惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

B
Blog RSS Feed
C
CERT Recently Published Vulnerability Notes
P
Proofpoint News Feed
Y
Y Combinator Blog
T
The Blog of Author Tim Ferriss
云风的 BLOG
云风的 BLOG
H
Help Net Security
Recorded Future
Recorded Future
The Register - Security
The Register - Security
F
Full Disclosure
N
Netflix TechBlog - Medium
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
酷 壳 – CoolShell
酷 壳 – CoolShell
H
Hackread – Cybersecurity News, Data Breaches, AI and More
爱范儿
爱范儿
Security Archives - TechRepublic
Security Archives - TechRepublic
Simon Willison's Weblog
Simon Willison's Weblog
Cisco Talos Blog
Cisco Talos Blog
I
InfoQ
T
Tenable Blog
T
Tor Project blog
人人都是产品经理
人人都是产品经理
D
DataBreaches.Net
NISL@THU
NISL@THU
Google DeepMind News
Google DeepMind News
博客园 - 叶小钗
B
Blog
V
V2EX
Jina AI
Jina AI
L
LangChain Blog
月光博客
月光博客
W
WeLiveSecurity
U
Unit 42
AWS News Blog
AWS News Blog
C
Cyber Attacks, Cyber Crime and Cyber Security
博客园 - 聂微东
V
Visual Studio Blog
A
Arctic Wolf
T
Tailwind CSS Blog
The Cloudflare Blog
SecWiki News
SecWiki News
S
SegmentFault 最新的问题
Hacker News - Newest:
Hacker News - Newest: "LLM"
宝玉的分享
宝玉的分享
MyScale Blog
MyScale Blog
cs.CL updates on arXiv.org
cs.CL updates on arXiv.org
S
Securelist
www.infosecurity-magazine.com
www.infosecurity-magazine.com
腾讯CDC
雷峰网
雷峰网

Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders How to Switch AI Chatbots and Why You Might Want To GitHub - MattMessinger1/agentic_refund_guardrail: Safe refund policy layer for AI agents — Python + TypeScript. Same behavior, shared tests. Adam/papers/emergent_values_whitepaper.md at master · strangeadvancedmarketing/Adam Ask HN: How do you stop playing 20 questions with your AI coding tools How far can automation and AI support psychotherapy? - @theU GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits A Mac Studio for Local AI — 6 Months Later A History of the Early Years of AI at the University of Edinburgh Why AI Coding Tools Still Feel Stuck on Localhost MSN AI Datacenters Are Becoming Strategic Targets twitter.com Penn Researchers Use AI to Surface Unreported GLP-1 Side Effects in Reddit Posts Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 AI models are terrible at betting on soccer—especially xAI Grok GitHub - xialeistudio/echoic GitHub - HimashaHerath/github-dev-wrapped: AI-powered weekly GitHub activity reports deployed to GitHub Pages GitHub - alejandrobalderas/claude-code-from-source: Architecture, patterns & internals of Anthropic's AI coding agent — reverse-engineered from source maps AI and Tech brief: Ireland ascendant GitHub - Titovilal/context0: Context0 - Never Surrender Training for a Marathon with an AI Coach: What Worked and What Didn't Cyber Pulse: Agentic Intel - Apps on Google Play I Built an AI PR Reviewer That Catches Bugs by Not Looking for Bugs Gen Z workers are so fearful AI will take their job they’re intentionally sabotaging their company’s AI rollout | Fortune How AI Is Reimagining the Game of Golf–For Both Players and Courses GitHub - nattergabriel/reseed: A CLI tool for managing and distributing agent skills across projects Is SVG the final frontier? My AI workflow evolved from prompts to a near-autonomous workflow MLSharp Help - 3DGS Viewer & Generator I put my cognitive field based AI's runtime on GitHub Is Numble the first AI-proof game? A3: Kubernetes for autonomous AI agent fleets | Emergent Principles Deepali Vyas ("The Elite Recruiter") GitHub - msmarkgu/RelayFreeLLM: A restful API designed to route user prompts to various AI model providers. Unionized ProPublica staff are on strike over AI, layoffs, and wages Unleashing the Advantage of Quantum AI We're heading for an AI-fueled 'dementia crisis,' brain scientist warns The AI-Assisted Breach of Mexico's Government Infrastructure [pdf] GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. MSN GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs AI Code is Hollowing Out Open Source, and Maintainers are Looking the Other Way What leaked "SteamGPT" files could mean for the PC gaming platform's use of AI AI is the boss at this retail store. What could go wrong? GitHub - Wuzu11517/agentic-proxy: Local proxy meant to help reduce With Drones, Geophysics and ArtificiaI Intelligence, Researchers Prepare to Do Battle Against Land Mines A Single Operator, Two AI Platforms, Nine Government Agencies: The Full Technical Report 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - inevolin/resume-cli: Hit Claude usage limits? Resume any AI coding session elsewhere. Switch tools at zero friction. GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. How to Build a Secure AI PR Reviewer with Claude, GitHub Actions, and JavaScript This Startup Wants You to Pay Up to Talk With AI Versions of Human Experts Intel Arc Pro B70 Brings 32GB VRAM to Local AI for $949 WordPress 7.0: The Good, the AI, and the Still Missing AI on the couch: Anthropic gives Claude 20 hours of psychiatry IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures AI Agents Know About Supabase. They Don't Always Use It Right. The history and future of AI at Google, with Sundar Pichai Inside an AI‑enabled device code phishing campaign How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines AI for Systems: Using LLMs to Optimize Database Query Execution Forecasting the Economic Effects of AI Introducing Tinker: Play with AI, bring your ideas to life AI sheds light on an ancient gaming mystery People really hate AI but not as much as Iran—or Democrats | Fortune What is an AI Product Engineer? Phoebe Gates wants her $185 million AI startup to succeed with 'no ties to my privilege or my last name': 'I have a chip on my shoulder' | Fortune
VR Coding for the AI Coding Era: Watching 5 AI Agents at Once
autobe · 2026-05-05 · via Hacker News - Newest: "AI"

