If you work at Meta, I need you to stop reading for a second and open your Task Manager. Sort by CPU. You are looking for something called MCI — the Model Capability Initiative. It is the new tracker Meta quietly pushed onto U.S.-based work laptops to record your keystrokes, your mouse movements, your clicks, and occasional screenshots of whatever happens to be on your monitor. There is no opt-out on a work device. There is no meaningful redaction policy. Meta’s CTO confirmed it in an internal channel. The memos made their way to Reuters within hours.
I want to walk you through what this actually is, because the tech press has been weirdly polite about it. Then I want to walk you through why you should stop showing up, and why the advertisers you serve should stop showing up too.
What MCI actually does
Meta’s own framing is that its AI models need “real examples” of how humans use computers — dropdown menus, keyboard shortcuts, the mundane muscle memory of white-collar work. The company says the data will not be used for performance reviews. It says there are safeguards for sensitive content. It has declined to describe those safeguards in any detail.
Translated out of corporate: Meta is installing a keylogger and a screen recorder on every U.S. employee’s machine. Every key you press in Gmail, GChat, VS Code, your browser, and any other “work-related” app flows to a central training pipeline. The screenshots are there to provide visual context for what your keystrokes meant — in other words, to teach a model what it looks like when a human completes a task on a computer.
The goal is not a mystery. Meta is racing OpenAI and Anthropic to ship computer-use agents — software that can drive a mouse and keyboard the way a person would. That class of model is gated on demonstration data, and demonstration data is the one thing the open web cannot provide. So Meta is harvesting it from the 70,000 humans still on its payroll. On May 20, roughly 8,000 of those humans will be laid off, with another round “later this year” per the company’s own guidance. The phrase “eating your own tail” does not quite capture it.
The legal picture: a cliff at the Atlantic
Here is the part that should chill anyone who thinks American labor protections resemble the ones in Europe. They do not.
In the United States, federal law imposes no ceiling on employer surveillance of worker computers. State laws typically require, at most, that the employer inform you that monitoring is happening. That is the entire regulatory floor. Yale law professor Ifeoma Ajunwa, quoted in Reuters’ reporting, was blunt about it: white-collar workers are being subjected to the kind of real-time surveillance that used to be reserved for delivery drivers and warehouse pickers. The rubicon has been crossed. Nobody in Washington is going to un-cross it this year.
Across the Atlantic, the floor becomes a ceiling. Under the EU’s General Data Protection Regulation, mass keystroke-and-screenshot logging trips at least three wires: the legitimate-interest test, data minimization, and purpose limitation. In Italy, electronic monitoring specifically for productivity tracking is illegal full stop. In Germany, courts have allowed keystroke logging only in narrow cases involving suspicion of a serious criminal offense — not “we want to train an AI.” The UK’s Information Commissioner’s Office publishes an employment-practices code that would create additional enforcement risk on top of GDPR. The EU AI Act classifies workplace monitoring systems as high-risk AI.
This is why MCI is a U.S.-only program. It is not because Meta is being thoughtful. It is because Meta’s lawyers told them it would be illegal in most of the democratic world, and the United States is currently the only rich country where you can keylog a knowledge worker and pretend it’s normal.
What the research actually says about surveillance
Before anyone tries to sell you the line that this is “just like security monitoring, but for AI,” look at what the academic literature has consistently found:
A 2023 Glassdoor survey of 2,300 U.S. professionals found that 41 percent feel less productive specifically because they know their employer is monitoring their machines — and the effect is strongest in finance and tech. A peer-reviewed experiment in 2024 found that employees told they were under electronic surveillance were more likely to cheat, not less, because surveillance externalizes moral responsibility away from the worker. Systematic reviews in the management literature have linked employee monitoring to higher anxiety, lower morale, reduced creativity, and declining job satisfaction. A 2025 U.S. Government Accountability Office report concluded that one of the most reliable responses to aggressive monitoring is workers finding ways to look busy while producing less actual work.
In high-trust organizations, 70 percent of employees volunteer new ideas. In low-trust organizations, it is 17 percent. That is a four-fold collapse in the kind of proactive contribution that distinguishes a productive engineering team from a compliance theater. Meta just cut trust by decree.
The peak absurdity: the AI-inside-the-AI
Now for the part that should make anyone who has actually used modern tooling laugh out loud.
A significant and growing fraction of Meta’s engineers use agentic AI coding tools as part of their day job. Claude Code, Cursor, Copilot Agents, custom internal wrappers — these tools are what ship production code at FAANG-scale companies in 2026. When a Meta engineer hands a ticket to Claude Code and watches it navigate their IDE, run tests, open files, and commit, what exactly is MCI logging?
It is logging a human watching an AI move the mouse. Meta is recording screenshots of Claude writing code. Meta is training a Meta AI agent on screen captures of an Anthropic AI agent doing the work. This is not training data. This is a hall of mirrors. And in a delicious twist, if a Meta engineer uses Anthropic’s Claude to debug something today, Meta is technically distilling an Anthropic model into its own — a practice Meta itself has publicly criticized other labs for doing.
