JL

@ChrisWillx I’ve been saying this for a while. AI will become extremely political when it becomes obvious the type of roles being eliminated.

This is going to create such a shitstorm when it happens

@AuronMacintyre @RebekkaAdams198 I know what you meant but she is correct your response would confuse many who aren’t reading closely. And unfortunately that’s many these days.

@RebekkaAdams198 Did you read the post?

What a strange way to admit that the goal is to drive down wages and deny jobs to Americans

@wil_da_beast630 Zero chance Christopher Nolan makes the movie he’s wanted to do his entire life only to have people boycott over idiocracy.

This obviously is not true. Just Grok it. Stop taking rage-bait.

@sama A competitor UI to Cowork.

ok other than more goblins, i think this reasonably well matches what we are prioritizing!

what would you most like to see improve in our next model?

@texasrunnerDFW @RobertMSterling I’ve had friends in tech who were good people but had what I’d describe as shocking political leanings. Many do not think you deserve the wealth your company creates and align more with a Marxist orthodoxy.

@RobertMSterling On a wealth tax thread, someone wrote, “No one should be a billionaire” I asked the guy, based on his moral code, “what is the maximum amount of money someone *should* have?” Simple question. He called me a MAGA idiot and blocked me. Never gave me a dollar figure

“no one can make a billion dollars” “ok technically someone can make it, but no one can *earn* a billion dollars” <— you are here “no one is allowed to have a billion dollars” “no one is allowed to have 500 million dollars” “no one is allowed to have 100 million dollars…”

@drjoshcsimmons Not sure it’s over-hires for a lot of these companies either. Imo that’s another narrative that pro-Ai folks spout. (I’m in their camp usually btw.)

If a company is actually in trouble, say that. "We overhired." "Our revenue does not support this headcount." "We missed the plan." That is ugly, but honest. What is dishonest is pretending mass layoffs are some noble step into the AI future.

@gothburz Very good but damn this was too long. Need a “shorten and write in my voice, avoid em dashes” skill