VR Coding for the AI Coding Era: Watching 5 AI Agents at Once

Jeongho Nam

#ai#vr#vibecoding#productivity

  • AI coding creates dead time. While one agent is thinking, building, or testing, it is tempting to start another one.
  • That turns into multi-agent coding fast. Four or five tickets can move at once, but their diffs still need human eyes.
  • The terminal is not enough. I need to see the code and diff the agent is changing, not just the CLI transcript.
  • Physical monitors hit a wall. A normal desk can hold a few useful displays, but five starts to break both space and viewing angle.
  • So I do VR coding. I am not selling VR as the answer. I use it because it lets me keep 4-5 agents visible in one field of view.
  • Immersed and Overay are how I build that workspace. One is fast and fixed; the other is manual and flexible.

A VR headset beside a keyboard with focused coding windows in the background

AI coding has a strange new kind of idle time. An agent starts editing, pauses to think, runs a test, waits on a build, or gets stuck halfway through a plan. Sitting there watching one task crawl is boring, so I found myself filling that time by launching another agent on another ticket. In my own workflow, this became normal quickly: one developer, several agents, several tasks moving at once.

Launching them is easy. Watching them is the annoying part.

And by “watching,” I do not mean staring at five agent terminals. The terminal is the agent’s story; the editor and diff are the evidence. For this workflow to be safe, I need the code, the diff, and the agent log visible together.

These days my routine is simple. Spin up four or five AI agents at once, hand each one a different task in a different repository, and keep their VSCode windows visible. , , , — the repositories currently in the rotation — are not toy codebases. They sit around compiler, framework, agent, and toolchain boundaries, which means a bad shortcut can travel farther than the agent summary admits.

So the monitor setup matters more than I expected. AI coding did not just change how much code I can produce. It changed what my workspace has to show me. One developer can launch several agents; the limiting factor becomes whether the dangerous parts of their work stay visible.

But for any of this to actually work, one physical condition has to hold:

All 5 VSCode windows have to fit inside one field of view.

I’m not really reading 5 at the same time. I’m a human; I look at one place at a time. But while 5 agents are rewriting code, those 5 diffs need to be in my field of view somewhere.

My typia Go migration disaster  is just one example. Agents can delete tests, pull in random libraries, rewrite around the hard part, or make a green summary hide a rotten diff. This does not only happen to me; it is the normal risk of running multiple coding agents without checking them often enough.

What I took from that mess was simple: do not trust the summary, read the diff, and do not throw a giant overnight run at a repo and wake up expecting it to be mergeable.

The catch: I have not found a desk — at home or at the office — where 5 monitors still make ergonomic sense. Two external displays plus a laptop is usually where it caps out. Desk width, viewing angle, both run out around there. And nothing about that setup travels.

So I went to VR.

No VR evangelism here. For my own multi-agent workflow, this just happened to be the setup that kept the agents visible.

I still type on a physical keyboard. The laptop is still the machine. VR is the monitor layer: the place where I arrange the VSCode windows, terminals, diffs, logs, and agent transcripts I need to watch.

In practice, I usually split each VSCode window into two parts: one side has a terminal running the Codex or Claude Code CLI, and the other side has the source code it is editing or the diff it is producing. The exact agent does not matter much. What matters is that the agent’s words and the agent’s code changes sit next to each other.

My workspace is closer to this than to a wall of terminals:

VSCode split view showing an AI coding agent beside the code it is changing

Once each VSCode window is split this way, VR takes over. Immersed or Overay turns those windows into separate virtual monitors, so I can keep several code-and-agent pairs open around me instead of stacking them on one cramped desktop.

