Microsoft Build 2025: Inside the Dawn of the “Agentic Web”

Podcast: Microsoft Build 2025_ Unpacking the Age of AI Agents, From Grand Vision to Ground Reality

Introduction: Beyond the Hype, a New Computing Paradigm

Microsoft Build 2025, held from May 19-22 in Seattle, was not a typical developer conference. It was the formal declaration of a new strategic era for the company: the “age of AI agents”.¹ The atmosphere was a complex mixture of groundbreaking ambition and corporate chaos. On one hand, Microsoft presented a cohesive, powerful vision for an interconnected AI future; on the other, the event was marked by on-stage protests over military contracts and the sobering backdrop of recent mass layoffs, creating a palpable sense of developer whiplash from the relentless AI hype cycle.³

In the opening keynote, CEO Satya Nadella, alongside CTO Kevin Scott, articulated the conference’s central theme: the creation of an “open agentic web”.² This vision served as the narrative thread connecting every major announcement, from the evolution of Azure and GitHub to the fundamental reimagining of Windows itself. It represents a future where autonomous AI agents are first-class citizens of the digital world, capable of reasoning, planning, and acting on behalf of users and organizations.

This report will dissect the announcements from Build 2025, moving beyond the press releases to analyze the strategic implications for developers, enterprises, and the tech industry at large. The conference revealed four core pillars of Microsoft’s strategy for this agentic future:

1. A New Class of AI Agents: A definitive shift from simple chatbots to autonomous, collaborative AI systems that can be orchestrated to solve complex problems.
2. The Platforms to Build Them: The unification of the Azure AI Foundry and the new Windows AI Foundry, creating a seamless development pipeline from the cloud to the edge.
3. The Tools to Command Them: The evolution of GitHub Copilot from a “pair programmer” to a “peer programmer” and the deep integration of agentic workflows into Visual Studio.
4. The Data to Fuel Them: The critical role of Azure’s data and analytics stack, now being re-engineered to serve as the long-term memory and knowledge base for intelligent agents.

The following table provides a high-level overview of the most impactful announcements, offering a quick guide to the key developments that will be explored in detail throughout this analysis.

The Agentic Web: Microsoft’s Blueprint for an Interconnected AI Future

At the heart of Build 2025 was the articulation of a new computing paradigm: the “open agentic web”.² This concept moves beyond the current internet of human-navigated documents and applications to envision a web where autonomous AI agents can discover, communicate, and collaborate with each other and with digital services to accomplish complex goals. This is not merely about smarter chatbots; it is a fundamental restructuring of how software and information are interconnected, with protocols and standards designed for machines first.

The Protocols of Connection

To enable this vision, Microsoft announced its deep commitment to two key open protocols, positioning them as the foundational standards for agent-to-agent and agent-to-app communication.

• Model Context Protocol (MCP): Described as the “universal USB-C connector for AI,” MCP is a standardized framework for AI agents to securely connect with and access the capabilities of native applications and external services.¹¹ By integrating MCP support across its entire ecosystem—including GitHub, Copilot Studio, Azure AI Foundry, and Windows 11—Microsoft is signaling a major push for industry-wide adoption.² This protocol allows an application to expose specific functions or data sources to an agent with fine-grained permission controls, turning siloed software into a network of discoverable “tools” that agents can use to perform tasks. Microsoft’s decision to join the MCP Steering Committee further solidifies its intent to shape this emerging standard.²
• Agent-to-Agent (A2A) Protocol: While MCP defines how agents talk to apps, the A2A protocol governs how agents talk to each other. Now in preview for agents built for Microsoft Teams, A2A enables secure, peer-to-peer communication without requiring a centralized intermediary.¹⁵ This is the technical underpinning of the “multi-agent orchestration” that Microsoft repeatedly showcased, where a primary agent can delegate sub-tasks to specialized agents, each contributing its unique skills to solve a larger problem.

