The August 2026 update for the AI Gateway tier (preview) of Azure API Management introduces new capabilities for observing AI workloads and governing model spend.

Release highlights

• Richer OpenTelemetry observability: AI Gateway can now emit logs, distributed traces, token metrics, and estimated cost metrics through the OpenTelemetry Protocol. The built-in monitoring experience helps teams investigate model and MCP tool activity, policy execution, latency, errors, token consumption, and individual traces.
• Model cost monitoring and budget enforcement: Teams can review estimated model spend by API key and model, then use cost limit policies to set calendar-based budgets and block requests when configured limits are reached.

The release also streamlines Microsoft Foundry model imports, refines provider onboarding, improves portal reliability and error guidance, expands Anthropic Messages compatibility, and adds an in-product What's new experience.

For configuration guidance, important upgrade information, and the complete list of changes, read the full August 2026 release notes in the AI Gateway portal.

Try the latest capabilities in the AI Gateway portal.

"Every journey begins with curiosity. Mine started in 18 October 2023 with a simple decision to join the Microsoft Student Ambassador program."

When I became a Microsoft Student Ambassador in 2026, I never imagined that one day I would be writing this as a Microsoft Most Valuable Professional (MVP).

Back then, I wasn't thinking about titles or recognition. I simply wanted to learn new technologies, connect with like-minded people, and become a better developer.

Looking back today, I realize that this journey was never about earning badges it was about becoming someone who could make a meaningful impact on others.

Like many students, I joined the Student Ambassador program because I loved technology and wanted to learn beyond the classroom.

Every Microsoft Learn module completed, every community event attended, and every challenge accepted became another opportunity to grow.

What started as curiosity gradually turned into confidence.

The Student Ambassador program gave me opportunities that a traditional classroom never could.

I learned how to:

• Speak confidently in front of an audience.
• Organize technical events.
• Collaborate with communities worldwide.
• Build projects using Microsoft's latest technologies.
• Write technical content that helps others learn.

Every experience pushed me a little further outside my comfort zone.

As my journey progressed, I realized that learning becomes far more meaningful when it is shared.

Over the years, I had the opportunity to:

• Deliver technical sessions for students.
• Organize community events.
• Contribute articles to Microsoft Tech Community.
• Explore GitHub Copilot and AI-powered development.
• Build AI projects using Microsoft Foundry, Azure AI Search, GPT-4.1, and Retrieval-Augmented Generation (RAG).
• Participate in the Microsoft Agents League Hackathon.
• Moderate the Microsoft Developer YouTube livestream during Microsoft Build.
• Speak at Microsoft's Reasoning Agents Live Battle, presenting ShadowQuest, a multi-agent RPG demonstrating collaborative AI agents.

Each milestone taught me something new not only about technology but also about communication, leadership, and community.

One of the greatest gifts of this journey has been the people.

I met mentors who encouraged me, fellow Student Ambassadors who inspired me, and community members who constantly motivated me to keep learning.

Technology changes quickly, but communities create lasting impact.

Every collaboration, every conversation, and every event reminded me that growth happens faster when people learn together.

Receiving the email that I had been recognized as a Microsoft Most Valuable Professional (MVP) was a moment I'll never forget.

It wasn't just recognition for writing blogs or speaking at events.

It represented years of continuous learning, community contributions, countless hours spent building projects, helping others, and saying "yes" to opportunities that once felt impossible.

Becoming an MVP wasn't the finish line.

It became the beginning of an even bigger responsibility to continue sharing knowledge, supporting the community, and helping others start their own journeys.

If these five years taught me anything, it's this:

• Never stop learning.
• Share your knowledge freely.
• Don't wait until you're an expert to help others.
• Growth happens outside your comfort zone.
• Communities can change careers—and sometimes even lives.

The titles eventually change.

The lessons stay forever.

Although my journey as a Microsoft Student Ambassador has come to an end, my journey with the Microsoft community is just beginning.

As a Microsoft MVP, I hope to continue building, writing, speaking, mentoring, and contributing to the developer community.

