre-built installation script for at-scale deployment of the Connected Machine agent to support your automated deployment needs.

Optimieren Sie die Effizienz Ihres Projektmanagements mit Microsoft Planner, Teams & Power Automate!

Von der Post-it-Wand zum digitalen Kanban-Board: Entdecken Sie in dieser 50-minütigen LifeHack-Session die Möglichkeiten der Automatisierung in Microsoft Planner & Teams und wie Sie durch den Einsatz von Power Automate zu einem erfolgreicheren Projektmanager werden. Agilität 2.0! Profitieren Sie von praxisorientierten Anleitungen zur Implementierung von Workflows und Optimierung Ihrer Arbeitsabläufe

Zero To Hero with Azure DevOps & Power Platform

Power Platform solutions can be easily exported from one environment and imported to other with manual efforts. Azure DevOps pipelines make it easy to automate to move your solutions from one environment to other. In my 45 min. Session I will set up Azure DevOps pipelines for this scenario and cover how to export and import the Power Platform solution from development environment to the Q&A environment and then export to the production environment using the key principles of: application lifecycle management, CI/CD, software tests & releasemanagement.