NLWeb: The HTML for Agents

Perhaps one of the most forward-looking announcements was the introduction of NLWeb, a new open project that aims to do for conversational interfaces what HTML did for the visual web.¹ NLWeb allows any website or service to easily expose a conversational endpoint that agents can interact with. Crucially, every NLWeb endpoint is also an MCP server by default, making the web’s vast repository of information and services programmatically accessible to AI agents in a standardized way.²

By championing these open protocols, Microsoft is executing a sophisticated long-term strategy. The company is fostering an open ecosystem where anyone can build agents and services that adhere to these standards. As this ecosystem grows, the value of Microsoft’s own platforms—which offer the deepest, most seamless, and most secure integrations with MCP and A2A—increases exponentially. This approach allows Microsoft to position itself as the central, indispensable hub of the agentic economy, commoditizing the individual AI agents while capturing immense value at the platform and infrastructure layer.

Azure AI Foundry: The Factory Floor for Enterprise Agents

If the agentic web is the vision, Azure AI Foundry is its industrial core—the “AI agent factory” where enterprise-grade intelligent systems are built, deployed, and governed.² The announcements at Build 2025 significantly expanded the Foundry’s capabilities, transforming it from a model catalog into a comprehensive, end-to-end platform for agentic AI development.

An Expanding, Agnostic Model Catalog

A key strategic move was the expansion of the Foundry’s model catalog to over 1,900 models, reinforcing Azure’s position as an agnostic “platform of platforms”.¹⁵ Notably, this includes models from direct competitors, such as xAI’s Grok 3 and Black Forest Labs’ Flux Pro 1.1, alongside OpenAI’s latest, including the Sora video generation model and the powerful GPT-5 series.² This strategy suggests Microsoft is confident in winning the infrastructure war, believing that enterprises will choose Azure for its security, governance, and integration capabilities, regardless of which underlying model they use.

Intelligent Tooling for Developers

To manage this growing complexity, Microsoft introduced several new tools designed to optimize the development and deployment of AI applications.

• Model Router: This new service, powered by a fine-tuned small language model (SLM), automatically selects the optimal model for a given prompt based on its complexity, performance requirements, and cost. Microsoft claims this can reduce inference costs by up to 60% with no loss in fidelity, addressing a major pain point for businesses deploying AI at scale.²
• Foundry Observability: Now in preview, this feature provides end-to-end monitoring for AI agents. It offers a streamlined dashboard with built-in metrics for performance, quality, and cost, alongside detailed trace logs of an agent’s reasoning steps and tool calls. This directly tackles the “black box” problem, giving developers the visibility needed to debug, trust, and optimize complex agentic systems.²
• Project Amelie: Microsoft also offered a glimpse into the future with Project Amelie, an autonomous agent from Microsoft Research that can build a complete, validated machine learning pipeline from a single natural language prompt, generating reproducible Python code and detailed evaluation metrics.¹⁰

Enterprise-Grade Governance and Security

Leveraging its long history in the enterprise, Microsoft unveiled a suite of security and governance tools purpose-built for the agentic era.

• Microsoft Entra Agent ID: Now in preview, this feature assigns a unique, first-class identity to every agent built with Azure AI Foundry or Copilot Studio. This allows agents to be managed within an organization’s existing Entra directory, enabling standard security practices like access control, policy enforcement, and auditing for non-human workers. It is Microsoft’s answer to preventing “agent sprawl” and the security blind spots that could emerge as thousands of agents are deployed within an enterprise.¹
• Purview and Defender Integration: Microsoft Purview’s data security and compliance controls are being extended to agents, enabling automated data classification, eDiscovery, and Data Loss Prevention (DLP) for AI interactions. Simultaneously, Microsoft Defender for Cloud integrates with the Foundry to provide runtime threat protection against attacks like prompt injection, sensitive data leakage, and wallet abuse.¹

These announcements reveal a preemptive strategy. Microsoft understands that the proliferation of AI agents will create unprecedented challenges in security, governance, and observability. By building the “boring but essential” infrastructure to manage these issues from the outset, the company is creating a powerful competitive moat. While competitors focus on raw model capabilities, Microsoft is building the enterprise control plane for the agentic future.