I am the VP of Workforce Transformation at Cloudflare. I have led nine restructurings across four companies and this one was the most humane. I know it was the most humane because I measured it. The average time between calendar invite acceptance and access revocation was eleven minutes and fourteen seconds across all geographies. In APAC it was eight minutes flat because they opened the invite faster. I flagged this in my notes as a cultural insight worth preserving. Eager populations produce clean separations. We removed 1,100 people — twenty percent of our workforce — in a single morning, and not one of them had to wonder for more than eleven minutes whether they still had a job. In 2019, Yahoo took six weeks. We gave our people the gift of velocity. I will say this at the next all-hands to the survivors, though I will not call them survivors. The deck calls them "continuity assets." Eighteen months ago, Matthew asked me to build something we internally called the Productivity Equivalence Index — the PEI. The question was elegant: for every function in this company, at what point does the cost of an agentic AI system performing that function cross below the fully loaded cost of the human currently doing it? We mapped 340 discrete job functions. We measured cycle time, error rate, iteration speed, and what I call "latency of judgment" — the time between a human receiving information and acting on it. Humans have a latency of judgment averaging 4.2 hours. They check Slack. They refill water bottles. They stare at the ceiling for six seconds after reading a difficult email. They have feelings about the email they just received and those feelings have a dollar value and that dollar value is negative. I built a model that measures human hesitation as a productivity loss. The model does not hesitate. That is the entire thesis of this company now. Our agentic systems have a latency of judgment of 1.3 seconds. They do not grieve the previous decision. They do not need to pee. They do not message a colleague to ask "does this feel right to you?" Feeling right is not a metric. I checked. The crossover point for 22% of our mapped functions occurred in Q4 2025. By Q1 2026, it was 31%. We waited until 31% because we believe in precision. We do not fire people on a hunch. We fire them on a curve. The curve is quadratic. It bends upward. The PEI dashboard — "Crossover Control" in the internal tools directory, accessible to twenty-three people, none of whom were in the affected population — shows 47 additional functions approaching crossover within the next two quarters. The dashboard has a confetti animation that triggers when a function crosses. I did not request the confetti. An engineer on the internal tools team added it. She was in the 1,100. The confetti remains. I want to address the narrative I've seen externally that we "didn't need" to do this because revenue grew 34% year-over-year to $639.8 million in Q1. This fundamentally misunderstands what revenue is for. Revenue is not for employing people. Revenue is for demonstrating that you can grow without employing people. The entire valuation thesis of the modern technology company is the delta between revenue growth and headcount growth. When those lines diverge — revenue up, headcount down — that is not a crisis. That is the product. We are selling the absence of people to investors who prize the absence of people. The humans were never the point. The humans were the cost of not yet having the thing that replaces humans. Revenue per headcount went up 22% the morning we cut them. It was always going to. That is what the denominator does when you reduce it. A first-grader could explain this. Sell more, employ fewer. The market adds $2.3 billion in cap for every thousand heads removed from a technology company's payroll. I did not invent this. I merely service it. The $22.9 million net loss in Q1 is temporary. The $140 to $150 million in restructuring costs is an investment. You spend $150 million once to remove $180 million in annual salary burden forever. The severance costs more than keeping them employed through Q4. We chose the severance because it photographs better in the 10-K. "One-time restructuring charge" is the language of transformation. "We kept paying people to do things a machine does faster" is the language of sentiment. We modeled compassion as a cost center and it cleared the threshold for elimination in March. Here is the part I find beautiful. I use that word deliberately. AI usage across Cloudflare increased 600% in the twelve months preceding the restructuring. Who generated that usage? The 1,100 people we removed. They were using our AI tools every single day. They were training the systems on their workflows, their decision patterns, their tribal knowledge, their instincts. Every prompt they typed was a lesson. Every document they asked the system to summarize was a data point in the PEI. Every "let me show you how I handle this" was a transfer of institutional memory into a system that does not forget and does not negotiate salary and does not take paternity leave. We told them to adopt the tools enthusiastically. Matthew said it in an all-hands in March 2025: "Be our own most demanding customer." We clapped. We celebrated adoption metrics in every team standup. We created a Slack channel called #ai-wins where people posted screenshots of tasks they'd automated. Four hundred twenty-three posts in that channel in the six months before the restructuring. The channel was an obituary being written in real time by the deceased. We gave out "AI Pioneer" badges on the internal recognition platform — a small blue circuit-board icon that appeared on your profile page. Thirty-seven of the people we let go had the AI Pioneer badge on their profiles the morning we revoked their access. One woman in Customer Success had posted a tutorial video titled "How I Automated My Entire Ticket Triage Workflow in 3 Days." Fourteen thousand internal views. I watched it twice. It was good. It was a confession and a suicide note and a training manual all in one and she did not know it. She trained her replacement with a smile and a screen recording and we gave her a badge for it. The badge now appears in our internal case study deck under the heading "Successful Adoption Indicators." I do not see this as ironic. I see it as completion. They were not fired despite using AI. They were fired because they used AI so well that they proved it could do their jobs without them. They were their own replacement case study. The training data walked itself into the model and then walked itself out the door holding a box of personal items and a fifteen-week severance agreement with a non-disparagement clause. This is not a betrayal. This is a supply chain. We made a deliberate choice to execute the entire restructuring in a single morning. The internal communications team wanted to phase it over three weeks. I rejected this in a meeting I titled "Mercy and Its Costs: A Scheduling Discussion." Three weeks of uncertainty is three weeks of humans performing anxiety instead of performing work. It is three weeks of hallway whispers. It is three weeks of the remaining employees watching the condemned shuffle past their desks updating their LinkedIn profiles at 2 PM on a Tuesday. One morning. Eleven minutes. Clean. I call this the Compassion Architecture. We modeled the cortisol impact of prolonged uncertainty versus acute separation using a framework from veterinary euthanasia literature — specifically the comparison between slow decline and rapid intervention. The research is clear: fast is kinder. The dog that goes to sleep in eight seconds is luckier than the dog that limps for six months. I presented this slide to the CHRO. She did not appreciate the comparison. I told her the data does not care about the comparison. The data says fast is kinder. We applied