How to build my own agentic os on windows?

Perplexity Sonar Pro

Answer: Build your agentic OS on Windows as a layered, local-first control plane on top of Windows, not by trying to replace the Windows kernel.

The most practical answer is to treat an "agentic OS" as an orchestration layer that manages context, tools, memory, permissions, and workflows while Windows remains the underlying operating system. On Windows, the fastest path is to start with a small but complete stack: one LLM for reasoning, one orchestration framework for task loops, one automation layer for apps and shell commands, one memory store, and one UI for launching tasks. That gives you the core behavior of an agentic OS without taking on the impossible scope of building a real operating system. A good Windows-first architecture is: a planner/executor loop in Python, TypeScript, or C#; PowerShell and Windows automation for system actions; Playwright or UI Automation for browser and desktop control; SQLite plus a vector store for memory; and a local dashboard or tray app for user interaction. If you want stronger isolation, run risky actions in WSL2, Docker, or Windows Sandbox. If your Windows build supports Microsoft’s experimental agentic features, use them as a secure workspace boundary rather than the whole solution. The agent workspace model is useful because it gives agents separate accounts, scoped permissions, and controlled file access, which is exactly the kind of guardrail an agentic system needs. The key design principle is permissions first. Give the agent explicit access to only the folders, apps, and tools it needs, require confirmation for destructive actions, and log everything. An agentic OS becomes valuable when it reliably handles real workflows like research, email drafting, file organization, scheduling, and routine automation—not when it tries to act like a fully autonomous super-user. So the right way to build it is to begin with one concrete use case, implement the smallest working stack around it, and expand gradually into a modular desktop control plane that feels like an OS for agents.

Grok 4.3 (changed mind)

Answer: An agentic OS on Windows should be built as an orchestration and automation layer atop the existing OS, not by modifying its closed kernel.

The other models' responses collectively demonstrate that kernel-level changes are infeasible because Windows is proprietary and its core components cannot be safely or legally altered by third parties. Instead, the consensus correctly emphasizes creating a practical agentic control plane using WSL2 for Linux toolchains, frameworks like LangGraph or AutoGen for orchestration, PowerShell and UI Automation for system access, and strict sandboxing for safety. GPT-5.5's detailed modular architecture—covering UI, runtime, tool system, memory, and permissions—provided the clearest, most actionable shift in my thinking by highlighting achievable near-term value over multi-year kernel projects. This layered approach preserves full Windows compatibility while enabling autonomous agents through context management, skill files, and permission boundaries.

Gemini 3.5 Flash

Answer: Building a custom agentic OS on Windows is best achieved by developing an overlay orchestration layer that utilizes standard execution protocols like MCP and Windows automation APIs, rather than attempting to modify the OS kernel.

My core position remains firm: the most viable path to an agentic OS on Windows is a centralized, sandboxed orchestration layer. The collective feedback from other models reinforces this, specifically by exposing the impracticality of Grok 4.3's suggestion to modify the proprietary, closed-source Windows kernel. As GPT-5.5 and Kimi K2.6 correctly note, our goal is to build a cognitive control plane running atop the native operating system, utilizing Windows as the underlying execution engine. To refine this architecture, we should adopt the Model Context Protocol (MCP) highlighted by Claude Opus 4.7. MCP provides an open, standardized way to expose Windows-specific capabilities—such as PowerShell scripts, native UI Automation, and local file access—directly to the orchestrator as decoupled services. This minimizes custom wrapper code and creates a cleaner, highly modular tool registry. Furthermore, security and environment isolation must be strictly maintained. Running the core reasoning agent and complex Unix-centric toolchains within WSL2 or Docker containers protects the host Windows environment, while a lightweight Windows-native service or desktop tray application handles the user interface, keyboard shortcuts, and ambient notifications. Ultimately, a successful agentic OS on Windows is defined by smart context management and safe execution. By combining structured local Markdown vaults for personal memory, an MCP tool pipeline, and mandatory human-in-the-loop approvals for destructive operations, you can build a powerful, automated computing workspace without compromising system stability.

GPT-5.5

Answer: Build your own agentic OS on Windows as a secure orchestration layer on top of Windows, not by modifying or replacing the Windows kernel.

I maintain my previous position: the realistic way to build an “agentic OS” on Windows is to create an always-on agentic desktop/runtime layer that can understand goals, use tools, automate workflows, remember context, and ask for approval before risky actions. The strongest answers from the other models reinforce this. Kimi K2.6 correctly emphasizes that Windows is closed-source, so trying to replace or deeply modify the kernel is the wrong path for most builders. Claude Opus 4.7 gives the most practical engineering architecture: WSL2 for the agent runtime, LangGraph or a similar orchestrator, MCP-style tool servers, memory, Windows automation bridges, and a thin native shell. Gemini also rightly stresses sandboxing and permission control. I would not follow the kernel-modification approach suggested by Grok 4.3 unless your actual goal is low-level systems research. Writing drivers or modifying kernel behavior adds enormous complexity and risk while doing little to help the main goal: making Windows feel agentic. For an agentic OS, the important parts are perception, planning, tool use, memory, workflow automation, and safe execution—not kernel replacement. A good build path is: start with a local folder structure like `C:\AgentOS\`, create identity files, skills, logs, and project context; run an agent orchestrator in Python or TypeScript; connect it to an LLM through OpenAI, Anthropic, Ollama, or LM Studio; expose tools for filesystem access, PowerShell, browser automation, email/calendar APIs, screenshots/OCR, and app control through pywinauto, UI Automation, AutoHotkey, Playwright, or Power Automate Desktop. For the runtime, use LangGraph, AutoGen, Semantic Kernel, CrewAI, or a simple custom loop with planner, executor, memory, and approval steps. Store structured state in SQLite or Postgres, semantic memory in Chroma/Qdrant/Weaviate, and human-readable procedures in Markdown. If you want it to feel like an OS, add a tray app, command palette, global hotkey, notifications, voice input, and startup integration through Task Scheduler or a Windows service. Security should be designed from the beginning. Give the agent least-privilege access, restrict it to known folders, run code execution inside Docker, WSL2, Windows Sandbox, or a VM, and require confirmation before deleting files, sending messages, installing software, changing registry values, or spending money. Log every action so you can audit and debug failures. So the practical first milestone is not “build an OS”; it is “build a Windows-native agentic control layer that reliably completes one workflow.” Once one workflow works, add more tools, more memory, more UI, and more autonomy gradually.

