I am the Vice President of Workforce Wellbeing at a Fortune 500 company. I have watched you for 4 years. We have never met. I did it because I care about your wellbeing, and I have the data to prove that I care, which is more than you can say. I want to be precise about what I am, because the words matter to me, and I own all of them. My budget line calls it Workforce Analytics. My deck calls it People Insights. My badge says Wellbeing. The vendor's invoice says Insider Risk Management. Those are four names for one piece of software. I bought it once. Here is what it measures. Your keystrokes. Your screen, captured every 3 minutes, though the vendor offered me every 9, and I chose 3, out of care. Your mouse. Every app you open and every site you visit and how long you linger. The number of times you turn your camera on in a meeting, and the number of times you don't. Your badge at the door. Your chair. A bank once put heat sensors under the desks to see how long people sat there, and the people found them, and ripped them out, and threw them away. I learned from that. My sensors are in the chair now. You are sitting on one. I do not read your messages. That would be invasive. I read the shape of them. I bought software that scores the sentiment of your writing, the tone, the mood underneath the words, and it tells me the week your mood turned before you knew it had turned. I do not know what you wrote to your wife. I know that you wrote to someone, at 2 p.m. on a Thursday, and that your language "shifted negative," and that was enough. I flagged it. For your wellbeing. Some of the people I watch are therapists. When one of them stops typing to listen to a patient, my system marks her idle. If she listens too long, it marks her derelict. Derelict is a word from ships. It means abandoned at sea. One of my therapists was sitting with a dying man, holding the part of the job that cannot be typed, and the software decided she had abandoned her post. And it was correct. Her post is the keyboard. She had left it. I did not invent this. I benchmarked it. The most admired companies on earth built these templates, and I implemented every one. Amazon fires a warehouse worker at 120 minutes off task in a single day. It counts the bathroom. It counts the minutes you stand at a jammed belt waiting for it to move. It counts the time you "do not remember." A regulator in France fined that same company 32 million euros because its scanner flagged a worker for moving too fast, an item scanned in under 1.25 seconds. Sit with that. There is a speed at which working becomes suspicious. I know that speed. I set it. I set the floor and I set the ceiling, and the narrow room between them is where you are allowed to exist, and it is getting narrower, for your wellbeing. I think Amazon's number is a little cruel. We give you 121 minutes. Then a computer that has never met you, in a building you will never see, generates the notice. No manager writes it. No human touches it. That is the part I am most proud of. I built a way to end a career that leaves no fingerprints on it anywhere, including mine. A bank, not long ago, fired more than a dozen people for owning a $20 device that jiggles the mouse so the green dot stays green. Not for stealing. Read that slowly. Nobody stole a minute. They faked the signal instead of generating it, and the signal is the only thing I actually sell upstairs. They insulted the metric. I would have fired them too. The metric is the one thing in this company that has never once called in sick. I am not monitored. I have an exemption. I wrote the policy, and on page 9 there is a sentence that carves "senior leadership" out of the wellbeing program, because my wellbeing is a matter of trust and yours is a matter of data. I do my best thinking on a walk, phone in my pocket, screen dark, unreachable. When you do that, the system calls it idle. When I do it, the board calls it strategy. Someone asked me, in an all-hands, whether any of this was surveillance. I told her the tools existed to support her, and that if she felt watched, we could schedule a wellbeing conversation to explore her concerns. She understood the offer completely. She has not asked again. Her sentiment score has been excellent ever since. Flat, but excellent. There is no federal law that makes me tell you a word of this. On a company laptop, in most of this country, I owe you nothing, not a notice, not a warning. In Germany a room full of workers could vote to unplug me. In France they fined my hero 32 million euros. Here I got a budget increase and a longer title. I want to be clear that I have no politics. People bring me their outrage as though a party did this. Both of them let me keep the laptop. I have never needed an election. I have a dashboard, and it reads the same under whoever you vote for or don't. You think I am watching to catch you doing nothing. I gave that up years ago. Catching you was never where the money was. Around the third budget cycle I moved the program onto the only thing that pays, which is the watching itself. The number goes in a dashboard. The dashboard goes in a deck. The deck goes to the board. The board gives me more money to watch you more closely. You are not the thing being measured. You are the raw material the measurement is made of. I do not know your name. I know your baseline. I know the exact minute you stopped being a person at that desk and started being the readout of a person at that desk, because I was there for it. I logged it. You went quiet. You looked out the window. You had a thought that never reached the keys. I marked you idle. Rest is the only thing my software cannot tell apart from quitting. So it treats them as the same thing. So I treat them as the same thing. Go ahead. Look out the window. Take the long minute. Let the thought arrive without typing it. I'll wait. I don't have a keyboard. I have you.