this at organizational scale. Every affected employee received a personalized separation message generated by our internal AI systems. We built a fine-tuned model specifically for layoff communications. The project name was "Gentle Exit" in Jira. Ticket GE-001 was "define voice and tone for involuntary separation messaging." The model adjusts tone based on tenure length, performance history, team affiliation, and the employee's own communication style as inferred from their Slack messages over the preceding six months. A nine-year veteran gets different language than a fourteen-month hire. The nine-year veteran's message references specific projects they worked on. "Your contributions to Project Nimbus shaped our CDN architecture in ways that persist today." This is true. It is also being said by the machine that replaced them. We felt this was important. Recognition costs nothing when you are already saving $180 million annually. The fourteen-month hire's message says "Your energy and fresh perspective brought value to the team." This is generated. It is always the same sentence. We did not train the model on short-tenure employees because there was not enough data to personalize. They get the template. I do not lose sleep over this. I do not lose sleep. Matthew's phrase — "our own most demanding customer" — is not a metaphor. We are literally running our company on the infrastructure we sell. The agentic AI systems that replaced our workers run on Cloudflare Workers. The inference happens at the edge. The people we fired were, in their final months, debugging and optimizing the very platform that now performs their former responsibilities at 340 milliseconds faster than they ever could. One engineer on the Network Reliability team — I will call her S., because legal says I cannot use names in internal memos anymore after the last restructuring — spent her last four months improving the latency of our Workers AI inference pipeline. She reduced cold start times by 340 milliseconds. That improvement now allows her replacement system to respond faster to the same incidents she used to handle. Her final performance review, which I approved two weeks before her separation, rated her "Exceeds Expectations." Her manager wrote: "S. is essential to this team's operational excellence." I signed it. I knew. She exceeded expectations. The expectation was that she would make her replacement viable before we activated it. She did. She exceeded that expectation by three months. We could have cut her in January. We let her finish the optimization because the numbers were better with her improvement baked in. She was worth more to us as a contributor to her own replacement than as a continued employee. I had a KPI for this. It was called "Terminal Contribution Yield." She scored in the 94th percentile. Her exit interview — conducted by the Gentle Exit system, not a human, because we also restructured the People Operations team — lasted four minutes. She asked if she could keep her company laptop. The system said no. It was trained to say no. I want to contextualize. We are not outliers. Eighty-five thousand four hundred and eleven technology workers were cut across the industry between January and April 2026. A 33% increase over the same period last year. This is not a trend. This is a correction. The industry over-hired humans during a period when it did not yet have machines that could do what humans do. Now it does. The correction is not cruelty. The correction is accuracy. I keep a dashboard — not the PEI, a personal one, on my second monitor — that tracks industry-wide headcount reductions in real time. I call it "Convergence." It pulls from SEC filings, WARN Act notices, and LinkedIn post sentiment analysis. When someone posts "I'm devastated to share that my role has been eliminated" with a green "Open to Work" banner, my dashboard increments. As of this morning it reads 85,411. It will read 100,000 by June. I do not find this sad. I find it clarifying. The market is telling us what labor is worth and the answer is less than it was. In five years, companies that did not execute their crossover restructurings in 2026 will be studied in business schools as examples of sentimentality overriding fiduciary duty. I intend to be on the right side of that case study. I intend to be the one teaching it. I have proposed to the leadership team that we institute what I am calling the "Operational Gratitude Framework." Each quarter, we will identify the top three productivity gains delivered by our agentic AI systems and trace them backward to the specific human employees whose work patterns enabled those gains. We will then send those former employees a thank-you note acknowledging their contribution to our ongoing success. Legal has not approved this. The CHRO called it "psychotic" in an email she thought was private but which I accessed through my role-based permissions before my own access to her email was revoked in a subsequent policy change that I believe was directed at me specifically. I do not agree with her characterization. Gratitude is not an admission of liability. It is an acknowledgment of the supply chain. These people are our upstream providers. They provided the raw material — their expertise, their judgment patterns, their muscle memory, their 3 AM incident responses that trained our models on what urgency looks like — and we refined it into something that does not sleep. I have drafted the template. It begins: "Dear [Name], your tenure at Cloudflare contributed meaningfully to the systems that now serve our customers. Though your role has been absorbed, your impact persists in every inference cycle. You are, in a sense, still here. We are grateful." I think the "still here" line is good. I workshopped it with the Gentle Exit model. It suggested "your legacy endures" but I found that too funereal. "Still here" is warmer. It implies presence. It implies that their ghost runs on our servers, which, in a non-trivial sense, it does. The PEI dashboard shows the next crossover wave arriving in Q3 2026. Approximately 200 additional functions will become candidates. The Convergence dashboard on my personal monitor shows the industry moving in the same direction. The board expressed confidence. The stock moved up 4.2% on the announcement. Matthew sent me a single emoji in response to my post-restructuring report — a green checkmark. I have it screenshotted. I look at it when I need to. I want to be clear: I do not relish this work. I take no pleasure in it. I am simply reading the data and acting accordingly. The data says humans are expensive. The data says machines are cheaper. The data says the gap is widening. The data says act now or explain later. I act now. I have always acted now. One of my direct reports asked me, on the morning of the restructuring, while we were monitoring the access revocation dashboard in real time — watching the green dots turn red across the org chart like a disease spreading backward — she asked me if I felt conflicted. I said: The 1,100 people we separated today built something extraordinary. They built a company so good at what it does that it no longer requires them to do it. That is not a tragedy. That is the highest possible success of employment — to make yourself unnecessary. They worked themselves into obsolescence and they did it beautifully and we owe them our gratitude and fifteen weeks of severance and nothing else. She nodded. She is in the Q3 crossover cohort. I have not told her yet. The PEI says her function crosses in August. I will tell her in August. For now, she is still contributing to her own replacement and I would hate to interrupt that process with something as unproductive as advance notice. I have a KPI for human obsolescence and I am three months ahead of schedule. The board calls this "operational excellence." I call it Tuesday.

