I’m #humbledandhonored to share that I have been appointed to the .NET Foundation Board of Directors – Thank You for your service, Kendall Miller!
The .NET ecosystem has played a significant role throughout my career – as a developer (of it and with it), architect, open source contributor, community organizer, speaker, mentor, and Microsoft MVP. Being entrusted with helping guide the future of this community is both humbling and exciting.
Thank you to everyone who voted, supported my candidacy, encouraged me to run, and contributed to the conversations along the way. Most importantly, thank you to the countless maintainers, contributors, volunteers, sponsors, and community members who make the .NET ecosystem thrive every day.
I look forward to working alongside my fellow board members and the broader community to help the Foundation continue to grow, support its projects, and create opportunities for the next generation of developers.
Here’s to the future of .NET and open source. Looking forward to be working with the new members, Meagon Hansen and Hayden Barnes, and congrats Mitchel Sellers on his re-election to the board! Louëlla Creemers, Chris Woody Woodruff – thank you for your service! Chris Sfanos, Kevin Griffin, Jonathan “J.” Tower, Irina Dominte Scurtu, thank you for the trust in me, looking forward for collab!
One of the most interesting things about looking at this collection of sessions together is that they are not isolated conversations.
They form a trajectory – let me show how. Each session approaches a different part of the modern enterprise technology landscape: AI adoption, agentic development, data quality, governance, observability, user experience, and the evolution of integration itself. But taken together, they describe a broader shift in how we design, build, and operate technology – starting from the keynote and going through each aspect.
The common theme is not simply that AI is changing software.
It is that the enterprise technology stack is becoming more intelligent, more automated, and more connected, and that this makes judgment, governance, trust, and architectural discipline more important than ever.
So, let’s go session by session here! But first, came breakfast!
1. Faster Is Not Always Better: Stop Optimizing the Obvious
The opening keynote by Peter Ward challenged one of the most common assumptions in technology: that faster, more automated, and more AI-driven always means better outcomes.
Peter Ward opening Keynote “The hidden value of asking better questions with AI projects”
While modern cloud platforms and AI capabilities have made it possible to optimize nearly every process, the session argued that judgment—not technology—remains the true differentiator.
Using examples from Copilot deployments, automation initiatives, and digital transformation programs, the presentation demonstrated how organizations often optimize the wrong metrics, achieving technical success while missing the commercial value they were trying to create.
The message was simple: the wrong metric scales just as efficiently as the right one.
The audience was encouraged to shift from measuring activity to measuring outcomes, and to use the Microsoft ecosystem not simply to do things faster, but to make better decisions.
Optimizing the obvious is easy. Optimizing for real business impact is what creates lasting value.
His keynote made serious ripples across the other presenters too – I think there weren’t a single presenter who hasn’t reverted back to Peter’s slides and message.
2. AI-Native Development and Spec Driven Development: Moving Beyond Vibe Coding
That same principle applies directly to software development – as we learned from Dr Dave Goad GAICD in the second session. He explored how the rapid adoption of Agentic AI IDEs has made vibe coding increasingly common, while highlighting why many enterprises have struggled to realize the expected return on their AI investments.
Generating more code faster is not enough.
Dr Dave Goad presenting about the move from vibe coding to spec driven development
Without structure, context, and governance, AI-assisted development can create inconsistent implementations, security concerns, and technical debt at a speed that traditional development processes were never designed to manage.
The presentation introduced Spec Driven Development as the next evolution of AI-native software engineering.
It demonstrated how well-defined specifications can provide the structure and context AI agents need to produce reliable, maintainable, and secure code. Rather than replacing engineering discipline, AI makes that discipline even more valuable.
Attendees learned how organizations can move beyond ad hoc vibe coding toward a scalable enterprise model: one where agents accelerate delivery, but specifications, standards, and human judgment continue to guide the outcome.
We had a greatly appreciated coffee break here with breakfast burritos and more.
3. Toolkit for Building Agents: Microsoft 365 Copilot, Copilot Studio, and SharePoint in Action
The next session, presented by Manpreet Singh, moved from the development lifecycle into the workplace, showing how organizations can begin building practical agents today.
Manpreet Singh speaking about “Toolkit for building Agents: M365 Copilot, Studio & SharePoint in Action”
This hands-on workshop demonstrated how Microsoft 365 Copilot, Copilot Studio, and SharePoint can be used together to create intelligent, low-code agents capable of answering questions, generating content, and automating everyday business processes.
Participants learned how to design, build, and deploy custom agents tailored to their organizations’ needs, while using SharePoint as a secure, context-rich knowledge source.
Through practical exercises and guided demonstrations, the session explored when and where each tool fits, how low-code conversational agents can be created in Copilot Studio, how Microsoft 365 Copilot can be extended with custom capabilities, and how AI experiences can be integrated into SharePoint. The workshop also covered licensing considerations, implementation patterns, tips, and best practices.
The key takeaway was that agents are most valuable when they are not treated as isolated experiments. You see how this fits into the general message? They become useful when they are connected to organizational knowledge, embedded into existing workflows, and governed in a way that keeps humans in control.