If you're currently a Student Ambassador or thinking about becoming one my advice is simple:

• Take every opportunity.
• Build projects.
• Write blogs.
• Speak at events.
• Ask questions.
• Help others.

You never know where one opportunity might lead.

Mine led me from a curious student in 2023 to becoming a Microsoft MVP in 2026.

And for that, I'll always be grateful.

Thank you, Microsoft. Thank you to every mentor, friend, and community member who has been part of this incredible journey.

The next chapter starts now. 💙

Microsoft Build 2026 brought developers together to explore what’s next across AI, agents, cloud platforms, data, and developer tools. This year, Microsoft Most Valuable Professionals (MVPs) delivered 20 lightning talks focused on practical, real-world approaches to building with Microsoft technologies.

From agentic AI patterns and MCP servers to production-ready Azure foundations and Microsoft Fabric experiences, these MVP-led sessions offer high-impact guidance for developers and technical leaders looking to turn emerging ideas into working solutions.

Top MVP-led lightning talks from Microsoft Build 2026

1. Build Intelligent Agents with Work IQ, Foundry IQ, and Fabric IQ

Speaker: Prashant G Bhoyar
Session: LTG448
YouTube recording: https://aka.ms/AA13c4jg

Prashant G Bhoyar explores how developers can build intelligent agents using Work IQ, Foundry IQ, and Fabric IQ. This session is a great starting point for anyone looking to understand how Microsoft’s AI platform capabilities can work together to create smarter, more context-aware agent experiences.

Use this talk to: help teams understand how different Microsoft IQ capabilities can connect across work, data, and AI workflows when designing intelligent agent experiences.

2. Closing the Loop: Feedback-based Learning for Agentic RAG on Azure

Speaker: Priyanka Shah
Session: LTG449
YouTube recording: https://aka.ms/AA13cjyh

Priyanka Shah dives into feedback-based learning for agentic retrieval-augmented generation on Azure. The session highlights an important shift in AI application design: moving beyond one-time responses toward systems that learn, improve, and refine outputs through feedback loops.

Use this talk to: guide discussions about improving AI quality over time and incorporating feedback into retrieval-augmented generation systems.

3. From Idea to Agent in Minutes: Copilot Studio + Claude Code

Speaker: Renato Romao de Souza
Session: LTG450
YouTube recording: https://aka.ms/AA13cjyj

Renato Romao de Souza shows how ideas can quickly become working agents using Copilot Studio and Claude Code. For builders looking for a fast path from concept to implementation, this talk demonstrates how modern tools can accelerate agent development.

Use this talk to: inspire rapid prototyping sessions, hackathons, or internal demos where teams want to move quickly from concept to agent.

4. Building an End-to-End Enterprise AI Platform on Azure

Speaker: Ehsan Eskandari
Session: LTG453
YouTube recording: https://aka.ms/AA13c4jl

Ehsan Eskandari focuses on what it takes to build an enterprise-ready AI platform on Azure. This session is especially relevant for teams thinking about architecture, scale, governance, and the practical foundations needed to support AI workloads across an organization.

Use this talk to: support planning conversations with platform, architecture, and leadership teams about what is required to move AI from experimentation to enterprise readiness.

5. From Code to Agents: Build Production MCP Servers on Azure Functions

Speaker: Jonah Andersson
Session: LTG455
YouTube recording: https://aka.ms/AA13cc99

Jonah Andersson covers how to build production Model Context Protocol (MCP) servers with Azure Functions. As MCP becomes increasingly important for connecting tools, data, and agent workflows, this session offers timely guidance for developers moving from prototypes to production-ready implementations.

Use this talk to: help developers understand how MCP can extend agent capabilities and how Azure Functions can support production-oriented implementations.

6. Beyond the Basics: What GitHub Can Do Today

Speaker: Scott Sauber
Session: LTG465
YouTube recording: https://aka.ms/AA13cc9b

Scott Sauber rapidly explores 10 lesser-known GitHub capabilities spanning AI, agentic workflows, GitHub Actions, and code collaboration. This foundational session gives developers practical ideas they can apply immediately to get more value from the GitHub platform.