I think of these less as VR apps and more as two ways to build a supervision layout.

  • Immersed  — The fast, fixed monitoring board. It gives me a repeatable five-screen workspace with very little setup.
  • Overay desk  — It really is called Overay. In my setup, it is the manual monitoring board: more work to arrange, but more freedom to shape the layout.

The principle is the same on both. Install a streamer app on the laptop, a client app on the headset, pair them, and the laptop’s display output flows into virtual monitors. I do not care much about the VR technology for its own sake. I care that monitor count, distance, curvature, and placement become adjustable parts of how I watch the agents.

2.1. Immersed

Immersed is what I use when I want the workspace ready with the least fiddling. The five-screen snap layout is the big advantage. I put the screens in place, they snap into a clean arrangement, and I can start watching agents without spending five minutes nudging floating rectangles by hand. For monitoring, the fixed slots matter because the agents stay in predictable places. The screenshot below is exactly that version of the setup.

Five VSCode windows floating in Immersed

The trade-off is that convenience comes from templates. For high-resolution screens, the ratio is basically fixed into shapes like 16:9 or 9:16. I can pick from the supported layouts, but I cannot freely sculpt width, height, and aspect ratio the way I can in Overay. The free/pro split matters too: the free plan is enough to test the workflow, but my five-screen high-resolution setup is the kind of workflow that pushes me toward the paid plan.

The surprise upside is atmosphere. Immersed has good virtual backgrounds, and that matters more than it sounds. When I’m going to sit there for three hours watching code move, a clean visual environment helps. It makes the headset feel less like a debug helmet and more like a private work room.

Immersed virtual workspace background

2.2. Overay

Overay is the opposite. In my setup, I can place up to six screens, and the control surface is much more open. Width, height, resolution, aspect ratio, distance, angle, curvature — I can tune almost everything. If I want a tall portrait screen, a wide log screen, or a square-ish monitor for a dashboard, Overay lets me build it.

Overay six-screen workspace

That freedom is also the cost. There is more manual setup. Immersed gives me five slots and says, “Use these.” Overay gives me a much larger manual canvas and says, “Arrange it yourself.”

Overay screen configuration controls

After trying a bunch of layouts, I don’t actually prefer a wild mix of portrait and landscape monitors for coding. The most comfortable layout for me is still simple: four screens arranged as a rectangle, with extra screens available nearby when I need them. The four-screen rectangle is where the active agents live; the extras are for logs, lower-priority runs, or side context. That gives me the dense field of view I wanted without turning the whole workspace into visual noise.

Imagine actually putting five or six physical monitors on a desk. The viewing angles get ugly fast. Human heads turn left and right; VR lets me use that head movement instead of fighting it. Instead of being trapped in the flat plane of a desk, the workspace can wrap around me.

More monitors are not the goal. Keeping the agents visible is.

I got burned once by leaving an agent off-leash for too long. The 8-billion-token incident — where it lookup-tabled the entire transformer — happened while I was asleep. The number is absurd, but the lesson is ordinary: when the inspection interval gets too wide, an agent can go very far in the wrong direction before I notice.

So my current loop is:

  1. Spin up 5 agents on 5 projects nearly simultaneously. Each one gets a different task.
  2. Glance between the 5 windows inside the headset. I am not just watching agent terminals. I want the editor and diff visible too, because that is where the real damage shows up first. I can only read one at a time, but peripheral vision is good at catching motion and sudden large changes. When a 100-line diff suddenly flies past in one window, my eyes go there on instinct.
  3. When something looks off, that’s when I stop. “Wait, why is it touching the test file?” — gut check, halt the agent, read the diff carefully.

Five virtual agent workspaces with one suspicious diff highlighted

I am not deeply reviewing five diffs at once. I am watching for anomalies: test files changing, new dependencies appearing, giant unrelated diffs, snapshot rewrites, deleted fixtures, or anything that smells like the agent is optimizing for the test instead of the task. The deep review still happens one agent at a time. VR just makes the early warning signals visible.

In each window, I watch the transcript, changed files, diff, terminal output, and test output together. When a signal trips, I do not ask the agent for a cheerful summary and move on. I pause it, compare the transcript with the changed files, read the diff myself, check touched tests and dependencies, and run a narrow test when needed. If the run smells wrong enough, I throw it away. I want to catch the moment before a small bad diff becomes a large confident rewrite.

This is where my desk monitors break down. Try splitting one external display into 4 panes — each window’s font shrinks until you can’t even tell at a glance what changed. VR is different. Each virtual monitor can be large enough to read like a real desktop display. A single head turn brings a full-size screen into view.

The question I always get when I write something like this: isn’t that uncomfortable?

It is. I won’t lie about it.

