We are all familiar with the basic concept of Microsoft Windows as an operating system. You install apps, click around with a mouse, and maybe script a few things on the side. That model still exists, but it now sits beside something fundamentally new: software that acts for the user rather than waiting for instructions. AI agents can interpret tasks, make decisions, and execute actions at a level that looks less like a tool and more like a digital coworker.
That shift forces a rethink of what an operating system must do. If agents are going to perform tasks that mimic human behavior—retrieving files, changing settings, manipulating applications—Windows has to recognize them, govern them, and contain them. At Ignite 2025, Microsoft previewed a number of updates to Windows that show the early contours of that transformation.
I sat down with Jatinder Mann, partner director for product management at Microsoft, and Divya Venkataramu, director of product marketing management for the Windows Developer Platform at Microsoft, to talk about the updates and what they mean for both businesses and users.
A New Plumbing Layer for Agentic Interaction
One of the most important pieces in this pivot is native support for the Model Context Protocol. MCP gives agents a standardized way to interact with tools and data sources—critical at a time when AI capabilities are showing up in unexpected places, including a new wave of AI-enabled browsers competing to become the central interface for digital work. As those browsers introduce their own agentic features, it becomes clear that browsing alone isn’t enough. The OS must provide stable, secure access points for anything that reaches into system resources.
Windows takes MCP a step further by introducing an on-device registry of “agent connectors”—MCP servers that represent specific capabilities like file access or system configuration. All calls to these connectors flow through an OS-level proxy that handles identity, permissions, consent, and audit logging.
As Jatinder explained during our discussion, “This infrastructure can’t be delivered easily just by middleware or apps alone, because it demands that OS-level integration for security, consent and control.” That comment captures why Microsoft is embedding these controls at the platform layer instead of leaving them to individual developers.
Clear Capabilities, Clear Guardrails
The first connectors available in preview focus on two core areas: File Explorer and System Settings. They let agents retrieve and organize files, or modify settings like display mode or accessibility features. These are small, familiar tasks—but they demonstrate why structure matters. A connector advertises what it can do, under what conditions, and with what restrictions. There’s no ambiguity, no scraping the interface, and no guessing at behaviors.
Windows backs these capabilities with an explicit consent model. Anytime an agent wants to access a connector, the system prompts the user with a clear explanation and options: allow once, always allow, or never allow. It’s a familiar pattern, but it needs to avoid becoming invisible noise, the way cookie banners and UAC prompts have.
Transparency is essential here. A system prompt telling you exactly what the agent wants and why it wants it is far more useful than a generic permission request. And because every choice can be reversed from a centralized settings page, the model encourages cautious experimentation rather than blanket approvals that can’t be undone.
Giving Agents a Space of Their Own
One of the most interesting changes is Agent Workspace—a separate, isolated desktop environment where agents operate under their own identity. Instead of co-mingling their actions with yours, agents run alongside you in a contained session. The OS can attribute actions, monitor access, and limit what the agent can reach.
The design recognizes an emerging reality: agents behave less like traditional software and more like autonomous actors. They can execute tasks faster than humans, and sometimes more aggressively than expected. A misinterpreted instruction can lead to unintended consequences. The Genie Problem—where an agent fulfills the literal meaning of a prompt rather than the intended one—isn’t hypothetical. Containment matters.
As Divya put it, “Agents at any time on Windows will operate with least-privileged access. They will only have access to what you define.”
Least privilege has been a driving mantra since the inception of cybersecurity. It’s crucial to apply it to agentic AI as well, and build a controlled boundary around autonomous software before it becomes deeply embedded in everyday workflows.
Security Expectations Rise With Autonomy
Once a system allows autonomous software to act on behalf of a user, the bar for security rises dramatically. Connectors now must be signed, packaged, and associated with explicit capability declarations. The OS knows who created them, what they can do, and whether they’ve been tampered with. Agents also run through a standardized proxy that enforces authentication, authorization, and auditing.
The need for visibility is obvious. If an agent deletes the wrong calendar entry, modifies a configuration incorrectly, or escalates privileges in an unexpected way, the system must be able to determine exactly which agent did it and why. That level of observability wasn’t necessary when applications simply ran at the user’s direction. It becomes non-negotiable when the software can act independently.
Organizations are already starting to treat agents less like tools and more like a new class of digital worker—capable, fast, and potentially error-prone. Without OS-level controls, there’s no reliable way to monitor or manage that behavior.
Local AI as a Native Capability
Another key component is the expansion of on-device AI processing. Windows is introducing APIs for image generation, video enhancement, content search, and other model-driven capabilities—including support for running more advanced models directly on the device. Local inference reduces latency, keeps sensitive data off the network, and gives agents faster access to capabilities they rely on.
This part isn’t unique to Windows, but the integration with OS-level connectors and permissions gives it a different flavor. Agents can call local models with the same governed pathways they use for system resources, which keeps the behavior predictable and auditable.
A Platform Beginning to Shift
None of this suggests Windows is suddenly becoming an agent-first operating system. Human users still sit at the center of the experience. But the groundwork for a dual model—humans operating in one space, agents operating in another—has begun.
The operating system is emerging as the place where identity, permissioning, containment, and logging converge. As more applications, browsers, and services ship their own AI assistants or embedded agents, Windows is positioning itself as the arbiter of what those agents can do safely.
This is the early stage of a long transition. The value of AI agents will take time to reveal itself at both the enterprise and consumer levels. But the architectural pieces—standard interfaces, clear permissions, isolated execution environments, and system-level observability—are starting to appear.