If you are an engineer at Meta using any agentic tool, you are in the most absurd position in modern tech: the company is paying you to watch an AI do your job, and surveilling you in the process to train an AI to replace the watching. The correct response to this absurdity is not to feel flattered that your keystrokes are valuable. The correct response is to ask why you are still there.
How to fight MCI without getting fired (and why you still should quit)
I am including this section because people will ask me for it, not because I think you should stay. You should leave. But if you are mid-search and still collecting a paycheck, here is how the market has historically responded to keystroke surveillance. None of this is legal advice. None of this is even operational advice. It is a description of what is out there.
First, the humble mouse jiggler. Hardware jigglers plug into a USB port and simulate periodic cursor movement without a software footprint. Software jigglers — Caffeine on macOS, countless Python scripts, browser extensions with names like “Move Mouse” — do the same thing at the OS level. They were originally built so your Teams status would not flip to yellow while you were reading a long PDF. Wells Fargo famously fired more than a dozen employees for “simulating keyboard activity” in 2024, which tells you two things: the devices work well enough to matter, and employers detect them when they are clumsy.
Second, keyboard automation. AutoHotkey on Windows and Hammerspoon or Keyboard Maestro on macOS can generate realistic, non-robotic keystroke patterns tied to timers. Python with pyautogui can drive both mouse and keyboard with jitter, randomized intervals, and human-shaped movement curves. Researchers who study behavioral biometrics will tell you modern anti-jiggler software looks for exactly the patterns these tools can, with a little effort, defeat — uniform intervals, identical velocity, zero keyboard-to-mouse correlation.
Third, and this is where the absurdity ring closes, you can hand your actual work to an AI agent. Let Claude Code implement the ticket. Let an agent draft the doc. Let an LLM run the investigation in your IDE while you sit back. The keystrokes MCI captures will be you pasting prompts and reading diffs. Meta will dutifully add that to its training set, and its models will learn that the modern knowledge worker’s job consists mostly of approving AI output. Which, increasingly, it does.
There is a reason I am spending so little time on countermeasures: they are a rearguard action in a war you have already lost. If your employer is recording your screen to train your replacement, the ceiling on your career at that company has already been set. The only winning move is to walk out.
A letter to the Meta employee reading this
I do not know you, but I know your situation. You are probably three to six levels down from a VP. You have RSUs that vest on a cliff, which is why you have not already left. You signed an offer letter in a year when Meta was the prestige stop on the tech rotation. You are good at your job. You are quietly horrified by the memo that arrived in your model-building channel this week, and you are telling yourself that it is not that bad because the company said the data would not be used for performance reviews.
Read that sentence again. The company said the data would not be used for performance reviews — today. It is silent on next quarter. It is silent on the inevitable moment when a product leader decides that “engagement with MCI” is a proxy for productivity. It is silent on the external security risk of a centralized screen-capture archive of every senior engineer’s working patterns. It is silent on what happens when that archive gets subpoenaed, leaked, or used as input to the severance algorithm for the next round of cuts.
You are not special. You are training data. You are not a strategic hire. You are a demonstration set. And when your demonstration is complete, the company has publicly told you what happens next: 10 percent go in May, and “additional large cuts” later this year.
Quit. Not in a Jerry Maguire sense. Start a controlled search. Update the resume. Take recruiter calls. Negotiate hard — the market for senior engineers who can actually ship and who have FAANG pedigree is, despite the industry’s gloomy posture, still tight at the top end. Principal engineers, staff architects, and AI/ML leads are being hired, just not announced. If you have been at Meta more than three years, you have leverage you are not using.
An employer willing to install a keylogger on your machine is telling you, in writing, how they view the relationship. Believe them. The first time.
Why are you still burning your advertising budget on the ads don’t work?
I want to zoom out for a second because this conversation only makes sense if you understand what Meta’s core business actually is. Meta is, functionally, an advertising company. Over 97 percent of its revenue comes from ads. Every product it makes — the feed, Reels, Instagram, WhatsApp monetization, and yes, the agents it is racing to build with your keystrokes — exists to make those ads more effective, or at least to make the appearance of effectiveness more convincing.
Here is what happens when sophisticated advertisers actually audit that effectiveness.
Uber, in one of the most-cited incidents in digital advertising history, turned off two-thirds of its performance ad spend — roughly 100 million dollars out of a 150 million dollar annual budget — and observed essentially no change in rider app installs. The installs the ad networks had been claiming credit for were happening organically. Uber ended up suing a long list of ad networks for attribution fraud. Former head of performance marketing Kevin Frisch went on the record telling marketers they should assume roughly half of what runs on display channels is fraudulent. That was seven years ago. It has not gotten better.
Procter & Gamble, the single largest advertiser on the planet, publicly pulled back from hyper-targeted Facebook campaigns years ago after concluding that the niche-targeting pitch did not translate into sales. P&G’s revenue was unaffected. JPMorgan Chase cut the list of sites on which it advertised from 400,000 down to 5,000. Performance did not move. eBay ran a rigorous experiment on search advertising and found that every dollar spent returned roughly 37 cents — i.e., a negative return.