4. Embedding Governance into the SDLC: Enforcing Backlog Integrity Through Pull Request Checks
Did you know your backlog is lying? Do you even still maintain one? Our beliefs been shattered in the session from Vladimir Gusarov (and saw the open source 3D printable octocat lamp live!). Why? As AI increases the speed of delivery, it also increases the importance of quality at the source.
Vladimir Gusarov presenting about “Your Backlog Is Lying: Enforce It with PR Checks”
His presentation demonstrated why maintaining a consistent and well-structured backlog is essential for producing reliable metrics, accurate planning, and effective software delivery.
If your backlog is not consistent, your metrics and plans are not either. The presentation showed how organizations can embed governance directly into the development workflow by using Pull Request validation in Azure Repos and GitHub. Attendees learned how to validate linked work items, enforce required fields and naming conventions, and automatically block pull requests that fail to meet organizational standards.
Rather than introducing manual reviews or additional bureaucracy, the approach placed guardrails directly inside the tools developers already use. The session also showcased repeatable implementation patterns, including PR checks, validation rules, and integrations between Azure Boards, Azure Repos, and GitHub.
The broader lesson was important: governance works best when it is not added after the fact. It should be built into the workflow.
5. From UDDI to MCP: History Is Repeating, but This Time It Might Work
The sixth session – by me – stepped back and looked at the historical arc behind many of these developments.
I am speaking about “From UDDI to MCP – What We Learned About Finding APIs in 30 Years?”
I explored how today’s AI agent ecosystem has brought the industry full circle, tracing the evolution from UDDI and Microsoft Hailstorm to Model Context Protocol, agent skills, and modern AI collaboration.
Rather than presenting MCP as an entirely new idea, I demonstrated how many of today’s concepts are the natural evolution of ambitions first imagined more than two decades ago.
The industry has long wanted systems that could discover capabilities, understand contracts, connect services, and act on behalf of users.
What has changed is the environment. Cloud platforms are mature. Identity systems are stronger. Semantic search is practical. Large language models can interpret intent. Agents can reason across tools. Protocols such as MCP can help expose capabilities in a consistent way.
My session contrasted contracts with intent, integration with collaboration, and static registries with intelligent, discoverable capabilities. It also explored the questions that remain: governance, trust, security, interoperability, and standardization. The technology has changed dramatically. The original vision has not. This time, the ecosystem may finally be ready to realize it. Recognizing this was helped by another coffee break.
Yummie!
6. Building an Enterprise ChatGPT-Style Application with Azure OpenAI and RAG
The next session, from David Patrick, focused on one of the most common enterprise AI use cases: grounding conversational AI in private organizational knowledge.
David Patrick speaking about “From Zero to ChatGPT: Building Your Own AI Assistant with Azure AI”
The presentation demonstrated how to build and deploy an enterprise-grade, ChatGPT-style application using Python, Azure OpenAI Service, and Azure AI Search with Retrieval Augmented Generation.
Using practical examples based on employee handbooks, benefits guides, and role descriptions, the session showed how to ingest, chunk, embed, index, and retrieve information from internal PDF documents.
Participants learned how to wire these capabilities into a conversational interface capable of answering questions using private organizational data rather than relying solely on public internet knowledge.
The session walked through the full architecture, explained the role of each Azure service, and shared reusable Python implementation patterns for building secure and scalable chat experiences.
This connected naturally with the earlier discussion about agents (you see the trend?).
An enterprise chatbot is not simply a better search box. It is an example of a broader architectural pattern: AI becomes valuable when it is grounded in trusted data, connected to organizational context, and deployed with security and governance in mind.
7. From Data Democratization to Data Enablement
That same story applies to data (long live the data scientists!).
Preeti Gupta speaking about “Data Enablement in Regulated Finance: Moving Beyond Access to Outcomes”
Over the past few years, many organizations have invested heavily in making data more accessible. But wider access has not always translated into better decisions, faster delivery, or measurable outcomes.
The problem is not access. It is what comes after. The seventh session, from Preeti Gupta , challenged the assumption that data democratization alone creates value.
Drawing on experience from regulated enterprise environments, the presentation showed why organizations often struggle to turn available data into actionable insight. Without clear ownership, consistent quality, and embedded governance, access can scale confusion instead of value.
The session introduced data enablement as the next stage in the evolution of enterprise data strategy. Attendees explored how organizations can move from datasets to data products, assign clear ownership and accountability, adopt platform thinking, and provide reusable self-service capabilities. The presentation also emphasized the importance of embedding governance and compliance directly into workflows, using guardrails rather than relying entirely on manual controls.
Open-source principles were positioned as an important foundation for building interoperable, scalable, and sustainable data platforms. This connected directly to the earlier RAG and agent sessions. AI systems are only as useful as the information they can trust. Data enablement is not a separate concern from AI adoption. It is one of its most important prerequisites.
8. Observability Deep Dive: Correlating Logs Across Azure Monitor, Application Insights, and Distributed Services
As applications become more distributed and intelligent, operational visibility becomes equally important.