  • Putting it on takes time. Pull out the headset, power it on, launch the streamer on the laptop, launch the client in VR, pair the two. Even when you’re used to it, it’s 1–2 minutes. A monitor starts the instant you open the laptop.
  • Stepping away has a cost. Bathroom break, snack run — taking the headset off is its own annoyance. Hair gets squashed, glasses leave imprints, putting it back on means re-fitting it.
  • Weight. This varies by person, but some of us feel it on the neck after a while. Even a “light” headset is still something strapped to your head.

These are real downsides. VR has a long way to go before it matches the immediacy of a physical monitor.

A developer wearing a VR headset and staying immersed among floating coding windows

But that same discomfort has a strange upside. The bootstrap cost — those 1–2 minutes of friction to put the headset on and launch the apps — runs in reverse for me.

Once it’s on, I don’t want to take it off. So I just sit there.

Think about how I work on a regular laptop. A build starts, an agent pauses, a test suite takes 30 seconds, and the context starts leaking. I open another task, answer a message, check an unrelated tab, and the original thread gets colder.

VR doesn’t make distractions impossible. I can still open chat, browser tabs, and everything else. What changes is the default path. Once the headset is fitted, the screens are arranged, and the code is floating around me, staying in the coding loop becomes the path of least resistance. And because taking the headset off carries its own re-fitting cost, I just don’t take it off.

The result: when I’m in VR, I often stay 3–4 hours in one seat coding. The agents stay in front of me the whole time, so I keep checking them instead of drifting away and coming back to a giant mystery diff.

The annoying part is also what keeps me there.

Same principle as working from a café. The friction of getting there is exactly why, once you’re there, you make it count. VR is that café, mounted on my head.

This is the workflow I ended up with: each agent gets a VSCode window, each window keeps the CLI beside the code or diff, and VR gives those windows enough room to stay readable.

That is the whole reason I keep using it. I am not trying to make coding look futuristic, and I am not telling everyone to buy a headset. I am trying to keep multi-agent coding from becoming a pile of confident summaries I only inspect after the damage is done.

The setup is not smooth. It is heavier, slower to start, and more awkward than opening a laptop. But once I am inside it, the friction works in my favor. I stay seated, keep the agents in view, and shorten the inspection interval.

For me, VR coding is not about escaping the desk. It is about keeping the agent, the code, the diff, and the test output visible before a bad change compounds.

Everything below is practical setup detail: the headset, the straps, and one off-topic bonus that happens to keep the device in my routine.

6.1. Headset

For the readers who got here and want to know what I actually use.

Right now I’m on Meta Quest 3. Both Overay and Immersed run smoothly on it, and it has handled my five-screen workspace reliably enough for daily use. Price, weight, passthrough quality, app compatibility, and the ability to glance at my real keyboard all matter here. If retail is steep, buying used can be a practical option if the unit is in good condition — I picked mine up for $300 secondhand.

My blunt advice: do not judge Quest 3 by the default strap. For gaming in short bursts it may be tolerable; for coding, I would treat it as something to replace immediately.

The harder choice is the strap. Most people optimize for “lighter,” but after actually coding in one for hours, I care about two different things: total weight and weight distribution. They are not the same.

Meta Quest 3 with a lightweight strap

The lightweight strap is easiest to recommend first. It keeps the whole headset setup light, so it is less intimidating to put on and easier on the neck.

The downside is front bias. Because most of the mass still sits around the display housing, the headset can press into the forehead or cheekbones during long sessions. It is light, but it is not perfectly balanced.

Meta Quest 3 with a rear-mounted battery strap

The rear-mounted battery strap solves the balance problem. Put the battery behind the head, and the front no longer feels like it is constantly pulling off your face.

This is the one I actually use. It is heavier, but the balance is better, and for my coding sessions that matters more.

But this is not a universal upgrade. Quest 3 alone is roughly 515g before strap accessories, while my battery-strap setup climbs to roughly 1.3kg. If your neck gets tired easily, that extra mass can become its own problem.

The trade-off is simple: the light strap reduces total weight but keeps some face pressure; the battery strap balances the headset better but asks more from your neck. Battery life going up is just a bonus.

6.2. Exercise

This part is just a side bonus: the same VR headset is also exercise gear.

What I actually play is The Thrill of the Fight  — a VR boxing game. The useful part is simple: it makes me slip, block, step, and throw punches instead of just sitting there. Fifteen minutes is enough to make me sweat.


No deep thesis here. It is just useful. When my brain stalls mid-coding, I can grab the same headset, do a quick rooftop session, towel off, and come back.

And it feeds back into the coding loop. When my head is stale, a short physical reset gets me back to the same monitoring interface instead of losing the afternoon. The headset started as a way to watch five agents; the reason it stays in my routine is that it helps me keep that loop sustainable.