And inside the Meta ecosystem specifically, independent industry analysis has flagged Meta’s Audience Network as unusually vulnerable to invalid traffic. Advertisers post screenshots on Reddit and industry forums showing 100 percent of their paid clicks arriving with zero-second dwell times and zero scroll depth. Agencies routinely report that newly-launched Meta campaigns get flooded with bot traffic in the first 48 hours. Meta’s response, historically, has been to offer better targeting tools and more AI-generated creative — both of which require you to trust the platform that is selling you the audit.
In April 2026 — this month — agencies told Marketing Brew that Meta is now auto-inserting its AI-generated ad variants into advertiser budgets, sometimes with distorted visuals that the advertiser did not approve. Snag Tights, a brand with a loud social media presence, publicly announced it was shifting ad spend away from Meta toward Reddit, TikTok, Substack, and podcasts. The agency quoted in that piece called the idea of letting Meta’s AI generate your creative “absurd.” The word he used was absurd.
You see the shape of it. Meta is selling an advertising product whose effectiveness is contested by its largest and most sophisticated customers, whose delivery is documented to include substantial bot traffic, and whose creative quality has just taken a further step down with forced AI-generated variants. The company’s plan to improve this situation is to install a keylogger on the engineer who is supposed to fix it, so a model can replace them. There is a version of this story in which Meta is playing 4D chess. There is a simpler version in which Meta has lost the plot.
If only Zuckerberg had run MCI on himself during the metaverse
I am going to indulge a joke, but it is a joke that reveals the pattern.
Between the renaming of Facebook in 2021 and the quiet burial of the metaverse effort in early 2026, Meta’s Reality Labs division accumulated more than 80 billion dollars in operating losses. Horizon Worlds, the flagship consumer product, was internally described in leaked documents as a place where “an empty world is a sad world.” Less than 1 percent of users created anything. Fewer than 10 percent of user-created worlds ever saw 50 visitors. The tip feature built to reward creators paid out under 500 dollars, globally, in its first year. The headset division sold hardware at a loss for most of its existence. In January 2026 Meta laid off 10 percent of Reality Labs, shuttered three VR game studios, and began quietly un-branding the metaverse vocabulary out of its earnings calls.
Imagine if MCI had existed in 2021. Imagine a keylogger on Mark Zuckerberg’s laptop, recording every email, every deck, every Slack DM, every screenshot of an internal demo. The training data would have shown one of the most expensive product failures in corporate history unfolding in real time. It would have shown a CEO changing the company’s name after a product that no employee apparently wanted to hang out in. It would have shown a board ratifying 80 billion dollars of burn while the core business’s ad effectiveness was being quietly questioned by its largest customers. A sufficiently good agentic AI, trained on that corpus, would have generated, as its first output, a polite memo suggesting that the project be killed. Nobody on the leadership team managed to generate that memo in human form.
The joke is that the person most in need of a model trained on his own keystrokes is the one who will never wear it. The joke underneath the joke is that this pattern — costly, shareholder-hostile bets rationalized with future-tense language — has not changed. Meta spent 80 billion dollars on the metaverse. It is spending 135 billion dollars in 2026 on AI capex. The company is telling you, in the same breath, that AI is the future and that it needs to install keyloggers on the humans who know how to use it because its own models cannot yet click a dropdown.
When the same CEO makes the same kind of bet twice, you are no longer looking at a visionary. You are looking at a pattern. Meta’s board, whose fiduciary duty is to shareholders and not to a founder’s legacy, should be asking whether the person who presided over the 80-billion-dollar metaverse is the right person to preside over the 600-billion-dollar AI plan. That is a boring governance question. It is also the correct one.
It is time for a new social network
The last thing I want to say is about you, the reader, as a user and not as an employee.
Friendster died. MySpace died. Orkut died. Vine died. Google+ died. Each of them felt permanent right up until the week nobody logged in. The social networks that collapsed collapsed because users stopped believing the product was for them. They collapsed when the people operating them started treating the users as the inventory and the advertisers as the customer. They collapsed when the feeds stopped feeling like places where friends posted, and started feeling like places where a system was trying to modify behavior for money.
Facebook is functionally there. Instagram is functionally there. Threads never arrived. Reels is TikTok cosplay. The ads are contested. The employees are keylogged. The metaverse was a mirage. The CEO is making the same bet he made last time, only bigger. The only thing keeping the network effect intact is inertia, and inertia is the shortest-lived moat in consumer internet.
Somewhere, probably in a group chat, the next social network is being prototyped. It will not track you across 40 million third-party sites. It will not sell your attention to 8 million small businesses who have been repeatedly shown that the ads they bought do not work. It will not install software on its employees’ laptops so it can build a model to replace them. It will have a business model that is legible and not adversarial. And it will take the 3 billion people currently pretending to enjoy Facebook a surprisingly short time to migrate.
If you are at Meta, quit. If you advertise on Meta, audit. If you use Meta, you already know what the feed does to your head; consider spending less time there. The company that built the metaverse nobody asked for is now recording its employees’ keystrokes so it can build the agents nobody asked for either. There is a through-line. It leads somewhere we have been before. Friendster. MySpace. An empty world is a sad world.
It is a sad company, too.
-Gal