Use this talk to: introduce teams to overlooked GitHub features, spark workflow improvements, and identify practical ways to strengthen automation, AI-assisted development, and code collaboration.

7. Stop Writing Prompts. Start Writing Specs.

Speaker: Roelant Dieben
Session: LTG464
YouTube recording: https://aka.ms/AA13c4jo

Roelant Dieben challenges developers to think beyond prompt writing and toward specification-driven approaches. As AI-assisted development matures, this session offers a valuable perspective on creating clearer intent, more predictable outcomes, and better collaboration between people and AI tools.

Use this talk to: encourage teams to improve how they define requirements, structure intent, and collaborate with AI-assisted development tools.

8. Building your own MCP server

Speaker: Stuart van der Lee
Session: LTG466
YouTube recording: https://aka.ms/AA13cjyk

Stuart van der Lee walks through the process of building an MCP server. For developers who want to extend agent capabilities and connect custom tools or services, this session provides a practical entry point into one of the most important emerging patterns in agent development.

Use this talk to: introduce developers to MCP fundamentals and help them identify where custom servers could connect agents to internal tools, services, or workflows.

9. Secure AI Agents in Azure: AI Gateway, Tools, and Trust

Speaker: David Okeyode
Session: LTG467
YouTube recording: https://aka.ms/AA13cjyl

David Okeyode addresses one of the most critical topics in AI adoption: security and trust. This session looks at secure AI agents on Azure, including the role of AI gateways, tools, and trusted architecture patterns that help organizations build responsibly.

Use this talk to: anchor conversations about responsible AI architecture, secure agent design, and the trust patterns teams need before deploying AI systems broadly.

Watch, share, and learn from the MVP community

MVP-led sessions bring a practical community perspective, combining real-world solutions, candid lessons, and implementation experience. Whether you’re learning a new concept, preparing for a technical discussion, supporting a user group, or evaluating emerging Microsoft technologies, these talks offer focused insights you can apply and share.

Explore the sessions above and use them to spark deeper learning, discussion, and experimentation across your teams and communities.

Be sure to check out more MVP-led sessions at Microsoft Ignite 2026, coming up November 17-21 in San Francisco.

Want to Learn More About the MVP Program?

To find an MVP and learn more about the Program visit the MVP website and follow our updates on LinkedIn. 

Join us for a future live session through the Microsoft Reactor where we walk through what the MVP program is about, what we look for, and how nominations work. These sessions are designed to help you connect the dots between the work you’re already doing and the impact the MVP Program recognizes — with time for questions, examples, and real conversations.

Today, we're excited to announce APIOps CLI, a new command-line experience designed to help organizations manage Azure API Management (APIM) using modern configuration-as-code and GitOps practices.

As APIs become increasingly central to digital transformation, organizations need a reliable way to manage API definitions, policies, products, diagnostics, and gateway configuration across multiple environments. APIOps CLI provides a streamlined, developer-friendly approach to extract, version, review, and publish API Management configuration through familiar DevOps workflows.

Why APIOps CLI?

Traditional API management processes often rely on manual configuration changes, environment-specific customizations, and limited visibility into what changed and why. As API estates grow, these approaches become difficult to scale, audit, and govern.

APIOps CLI addresses these challenges by enabling teams to manage API Management configuration as source-controlled artifacts. Every change can be reviewed through pull requests, tracked through Git history, and promoted consistently across development, test, and production environments.

The result is improved governance, greater reliability, better collaboration between API developers and platform operators, and a simpler path toward enterprise-scale API operations.

What APIOps CLI Enables

APIOps CLI provides capabilities that help organizations adopt a true APIOps model:

• Extract API Management configuration into local artifact files
• Store and version configuration in Git repositories
• Review changes through standard pull request workflows
• Publish approved artifacts back into API Management environments
• Promote configuration consistently across environments
• Scaffold GitHub Actions and Azure DevOps pipelines
• Support automated CI/CD deployment patterns
• Enable auditable, repeatable API configuration management

By treating API Management configuration as code, organizations gain the same operational excellence practices that software development teams have relied on for years.