GitHub Copilot Ascendant: Your New AI Teammate

Microsoft Build 2025 marked a fundamental evolution for GitHub Copilot, shifting its role from a real-time “AI pair programmer” to an autonomous “peer programmer” capable of handling entire development tasks independently.¹¹ This transition is the centerpiece of Microsoft’s vision for “Agentic DevOps,” a new software development lifecycle (SDLC) where intelligent agents collaborate with human developers.¹

The GitHub Copilot Coding Agent

The star of this transformation is the new GitHub Copilot Coding Agent, now in preview for Copilot Enterprise and Pro+ subscribers.¹⁴ This is not merely an enhanced chat feature; it is an autonomous entity integrated directly into the GitHub platform. Its workflow represents a new paradigm for development:

1. Issue-Driven Activation: A developer can assign a GitHub issue directly to the Copilot agent (e.g., @Copilot fix this bug) to initiate a task.²⁴
2. Autonomous Workflow: The agent spins up a secure, sandboxed development environment using GitHub Actions. It then clones the repository, analyzes the codebase using Retrieval-Augmented Generation (RAG) to understand the project’s context, and begins implementing changes across multiple files to address the issue.¹⁴
3. Human-in-the-Loop: As the agent works, it pushes commits to a draft pull request and provides detailed session logs that show its reasoning and validation steps. This transparency allows the developer to monitor progress, provide feedback through PR comments, and ultimately review and merge the completed work.²⁴ The agent can even iterate on feedback, making it a true collaborative partner.

Open-Sourcing Copilot Chat

In a significant strategic move, Microsoft announced that the GitHub Copilot Chat extension for Visual Studio Code will be open-sourced under the MIT license.¹ This decision is a direct response to the rise of competitive AI-native IDEs like Cursor and serves multiple purposes: it solidifies VS Code’s position as the premier open platform for AI development, fosters community trust and contribution, and allows developers to inspect and customize how AI works within their most critical tool.

The introduction of the Coding Agent fundamentally redefines the SDLC. The traditional, human-led phases of planning, coding, testing, and creating a pull request are now collapsed into a single, agent-driven workflow initiated by a high-level command. The developer’s role is elevated from writing line-level code to defining architectural goals and reviewing the AI’s automated implementation. This is the birth of “Agentic DevOps,” a model that promises to dramatically accelerate development velocity but will also have profound long-term effects on how engineering teams are structured, what skills are valued, and how productivity is measured.

The Modern Developer’s Toolbox, Reimagined for AI

The agentic revolution showcased at Build 2025 extends deep into the core tools that developers use every day. Both Visual Studio and VS Code are being transformed into AI-native environments, while the.NET platform is evolving to simplify cloud-native and AI-powered development.

Visual Studio & VS Code: The AI-Infused IDE

Microsoft is deeply embedding agentic workflows into its flagship IDEs to move beyond simple code completion.

• Visual Studio “Agent Mode”: Now in preview, this new mode in Visual Studio acts as an AI assistant that can plan and execute complex, multi-file changes. It can interact with connected tools like GitHub to read issues, Azure to check deployment status, and even Figma to understand design specifications, allowing developers to delegate entire features to the AI.²⁸
• VS Code Enhancements: The world’s most popular code editor is receiving deeper support for the Model Context Protocol (MCP), a revamped tool picker for agents, and direct integration for assigning tasks to the GitHub Coding Agent from within the editor UI.¹³ The open-sourcing of Copilot Chat is a clear strategic play to ensure VS Code remains the primary hub for AI-native development, fending off challengers by embracing the open-source community.⁵

####.NET in the AI Era

The.NET ecosystem received significant updates aimed at modernizing development and simplifying the integration of AI.