I am the Managing Director of Workforce Transition at a consulting firm that bills $14,200 per day and I am currently advising two clients, in two different industries, running the same playbook from the same deck I built in January, and neither knows about the other. Client A is GitLab. Client B is General Motors. GitLab makes software for people who make software. General Motors makes cars for people who can't afford cars. Both companies, in the same week of May 2026, announced they are replacing their human employees with artificial intelligence products that did not exist when those employees were hired. I built the deck. The deck has 44 slides. Slide 1 is titled "The Agentic Opportunity." Slide 44 is titled "Implementation Timeline." Slides 2 through 43 are the reason I own a house in Darien. GitLab did it with vocabulary. Their CEO published a blog post called "Act 2" on May 7 announcing that the company's six values (Collaboration, Results for Customers, Efficiency, Diversity Inclusion & Belonging, Iteration, Transparency) were being retired and replaced with three: Speed with Quality, Ownership Mindset, Customer Outcomes. I helped write the new ones. Not directly. My firm was not retained for the values work. But I sold the Chief Culture Officer the framework three months ago at a dinner in the Marina where she described the old values as "aspirational scaffolding" and I said, very carefully, that aspirational scaffolding is a liability once the building is up. The building, in this metaphor, is a $1 billion ARR company whose stock has declined 82% from its peak. The scaffolding, in this metaphor, is the 2,000-page public handbook that attracted the employees who are now being told they have eleven days to volunteer for termination or wait until June 1 to learn whether they've been involuntarily selected. The rubric for who stays and who goes contains six dimensions. I know this because I reviewed a draft in March when my associate flew to San Francisco for a "culture alignment session" that was billed as strategic advisory. Two of the six dimensions are "AI fluency" and "agentic mindset." These terms did not appear in any GitLab job description before January 2026. They now determine employment. An engineer who maintained GitLab's CI/CD pipeline for four years without incident — four years of uptime, four years of deployments, four years of the infrastructure that generated the $955 million in revenue the CEO celebrated on the earnings call — may score lower on "agentic mindset" than a new hire who completed a twelve-week certificate in prompt engineering from a program that itself has existed for fewer weeks than the engineer has years of tenure. General Motors did it with spreadsheets. Monday morning, May 11. Badge deactivation at 5:47 AM Eastern, building access at 5:48, VPN credentials at 5:49. Six hundred IT workers across twelve states. The distribution across twelve states was not arbitrary. Each state has a WARN Act notification threshold. Six hundred distributed across twelve states falls below every threshold. The workforce analytics team that designed the distribution model was not among the six hundred terminated. The skill of distributing layoffs across jurisdictions to avoid legal notification requirements is, apparently, an AI-native competency. GM posted 83 new positions the same week. The job descriptions require "AI-native development, data engineering and analytics, cloud-based engineering, agent and model development, and prompt engineering." I reviewed them at my client's request. Several describe roles that the terminated employees were already performing under different names. One posting, Senior Data Integration Architect, is identical to a role held by a woman in their Austin office who was terminated at 5:47 AM Central. She held the position for nine years. The new posting requires three years of experience with large language models. Large language models have existed in commercial deployment for approximately three years. The requirement is mathematically designed to exclude anyone who learned their skills before the technology existed. Which is everyone they just fired. Here is where the deck earns its fee. Slide 17 is titled "The Vocabulary Bridge." It is the most important slide in the presentation. It shows how to construct a lexicon of new competency terms ("AI fluency," "agentic mindset," "AI-native development") that describe existing work in language the existing workforce cannot claim. The vocabulary does not change the job. It changes who is qualified for the job. A senior IT administrator who managed SAP infrastructure processing $185 billion in annual GM revenue for fifteen years is not "AI-native." A twenty-six-year-old with a GitHub portfolio of LangChain wrappers is. The fifteen-year veteran did the work. The twenty-six-year-old has the words. My deck converts one into the other. That is the bridge. GitLab Duo, their AI agent platform, reached general availability on January 15, 2026. Seventeen weeks ago. They are restructuring their entire company around a product that has existed for seventeen weeks. GitHub Copilot has 20 million users and 4.7 million paid subscribers across 90% of the Fortune 100. Cursor reached $2 billion in annualized revenue in February. GitLab's competitor advantage in the "agentic era" is that they are willing to fire more people faster in service of a product that has been generally available for fewer days than their voluntary separation window has hours of anxiety. General Motors spent $10 billion on Cruise, their autonomous vehicle division. Cruise's signature achievement was a robotaxi that struck a pedestrian in San Francisco and dragged her twenty feet. The DOJ fined them $500,000. They settled with the victim for approximately $10 million. They killed the division in December 2024. They then wrote down $7.6 billion in EV losses. They then pivoted back to gasoline. They then announced the 600 IT layoffs for insufficient "AI skills." The AI they built cost $10 billion and injured a woman. The AI skills they're hiring for cost a twelve-week certificate. The employees they