The Hallucinated OS: How VibeOS Turns AI Guesses Into a Working Computer

Steve Sanderson stepped onto the stage at Microsoft Build this month and introduced the world to what he called the first completely hallucinated operating system. The audience erupted in laughter. Yet the demonstration that followed was no mere joke. It was a pointed commentary on the current frenzy around AI agents and the lengths developers will go to push large language models into unexpected territory.

VibeOS, accessible at vibeos.sh, bills itself as the first AI-native operating system. From hardware to user interface, Anthropic’s Claude controls everything. Users type natural language prompts. Apps, widgets and even entire interfaces appear instantly. No traditional coding required. The site promises that simple instructions transform into functional applications right on screen.

But dig deeper and the picture grows more complex. One version of VibeOS, built by university student Kaan Şenol, is a genuine hobby operating system targeting ARM64 processors. It runs on QEMU emulators and a real Raspberry Pi Zero 2W. The entire codebase emerged from 64 collaborative sessions with Claude. Session logs sit in the public GitHub repository at github.com/kaansenol5/VibeOS. The README states plainly, “A hobby OS vibecoded completely from scratch with Claude Code. Not everything works, some stuff is not even tested, but most things do.”

Şenol’s creation includes a custom kernel with cooperative multitasking, a FAT32 filesystem, interrupt handling, a macOS-inspired graphical desktop, a basic TCP/IP stack with TLS support, a web browser, a terminal, a VibeCode IDE, and even a port of Doom. It ships with Tiny C Compiler and MicroPython. The student documented every prompt and response. This is not simulation. It boots. It executes real code.

Contrast that with the version that stole the show at Microsoft Build. Presented by Sanderson, this VibeOS takes the concept to an extreme. There is no underlying code for most applications. Launch the calculator and Claude, paired with a kernel agent, generates the visual interface on the fly. Type in an equation. The model guesses the answer and draws it in the results field. Accuracy is optional. As Cameron Coward explained in Hackster.io, “It isn’t like using a calculator, it is like telling Gemini ‘draw me a picture of a calculator program showing the square root of 16’ and hopefully the AI will put a ‘4’ into the results area of the UI it scribbled on the screen.”

The same principle applies across the system. Request a browser and the model fabricates a webpage complete with invented text. Ask for Excel and it renders a spreadsheet-like interface that mimics behavior without performing actual calculations. Fictional programs receive the same treatment. The OS will happily simulate software that has never existed. Everything is generated in real time based on the model’s training data and the user’s prompt.

And. It works. Sort of. The demonstration runs in a virtual machine. Users can spin up their own copy through Docker. The online demo at vibeos.sh offers a quick taste, though reviewers report occasional failures. Utilities bundled with the project extend its reach. One tool called daedalus lets the system tap into external model context protocols without installation. Another, onkernel, allows normal browser use until the user hands control to the AI agent. A dedicated browsing agent handles background tasks.

Mark Russinovich shared the YouTube recording on LinkedIn and praised its humor and insight. The session, titled “Scott and Mark Learn to… Vibecheck,” pitted hand-crafted projects against those entirely generated by AI. Judges had to guess which was which. Sanderson’s entry fooled many and left the room in stitches. Yet the underlying idea resonates. Developers already spend hours coaxing models to produce code. Why not let the model run the entire machine?

Critics were quick to label it slop. Reddit threads in r/LocalLLaMA dismissed it as a “fully hallucinated operating system” and a “sloperating system.” One commenter joked it runs natively on “slopbook pros.” The term “vibe coding” has entered the lexicon, often with derision. It describes the practice of describing desired behavior in loose, conversational terms and accepting whatever the model produces. Results vary. Determinism evaporates.

Still, the project exposes real questions. Traditional operating systems rely on precise, hand-written code that behaves consistently. Memory allocation, process scheduling, file permissions — all follow strict rules. Replace those with probabilistic model outputs and predictability disappears. A button might move. A menu could vanish. The calculator might return 5 instead of 4 on Tuesday. Is that a bug or a feature?

Security takes on new meaning too. If the kernel itself depends on model inference, what prevents malicious prompts from rewriting system behavior? Privacy concerns multiply when every action feeds into an LLM. Performance costs rise as well. Real-time inference demands dedicated hardware accelerators. Power consumption changes. Debugging becomes an exercise in tracing token probabilities rather than stack traces.

Şenol’s more traditional effort proves the middle ground has value. His OS combines real code with AI assistance. The kernel is deterministic. Applications run compiled binaries. Claude simply accelerated development. The student achieved networking, graphics and even Doom in a fraction of the time a solo developer might otherwise require. That model of collaboration appears sustainable. The fully hallucinated approach shown at Build feels more like performance art.

Yet both point toward the same horizon. AI is no longer content to sit inside applications. It wants the entire computing stack. Microsoft has poured resources into Copilot. Anthropic continues to improve Claude’s agentic abilities. Open-source projects experiment with local models that could one day run these systems offline. The barrier between prompt and execution shrinks daily.

Early reactions on X ranged from amusement to alarm. One user called it “purely design provocation, not a usable product.” Another wondered how many nested hallucinated operating systems one could run before the simulation collapsed. TempleOS received honorable mention as an earlier example of divinely inspired, if not AI-driven, system software.

The vibeOS.sh project itself remains something of a living document. It mixes real technical demonstrations with conceptual exploration. Docker images let enthusiasts boot their own copies. The site showcases widgets that display real-time data, mini-games created from single sentences, and news summaries generated on demand. These features work because behind the scenes some code still exists. The magic is selective.

Industry insiders have seen similar cycles before. Hypervisors once seemed exotic. Container orchestration looked like overkill until it wasn’t. Each wave of abstraction traded fine control for developer velocity. VibeOS asks whether the next abstraction layer should be probabilistic. Can an operating system remain useful if its responses carry uncertainty? Or does the value lie in forcing humans to verify every output?

Sanderson’s presentation succeeded because it made the absurdity visible. A computer that guesses its way through basic arithmetic forces viewers to confront how much trust they already place in black boxes. Most users cannot audit the code inside their calculators any more than they can audit a language model’s weights. The difference is transparency. VibeOS admits it is guessing. Conventional software pretends at certainty.

Where this leads remains unsettled. Some developers will extract practical techniques from the experiment — better prompt patterns, tighter integration between agents and system calls, novel user interfaces that adapt instantly. Others will treat it as a cautionary tale about over-reliance on generative models. A few will fork the code and push the idea further, perhaps grafting real execution engines behind the generated facades.

For now VibeOS stands as both technical achievement and cultural artifact. It captures the giddy, slightly unhinged spirit of 2026’s AI summer. Students build real kernels with model help. Keynote speakers unveil operating systems with no code. Audiences laugh, then pause to consider whether the future just walked onstage wearing a disguise. The hallucination, it turns out, can boot.