Every company’s AI workflow rn be like 😭💀

Yesterday Meta told every US employee their computer will now record mouse clicks, keystrokes, and screenshots while they work. All of it goes into training an AI to do their job. In 30 days, 8,000 of these same employees are being laid off. Reuters got the memo. The wording is the company's own: the recordings will be used to build "AI agents that can perform work tasks autonomously." Reuters also confirmed the May 20 date and the number, 8,000 people, exactly 10% of Meta's global workforce. Meta is spending $115 to $135 billion on AI infrastructure this year, almost double the $72 billion it spent last year. The entire business only generated $115.8 billion in cash for all of 2025. Meta is now planning to spend more on AI in 2026 than the whole company brings in. Part of the bill went to a company called Scale AI. Meta paid $14.3 billion for 49% of it last June, mostly to bring in CEO Alexandr Wang. Scale's whole job is to tag and clean the human-written data that AI models learn from. Meta wanted Wang because their old data supply ran dry. The public internet is almost out of fresh material to feed these models. A group called Epoch AI ran the math and projects the world will burn through its supply of high-quality human-written text on the web somewhere between 2026 and 2032. The industry calls this the "data wall." Google and OpenAI are stuck on the same side of it. So Meta turned inward, to the most expensive training material money can buy: their own employees doing their own jobs. Mouse movements teach the AI how to move around a screen, click by click. Keystroke logs hand it the exact shortcuts and rhythm an experienced worker uses, the muscle memory of the job. Screenshots show what a finished task should look like. The people being recorded in April are the raw material for the AI that replaces them in May. This is not just a Meta thing. Amazon laid off 16,000 corporate workers in January. Oracle let go of up to 30,000 of its people, about 18% of the company, on March 31. The cash they saved goes toward $156 billion in AI data centers. The whole pattern across big tech is identical. Record profits and record AI spending, paired with the biggest workforce cuts since the pandemic. The thing they are building is a software worker that opens the dashboard, reads the numbers, drafts the email, books the meeting, and never needs a coffee break. The training data for that worker is a senior Meta employee doing all of that, on Meta's payroll, one month before their last day.

AMAZON'S AI AGENTS ARRIVE: THE END OF DEVOPS JOBS? If AI manages the cloud, is the human sysadmin obsolete? #AINews Imagine an employee who never sleeps, never makes a typo, and fixes your cloud servers before you even know they're broken. Amazon just built him.

Amazon is holding a mandatory meeting about AI breaking its systems. The official framing is "part of normal business." The briefing note describes a trend of incidents with "high blast radius" caused by "Gen-AI assisted changes" for which "best practices and safeguards are not yet fully established." Translation to human language: we gave AI to engineers and things keep breaking? The response for now? Junior and mid-level engineers can no longer push AI-assisted code without a senior signing off. AWS spent 13 hours recovering after its own AI coding tool, asked to make some changes, decided instead to delete and recreate the environment (the software equivalent of fixing a leaky tap by knocking down the wall). Amazon called that an "extremely limited event" (the affected tool served customers in mainland China).

Goldman Sachs is rolling out Anthropic’s AI model to automate accounting and compliance roles completely. Anthropic engineers have been embedded at Goldman for 6 months, co-developing systems that act like “digital co-workers” for high-volume, process-heavy tasks. The new setup uses an LLM-based agent that can read large bundles of trade records and policy text, then follow step-by-step rules to decide what to do, what to flag, and what to route for approval. Goldman says the surprise was that Claude’s capability was not limited to coding, and that the same reasoning style worked for rules-based accounting and compliance work that mixes text, tables, and exceptions. The bank expects shorter cycle times for client vetting and fewer lingering breaks in trade reconciliation, and slower headcount growth rather than immediate layoffs. --- cnbc .com/2026/02/06/anthropic-goldman-sachs-ai-model-accounting.html