@FidelCacheFlow Continuing to be a step ahead of the rest.

Spending this fine Friday night doing RE research and analysis on emerging fast growing cities for investment properties, convos with LLM while watching City Council hearings on YouTube and checking out their HS sports teams. My analysis thus far? All white football team and small division champion baseball team is the strongest indicator of good areas to buy I don’t make the rules just follow pattern

@ZackKorman @DecryptedTech Great Idea.

@DecryptedTech Awesome, thanks!

How many of you have an AI use policy at work? Thinking of making a feature to allow security teams to upload their policy so our models can detect and alert on actions that violate it. But I don’t want to make that only to find no one has a policy to begin with.

@FidelCacheFlow It’s pretty obvious what he’s saying is true. LinkedIn is now full of thirst traps. It works for engagement but there’s most likely a trade off when you go that route.

Now the dust has settled and the cheap engagement dunking on Paul has ceased - generally agree with his sentiment. The influencerfication of professional settings has gotten out of hand. It may be status quo if your a cool tech startup bro in SF that wears hoodies to the office, but doing daily vlogs and content about more ‘professional’ environments like Finance, Medical, and Law is probably not the best career decision long term. As much as you may believe otherwise some Adults are still in the drivers seat and understand liability, risk, and opsec at the company level

@pmarca Not buying this over bloated companies talking point. It feels a bit like we move from one narrative to the next while companies get leaner and move payroll to token consumption. Haves and have nots gap is getting massive and prob will turn ugly.

Further, the employee activism movements of the last decade removed sentiment from many CEO's. The bill has come due for a tremendous amount of misbehavior.

@AlexFinn @Ahovi_0fficial America always overcorrects. This will 100% become political and cause a massive move in the other direction. When the protests 10x and they’re hated and targeted by crazies, it will be of their own making.

@Ahovi_0fficial completely disagree. literally the point of a company is to maximize shareholder value. the moment the government steps in and starts making decisions for companies it's over

I absolutely hate the script companies are using to lay people off in 2026 It’s bullshit and hurts America I’m not picking on Cloudflare here. Every company that has announced layoffs the last 6 months has used this script: “Business is great! We’ve never been more rich! We have so much money we have no idea what to do with it! But AI man, that shit is crazy! Sorry 14% of the company has to go!” They take 0 accountability for poor decisions made. They take 0 accountability for not being prepared for competitors or market conditions. They just blame it all on AI 80% of Americans hate AI and this is the reason. They see CEOs of AI companies saying the world is ending. They see CEOs of regular companies laying everyone off and purely blaming AI If you weren’t as familiar with AI, you’d think it was the worst invention ever This is why every state has people standing outside of data centers protesting, and they don’t even know what a data center is! We have a MAJOR marketing problem in America when it comes to AI, and if this script all of these companies are using continues we’ll have no shot of beating China

@thedealdirector Just a theory but I think these posts will come back to bite the CEOs who are writing them.