• .NET Aspire 9.3: The cloud-native stack for building distributed applications is now generally available. The latest version matures into a production-ready framework with enhanced observability, resilience patterns, and a new GitHub Copilot integration directly in the Aspire dashboard for AI-powered insights.³¹
• C# and.NET 10 Productivity: A major quality-of-life improvement for C# developers was the announcement that, starting with.NET 10 Preview 4, it’s possible to run C# scripts directly without a project file (dotnet run app.cs). This seemingly small change significantly lowers the barrier for quick scripting, testing, and experimentation, a feature long enjoyed by languages like Python.³²
• AI-Powered Modernization: The new GitHub Copilot for.NET Upgrades capability represents a powerful application of agentic AI to solve a persistent enterprise problem: legacy modernization. This tool uses AI agents to analyze older.NET Framework codebases, plan a migration strategy to modern.NET, and execute the necessary code conversions and dependency updates.³²

While these tools promise a massive boost in productivity, they arrive in a tense climate for developers. The relentless corporate push for AI-driven efficiency is directly linked by many in the community to recent mass layoffs and a cooling job market.³³ This has created a potential “vicious cycle”: Microsoft builds AI tools that allow senior developers to amplify their output, which is then used to justify workforce reductions. However, these layoffs contribute to a “demoralized workforce” and an “atmosphere of fear,” which could ultimately stifle the human creativity and meticulous engineering required to build the next generation of reliable, high-quality AI systems.⁵

Windows as an AI Platform: Intelligence at the Edge

One of the most significant strategic shifts at Build 2025 was the aggressive repositioning of Windows as a first-class platform for AI development and deployment at the edge. For years, serious AI and machine learning work has been synonymous with Linux. Microsoft’s announcements signal a concerted effort to change that narrative.

Windows AI Foundry: Unifying Local and Cloud

Microsoft rebranded the “Windows Copilot Runtime” to Windows AI Foundry, creating a naming and feature parity with its cloud counterpart, Azure AI Foundry.³⁵ This move establishes a unified, end-to-end AI development stack that allows developers to seamlessly move between local, on-device work and cloud-based training and deployment.

Foundry Local & On-Device AI

The core of this local-first strategy is Foundry Local, a new runtime for Windows and Mac that enables developers to download, test, and run open-source models entirely offline.¹⁰ This is complemented by several key on-device AI capabilities:

• New AI APIs: The Windows App SDK 1.7.2 includes new, ready-to-use APIs for common AI tasks like text summarization, image description, and Optical Character Recognition (OCR). These APIs run locally, leveraging the Neural Processing Units (NPUs) on Copilot+ PCs for efficient, privacy-preserving performance.³⁷
• On-Device Fine-Tuning: Developers can now use Low-Rank Adaptation (LoRA) to fine-tune the built-in Phi Silica small language model with their own custom data. This allows for the creation of specialized, private models that run entirely on-device, a powerful feature for applications that handle sensitive information.³⁷
• Native MCP Support: Windows 11 will have native support for the Model Context Protocol (MCP), turning the operating system itself into a platform for agentic computing. This allows locally installed AI agents to securely and seamlessly interact with Windows applications that expose their functionality via MCP.³⁷

Open-Sourcing WSL

Furthering its commitment to the developer community, Microsoft announced that the Windows Subsystem for Linux (WSL) is now fully open source.¹ This move was widely praised and is seen as a critical step toward enabling deeper integrations with essential developer tools like Docker, making Windows a more viable and powerful environment for cross-platform and containerized development.

Collectively, these announcements represent an aggressive strategy to reclaim developer mindshare from the Linux and macOS ecosystems. By providing a robust local AI runtime, enabling on-device model customization, and embracing open standards and open source, Microsoft is aiming to make Windows the premier platform for building the next generation of AI-powered applications at the edge.

The Human Element: A Reality Check on the AI Revolution

Beneath the polished keynotes and ambitious roadmaps, Build 2025 was shadowed by a more complex reality. The conference provided a stark look at the current state of AI: a technology of immense potential that remains visibly brittle, and a developer community grappling with a mixture of excitement, skepticism, and anxiety.

The Demo Effect and AI Fragility

A recurring theme, noted by attendees and journalists alike, was the prevalence of failed or flawed AI demos, even during high-profile presentations by executives like Satya Nadella and Scott Hanselman.³ One live demo of an AI travel agent incorrectly identified the season in New Zealand, while other presentations had to revert to pre-recorded videos after live agents failed.³ These public struggles served as a powerful counter-narrative to the marketing hype, offering a transparent glimpse into the current fragility and unpredictability of agentic AI systems.

