Notes from the trenches of real projects. What worked, what didn't, and why — no marketing spin.
With agents, a single request can fan out into model calls, retrievals, retries, and tool actions that cost far more than the prompt suggests. Here's how I measure, allocate, and govern that full cost — not just the token line — and tie it to outcomes.
A practitioner's reference for Power Platform core, Copilot Studio, Dataverse, Dynamics 365 Contact Center, and Dynamics 365 Customer Service.
This write-up shows how to build Skills in the new Copilot Studio agent experience. It covers the SKILL.md format, bundling scripts and resources, authoring and uploading, how the orchestrator uses them, and governance. It is separate from the legacy Bot Framework skill.
Azure Local is Microsoft's distributed infrastructure solution that extends Azure capabilities to customer-owned environments. This article provides a comprehensive overview of Azure Local, Foundry Local, and Microsoft 365 Local, their use cases, deployment options, and best practices for IT architects and decision-makers considering on-premises Azure solutions. With an appendix on agentic AI use cases on Azure Local and Foundry Local.
Discover ten core principles to transition AI agents from ideation to measurable business impact, including anchoring in real processes, maintaining scope discipline, integrating with live input channels, enforcing production-grade behavior, and planning for long-term flexibility.
Microsoft 365 E7, announced in March 2026, represents a strategic evolution of Microsoft's enterprise licensing to accommodate the rise of AI agents. This article explores what E7 includes, why it was created, and how it benefits organizations leveraging AI agents.
As AI agents become integral to business processes, reliable and repeatable testing is essential for confidence in deployment. This article introduces the Multi-Agent Test Environment (MATE) – an enterprise-grade framework for automated testing of AI agents across platforms and frameworks – and explains how its modular design addresses key challenges in agent testing. We explore why testing AI agents is critical, delve into MATE's architecture and features, compare MATE with alternative testing approaches, and outline MATE's roadmap, including red-team testing, enhanced cloud deployment, and support for emerging agent frameworks.
Choosing the right testing tool for your Copilot Studio agents: A detailed comparison of Copilot Studio Kit and Agent Evaluation (preview) to help you decide when to use each tool for optimal agent quality.
An in-depth exploration of Microsoft Frontier Agents, their architecture, capabilities, and impact on enterprise AI transformation.
Microsoft MVP & MCT | Low Code Hacker | Copilot, Copilot Studio, Power Platform & Azure Architect
I’m a Microsoft MVP focused on agentic AI, intelligent agents, and enterprise AI solutions. Using Microsoft Copilot Studio and Azure AI Foundry, I design and build systems that help people and organizations work smarter. This blog is a collection of field notes, practical insights, and real-world experiences—from architecture and orchestration patterns to lessons learned along the way. Your feedback is always welcome—let’s continue the conversation.