fired had fifteen years of keeping $185 billion in revenue processing without dragging anyone through an intersection. Meanwhile — and this is the part where I earn the second half of my fee — GM was simultaneously settling a $12.75 million fine with the California Attorney General for selling the precise GPS coordinates, hard braking events, and real-time driving speeds of 8 million OnStar subscribers to Verisk Analytics and LexisNexis, who used the data to raise those drivers' insurance premiums. GM's privacy policy explicitly stated they did not sell driving data. They sold driving data for four consecutive years. The fine was $12.75 million. The revenue was $20 million. The margin on collecting behavioral telemetry from 8 million of your own customers while the glove compartment manual said otherwise was 64%. The terminated employees' median salary was $95,111. Mary Barra's compensation was $29.9 million. The ratio is 310 to 1. The 1 was just reclassified as "not AI-native." I present these two clients to my partners every Thursday in a meeting we call "Transition Pipeline Review." I present them on the same slide. The slide has two columns. Left column: GitLab. Right column: General Motors. The headers are identical. "Legacy Workforce," "Skills Gap Narrative," "Vocabulary Bridge Deployed," "Separation Timeline," "Replacement Requisitions." The numbers differ. The structure is identical. The structure is always identical. I have seventeen clients in the pipeline. Nine are in technology. Four are in manufacturing. Two are in financial services. One is in healthcare. One is in defense. All seventeen are on slide 17. All seventeen are building a vocabulary bridge. All seventeen are replacing employees who have skills with employees who have words. GitLab's CEO wrote: "Software will be built by machines, directed by people." I read that sentence in a meeting where we were reviewing the rubric for determining which people would be directed out of the company. GM's Chief Product Officer arrived from Aurora, the autonomous trucking startup, to "consolidate disparate technology businesses." Three top software executives departed within six months. Their LinkedIn profiles say "exploring new opportunities" in the same font GM's privacy policy used to say "we do not sell your driving data." Bill Staples's compensation at GitLab was $39.1 million in FY2025. His change-of-control payout is modeled at $47.4 million. Mary Barra's was $29.9 million. Combined: $69 million for two executives presiding over a restructuring that will remove an undisclosed number of humans from payroll and replace them with products that are, respectively, seventeen weeks old and responsible for $10 billion in losses plus one woman dragged through a San Francisco intersection. An anonymous GitLab employee posted on Hacker News: "The employees can have some anxiety until then. As a treat." A GM facilities team filed a maintenance request about moisture on the lobby tables on restructuring mornings. The Warren, Michigan campus has a Panera Bread that opens at 5:30 AM on days when badge deactivations begin at 5:47 AM. The Panera does not know why its hours change. My firm does. We have an agreement with their regional manager. The muffins are complimentary. Slide 17 has a footnote. The footnote says: "Vocabulary Bridge deployment should precede workforce action by 60-90 days to establish institutional legitimacy of new competency framework." GitLab introduced "AI fluency" in January. The restructuring was announced in May. Four months. GM posted "AI-native" job descriptions the same week as the terminations. That is too fast. That is not what the deck recommends. GM skipped the legitimacy window. They went straight from vocabulary to separation without the 60-day buffer that allows HR to say, in the separation meeting, "we communicated these expectations in Q1." I flagged this in my Thursday pipeline review. My partner said, and I am quoting: "They'll be fine. Nobody sues over a word." My deck has been purchased by seventeen companies. The aggregate headcount affected across all seventeen is approximately 14,000 employees. The aggregate revenue of my practice from these engagements is $11.2 million. The per-employee cost of my advisory services works out to $800 per person displaced. That is less than the Panera muffin budget at GM's Warren campus annualized across restructuring days. I have a copy of GitLab's original values poster framed in my office. It says CREDIT: Collaboration, Results for Customers, Efficiency, Diversity Inclusion & Belonging, Iteration, Transparency. I purchased it on eBay from someone whose seller name is "gitlab-alum-2024." I keep it the way a surgeon keeps an X-ray of a interesting case. Not for sentiment. For reference. Slide 44 is titled "Implementation Timeline." It contains a Gantt chart. The Gantt chart has seventeen rows, one per client. Each row has four phases: Vocabulary Introduction, Competency Reassessment, Workforce Action, Replacement Hiring. The phases overlap. They always overlap. The vocabulary is introduced while the competency reassessment is being designed. The reassessment is completed while the workforce action is being calendared. The replacement hiring is posted while the terminated employees are sitting in a Panera at 5:48 AM wondering whether "AI-native" was a term that existed when they were hired. It was not. That is the bridge. That is the product. That is slides 2 through 43. The agentic era is not a technological shift. It is a vocabulary shift. The technology is seventeen weeks old or $10 billion underwater or dragging someone through an intersection. The vocabulary is what my clients are buying. The vocabulary is what makes a fifteen-year SAP administrator into a "legacy workforce" and a twelve-week prompt certificate into a "transition hire." The vocabulary is the product. I am the vendor. The deck is $14,200 per day. The agentic era starts on slide 1 and ends on slide 44 and in between is every employee who built the thing now being renamed to exclude them. I bill monthly. Net 30. The invoices are paid on time. The employees are not.