A Tale of Two Builds: Corporate Vision vs. Developer Reality

The optimistic, AI-centric vision presented on stage stood in sharp contrast to the sentiment found in developer communities on platforms like Reddit.³ The feedback from developers on the ground revealed several key concerns:

• AI Fatigue: A palpable sense of burnout from the relentless corporate push to “shoehorn AI into everything,” regardless of its suitability.³ Many felt that “AI-powered” was becoming a hollow marketing buzzword for features that were not genuinely innovative.
• Skepticism and Hype: A widespread belief that the technology is far from delivering on its grand promises. Developers pointed to the failed demos as evidence that AI is still “completely unpredictable and unreliable garbage,” with one Reddit thread titling the event “The era of failed AI demos”.³
• Job Insecurity: A direct and anxious connection was drawn between the industry’s push for AI-driven productivity and the recent wave of mass layoffs. Developers expressed fears that they are being asked to build the very tools that will make their own jobs redundant, with one user noting, “We are the frontline of AI users and abusers. We’re the ones tinkering, playing, and ultimately cutting our own throats”.³³

The Unspoken Context: Protests and Layoffs

The official narrative of Build 2025 was also punctuated by events that revealed a company under significant pressure. Satya Nadella’s keynote was interrupted by a Microsoft employee protesting the company’s cloud contracts with the Israeli military, a moment that highlighted ongoing internal dissent.⁶ This occurred against the backdrop of 6,000 recent layoffs, which journalists described as creating a “demoralized workforce” and a “pervasive atmosphere of fear” within the company.⁵

This confluence of events suggests that the AI hype cycle may be approaching a tipping point. Microsoft is making massive, multi-billion-dollar investments in an “agentic future,” yet the public-facing products are visibly struggling, and the developer community—the very people needed to build this future—is expressing significant burnout and anxiety. The widening disconnect between the corporate vision and the on-the-ground reality poses a substantial risk for Microsoft, which could lose developer trust if the promised agentic revolution fails to deliver tangible, reliable results in the near future.

Conclusion: Charting the Course for an Agent-Driven Future

Microsoft Build 2025 was a landmark event, not just for the volume of its announcements, but for the clarity and ambition of its strategic vision. The company has laid out a comprehensive blueprint for the future of software, centered on the paradigm of the “open agentic web.” If successful, Microsoft will have constructed the foundational operating system for the next era of computing.

The core strategies are clear: unify the AI development stack from the local device to the cloud with the AI Foundry; establish open protocols like MCP and A2A to win the platform war; transform the software development lifecycle with agentic DevOps powered by a newly autonomous GitHub Copilot; and revitalize Windows as a premier destination for AI development at the edge.

However, the path forward is fraught with challenges. The technology, while promising, is still in its infancy and prone to failure. The developer community, Microsoft’s most critical constituency, is wary of the hype and anxious about the economic implications of AI-driven automation. And the internal corporate culture appears to be in a state of turmoil, balancing aggressive innovation with the human cost of mass layoffs.

For those navigating this new landscape, the takeaways are clear:

• For Developers: It is time to begin experimenting with the new class of agentic tools. The GitHub Coding Agent and Foundry Local are not future concepts; they are available in preview today. Understanding and mastering open protocols like MCP will be a critical skill as the agentic ecosystem matures.
• For Tech Leaders: The time to evaluate the security and governance implications of multi-agent systems is now. Tools like Entra Agent ID and the new observability features in Azure are designed to address the challenges of managing a workforce of thousands of AI agents. Furthermore, data strategies must be re-evaluated to become “AI-native,” ready for the demands of agentic retrieval and analysis.
• For Everyone: A healthy dose of skepticism is warranted. It is crucial to separate the revolutionary long-term potential of agentic AI from the current, often-buggy reality. The transformation will not happen overnight, but the foundational pieces are being put in place. The next 3-5 years will see a fundamental shift in how software is built, deployed, and used, and the announcements at Build 2025 have provided the most detailed roadmap yet for that future.