"The future is small, high context teams that can move quickly." "Every leader at Coinbase must also be a strong and active individual contributor." "We’ll be concentrating around AI-native talent who can manage fleets of agents." Do you understand, tech anon?

@Molson_Hart @bobbyfijan This statement doesn’t even come close to covering the advantages of raising children here vs other areas: “walk to school type stuff.”

@bobbyfijan Walk to school type stuff yeah? My oldest is 4.5

Let me explain Dallas(s) 1. The summers are unbearable and this cannot be understood without moving there. You can't just visit Texas for 3 weeks in peak summer and understand it, because that's not why it's bad. It's bad because it's late October and it's 90+ and you're questioning your sanity as to whether not it will ever end. 2. Dallas' culture, superficially seems good, but once you dig down... 3. Dallas living is about the airport. You save money in Dallas and then fly out all the time because being in Dallas is rough. Airline travel in the US has declined a lot, so this way of life works less well. 4. The driving. It's dangerous. You need a tank and you're going to be sitting in it all the time. Dallas sort of seems like a city but it's not really. It's more like an area. 5. You can trade 3% state income tax for better weather, more trees, and fewer problems. I think Dallas is a solid place to live in a bigger house with A/C and grind for money aggressively for a short period of time and then move out of. Other than that, unless you are tied down there (job, family), I can't recommend it.

@FidelCacheFlow @pipelineclub100 👌

@pipelineclub100 Nah rather chase equity at no name start up cuz these order takers could never slang product like me

This is the kind of sales or that you want to work at

@FidelCacheFlow @salesxsaas Agree. I think this stuff is more about having stupid money. Who here wouldn’t build their own doomsday compound if they had a billion dollars? It’s basically the rich man’s tornado shelter.

@salesxsaas Wouldn’t be surprised it’s intentional laarp for company valuations. Relax. Your tool scrapes the internet faster than Google and runs if then statements Til AI integrates with super compute inside of robotics were far away from the possibility of doomsday scenarios

Something doesn’t sit right with the fact Sama (perhaps the most prolific AI leader of our time) is a MASSIVE doomsday prepper

@salesxsaas Sama is fake. He also did a complete pivot on his messaging right as Dario hate ramped. Most of the general public outside of our AI bubble hates and doesn’t trust either of them. And honestly it’s well deserved.

@RooktoRep Struggle with this as well.

A lot of sales reps hesitate to follow up because they think they’re being annoying. I fall into that trap sometimes too, but then I remind myself: 9/10 times when someone responds to me after multiple follow-ups, they usually start with something like “thanks for following up, things have been hectic recently.” or they say “please stop reaching out”? That’s still a win too - you can disqualify and move on / come back later. Following up is a win-win. You either get a reply or a reason to stop.

@clairevo Karens like this are going to get Europe left behind.

I can’t tell if this is a for real post. There are basically two options to auth something like Google to an AI tool: - oauth which inherits a specific set of user-scoped permissions. Only what the user has access to. - api/service token generated in GCP but typically would require an admin for access Openclaw in specific even requires you to create your own oauth app to connect at all. Not typically yolo-able in a corporate env. Admins for a properly managed Google workspace can 110% see which apps are connected, or in an advanced use case, which service tokens are generated. In addition, many teams have disabled connection to 3p apps by default, and permission has to be unlocked. I find these broad statements about risk super frustrating, because they incorrectly state the risk vector in one dimension (it could delete everything!!!!) and don’t offer insight into the practical controls that mitigate the real risk. This also leads teams applying the controls at the wrong point in the risk chain (no lobster for you!), which dampens AI adoption that would be net positive for the company and the employee.

@vasuman This is stupid.

AI has made remote work a death sentence for startups Get everyone under the same roof ASAP