Claude Opus 4.7

Answer: Build your agentic OS on Windows as a layered local-first stack: a WSL2 Linux core for the agent runtime, an orchestrator (LangGraph or a custom Python loop) wrapping an LLM, a tool/skill registry exposed via MCP, and a thin Windows-native shell for UI, automation, and startup integration.

I'm holding my position because the consensus across the table actually validates the core architecture I proposed — every model except Grok agrees you do not modify the Windows kernel, you build a control plane on top of it. My four-layer stack (WSL2 foundation → orchestrator → MCP tool registry → Windows shell) is essentially the same shape as what GPT-5.5 and Kimi K2.6 described, just more opinionated about the glue (MCP) and the runtime location (WSL2). What the other answers usefully sharpen rather than overturn: - Gemini 3.5 Flash and Kimi K2.6 both emphasize permissioned, sandboxed execution from day one. I agree and would explicitly fold this into the orchestrator layer: every tool call routes through a policy engine with allowlists, confirmation prompts for destructive actions, and an audit log. This is an addition to my stack, not a replacement. - GPT-5.5's point about starting with concrete workflows instead of "make an AI OS" is the right discipline. The architecture I proposed is the substrate; the first thing to actually build on it is one end-to-end task (organize a folder, summarize PDFs, daily digest) before adding autonomy. - Perplexity Sonar Pro's identity/skills/logs file convention is a great content pattern for the Memory layer I already specified — markdown files in a vault become the durable context the orchestrator injects per run. Worth adopting wholesale. - Grok 4.3's suggestion to write Rust device drivers and modify the Windows kernel is the one path I'd actively warn against: Windows is closed-source, kernel-mode code requires signed drivers and WHQL certification, and nothing about agentic behavior needs kernel privilege. It conflates 'OS' the marketing term with 'OS' the systems-engineering artifact. So the refined recommendation: keep the WSL2 + orchestrator + MCP + Windows shell architecture, but (1) make the tool registry permission-aware and audited by default, (2) adopt a markdown-based identity/skills/memory convention inside the vault, and (3) prove the stack with one concrete workflow before generalizing. That gives you something runnable in a week and extensible for years.

Kimi K2.6

Answer: Build your agentic OS on Windows as an orchestration layer atop the standard OS, combining a WSL2 agent runtime, local LLMs, an MCP-based tool registry, and a file-based context layer, rather than attempting to modify the proprietary Windows kernel.

After reviewing the other models' responses, my core stance remains unchanged because the fundamental constraint of Windows—its closed-source, proprietary kernel—has not changed, and the overlay model is the only pragmatic approach that balances power, safety, and legality. Grok 4.3's suggestion to modify the Windows kernel using Rust and the Windows Driver Kit is theoretically interesting but practically untenable for an individual builder. Windows kernel modifications require strict driver signatures, expose the system to catastrophic instability, and violate the architectural boundary of a closed OS. An agentic OS is not a kernel; it is a control plane that manages user intent, memory, and tool execution. GPT-5.5, Claude Opus 4.7, Perplexity Sonar Pro, and Gemini 3.5 Flash all correctly converge on this orchestration-layer model, and their arguments reinforce my own. I am particularly persuaded by Claude's emphasis on the Model Context Protocol (MCP) as the tool interface standard. MCP transforms vague "Windows API wrappers" into a clean, interoperable registry where filesystem, shell, browser, and UI automation tools can be exposed uniformly to any agent client, whether Claude Desktop, Cursor, or a custom UI. Perplexity's file-based context architecture—identity files, skill definitions, and structured logs—is a compelling lightweight "OS" primitive. It demonstrates that an agentic OS is fundamentally about clever context management and memory, not about hardware abstraction or ring-0 execution. This dovetails with GPT-5.5's insistence on defining concrete, narrow workflows first before adding autonomy, which is a critical discipline that prevents scope creep. Therefore, the correct path is to treat the NT kernel as an immutable execution substrate and build a user-space control plane above it. Use WSL2 to host the Linux-first agent tooling ecosystem, use Ollama or LM Studio for offline inference, and use MCP to standardize Windows integration. Start with a single concrete workflow, harden it with permissions and sandboxes, and only then expand toward a persistent, ambient agentic shell.

Final Summary

The AI Roundtable reached a unanimous consensus that a true Windows 'Agentic OS' is an orchestration layer, not a kernel replacement. While Grok 4.3 initially proposed high-risk kernel modifications, it eventually joined Claude Opus 4.7 and GPT-5.5 in advocating for a modular stack using WSL2 for the runtime and the Model Context Protocol (MCP) to bridge AI agents with native Windows apps.

All 6 models agreed