A Modern GitOps Workflow for APIs

The APIOps CLI workflow follows a simple yet powerful pattern:

• Extract configuration from an existing API Management instance.
• Store the generated artifacts in source control.
• Review and approve changes through pull requests.
• Run automated validation and deployment pipelines.
• Publish approved configuration back to target API Management environments.

This approach creates a clear separation between authoring, review, approval, and deployment while maintaining a complete audit trail of API platform changes.

For organizations already practicing GitOps, APIOps CLI integrates naturally into existing development workflows and governance processes.

Built for Real-World Enterprise Scenarios

APIOps CLI is designed to support customers operating at enterprise scale. Common use cases include:

• Migrating away from manual API Management administration
• Standardizing deployments across multiple environments
• Establishing controlled promotion paths from development to production
• Implementing governance and compliance requirements
• Supporting platform engineering and API platform teams
• Managing large inventories of APIs, products, policies, and configurations
• Enabling self-service API development with centralized governance

Whether you're operating a single API Management instance or managing a large multi-team API platform, APIOps CLI provides a foundation for consistent and repeatable operations.

Integrated with Your Existing Toolchain

APIOps CLI works alongside the tools teams already use:

• GitHub
• Azure DevOps
• Azure Pipelines
• GitHub Actions
• Azure CLI
• Existing Git repositories and branching strategies

The tool can generate CI/CD scaffolding to accelerate adoption, helping teams move from manual operations to automated deployments with less effort.

Open Source and Community Driven

APIOps CLI is available as an open-source project under the Azure GitHub organization. The repository includes source code, architecture guidance, command documentation, CI/CD examples, walkthroughs, troubleshooting guidance, and reference material.

By making the project open and community-driven, we are enabling customers, partners, and contributors to participate directly in the evolution of Azure API Management DevOps practices.

Getting Started

Getting started is straightforward:

• Install the APIOps CLI package.
• Authenticate with Azure.
• Extract an existing API Management instance into local artifacts.
• Commit those artifacts to a Git repository.
• Review and approve changes through pull requests.
• Publish approved changes back to Azure API Management.

We recommend beginning with a non-production environment to establish your workflow, validate governance processes, and familiarize teams with the configuration-as-code model.

Looking Ahead

APIs have become a strategic asset for every organization. As API estates continue to expand, successful teams will increasingly adopt automation, governance, and GitOps practices to maintain speed without sacrificing control.

APIOps CLI is an important step in that journey. It provides a modern foundation for managing Azure API Management configurations with the same rigor, automation, and reliability that organizations expect from modern software delivery practices.

We invite you to explore APIOps CLI, try it in your environment, share feedback, and join us in shaping the future of API operations on Azure.

Resources

• APIOps CLI GitHub repository: https://github.com/Azure/apiops-cli/tree/main
• Microsoft Learn: Manage API Management configuration with APIOps CLI 

Claude Fable 5.1 is now joining the frontier models available in Copilot Cowork and Copilot Studio, giving customers more choice as they delegate more complex tasks to AI. 

Fable 5.1 is designed for long-running work, financial analysis, and front-end visual coding, with tighter plans up front and more concise summaries at the end. 

As more work is delegated to AI, the quality of the result depends on both the model and the context. Work IQ grounds Fable 5.1 in your files, meetings, chats, and business data—within your existing permissions—so it can reason over your work instead of the prompt alone resulting in more relevant and accurate responses, with sources you can trace back to your work.

Get started today 

Claude Fable 5.1 is rolling out today to eligible users in Copilot Cowork and Copilot Studio. 

Availability may vary by region and organization. Admins can  manage access and configure availability for their organization through the Microsoft 365 admin center. 

For the latest rollout information, see Microsoft 365 Roadmap and Microsoft Copilot release notes. 

To learn more about the model, see Anthropic’s announcement of Claude Fable 5.1