The eighth session, from Monika Mundra , (PMP) , took a deep dive into observability in Azure, demonstrating how to correlate logs, traces, dependencies, and telemetry across Azure Monitor, Application Insights, and distributed services.
Monika Mundra presenting about “Observability Deep Dive: Correlating logs across azure monitor, app insights and distributed service”
Through practical examples, attendees learned how telemetry flows across modern cloud-native applications and why correlation is essential for understanding complex request paths.
The presentation showed how to write Kusto Query Language queries to trace requests end-to-end, identify bottlenecks, and diagnose failures across multiple services. Participants also explored correlation strategies they could implement in their own applications to improve visibility, reduce mean time to resolution, and simplify debugging in distributed environments.
This session reinforced a recurring theme across all of them:
Complexity should not be managed through additional manual effort. It should be managed through better platforms, stronger instrumentation, embedded standards, and reusable patterns. Observability is not an operational afterthought. It is part of the architecture.
And this session also came with the lunch!
9. Agent-Driven UI Development with MCP Servers, Skills, and Ignite UI
The sponsorship session brought the discussion back to the developer experience and showed what agent-driven workflows can look like in practice – thank you for Jason Beres for the engaging examples and real-time demos, you were brave on that Wi-Fi!
Jason Beres speaking about “Building Enterprise Apps with AI, MCP and Components”
Modern UI development is moving beyond AI-assisted code completion toward agents that understand frameworks, component libraries, and design systems. The presentation explored how MCP servers and Skills can accelerate the development of .NET applications and modern web interfaces across Blazor, Angular, and React.
Skills were presented as the “brain” of the workflow. They provide framework-aware guidance for correct component usage, imports, patterns, project conventions, naming rules, and theming standards. MCP servers were presented as the “hands.” They allow agents to scaffold UI, query component APIs, generate design-token-aware themes, and apply complex styling without inventing brittle CSS.
Using Ignite UI as a practical example, the session demonstrated how Skills and MCP servers can work together to generate grounded, on-brand, runnable code across Angular, React, Blazor, and Web Components. Attendees also learned how to adapt Skills for their own teams, encode preferred patterns, and handle advanced theming scenarios such as palette generation, adaptive contrast, typography, spacing, border radius, component-level styling, and design-system switching across Material, Fluent, Bootstrap, and Indigo.
The session closed with a practical model for AI-ready UI development:
Use Skills to reduce hallucinations. Use MCP servers to execute real development tasks. Use trusted component libraries and design systems to keep applications consistent, maintainable, accessible, and visually aligned.
10. Where do Copilot Studio Finishes and Where does AI Foundry Starts?
Last session of the day was from Abhijeet Jadhav (PMP®) – he explored how organizations can recognize when an AI solution has outgrown the capabilities of Microsoft Copilot Studio and when it is time to consider a move toward Azure AI Foundry.
Abhijeet Jadhav presenting about “Copilot Studio to Azure AI Foundry: A Framework for Knowing When – and How – to Scale”
Rather than presenting the platforms as competing choices, the discussion framed them as different stages in the maturity of an enterprise AI implementation, each suited to a particular level of complexity, scale, and customization.
The presentation introduced a practical framework for identifying the tipping point between low-code agent development and more advanced AI engineering. Attendees learned how to evaluate factors such as integration complexity, extensibility requirements, governance, performance, data orchestration, and the need for more sophisticated model management. The session also provided guidance on how to plan the transition across platforms without losing the speed and accessibility that made the initial solution successful. By the end of the presentation, participants had gained a clearer understanding of how to scale AI implementations deliberately, using Copilot Studio where it adds the most value and moving to Azure AI Foundry when enterprise requirements demand greater control, flexibility, and architectural depth.
One Trajectory: From Automation to Intelligent Enterprise Platforms
Taken together, these sessions describe a single evolution. We are moving from automation to intelligent systems. From AI-assisted development to agent-driven workflows. From ad hoc vibe coding to Spec Driven Development. From isolated copilots to grounded enterprise agents. From static integrations to discoverable capabilities exposed through MCP. From data access to trusted data products. From manual governance to embedded guardrails. From reactive troubleshooting to end-to-end observability. From generated UI code to framework-aware, design-system-aware development agents. From citizen developers to AI enabled power users.
The thread connecting all of them is that enterprise AI cannot simply be layered on top of existing complexity. It has to be woven into the architecture. The organizations that succeed will not necessarily be the ones that deploy the most copilots, generate the most code, or automate the largest number of workflows.
They will be the ones that combine speed with judgment. AI with trusted data. Autonomy with governance. Developer productivity with engineering discipline. Innovation with observability.
And intelligent agents with platforms designed to make them safe, useful, and scalable. That is where the real value is. And that is the trajectory these sessions collectively explored.
Again, would like to thank to our sponsors, Infragistics and Microsoft – and see you on November 16th for the #MSIgniteNYC conference! And congratulations for Brian Stith for winning the Quest headset of the raffle!
