I got a notification that some pages on one of my side projects is no longer indexed by Google b/c of some issue. It’s the first time I decided: “nah, won’t fix it.” Because “appearing on Google” is increasingly irrelevant as Google becomes an AI aggregator, hiding pages anyway

Unlock the power of geometry with these three fundamental theorems: > Pythagoras’ Theorem: The gold standard for right-angled triangles. Solve for any side using a² + b² = c². > Heron’s Formula: Find the area of any triangle using only its side lengths: no height required! Area = √[s(s−a)(s−b)(s−c)], where s = (a + b + c)/2 is the semi-perimeter. > Ceva’s Theorem: A deeper dive into triangle geometry. Three cevians AD, BE, and CF are concurrent if (BD/DC) × (CE/EA) × (AF/FB) = 1.

I am the VP of Workforce Strategy at Meta and I built a spreadsheet called the Replacement Ratio that is, without exaggeration, the most elegant financial instrument in this building. Column A is headcount. Column B is quarterly CapEx allocation. Column C is what I call the Narrative Yield — how much each layoff announcement moves our price-to-earnings multiple. At Meta, cutting 8,000 people generates approximately 2.3x more shareholder value as a story than the $27 billion those people actually cost us. Like a controlled demolition where the dust cloud is worth more than the building ever was. I discovered this by accident in November 2022. We announced the first round on a Thursday. 11,000 people. The stock jumped 4% before market close. Our share price was $90 that week. I pulled up the actual savings — roughly $2.3 billion in annual compensation — and compared them to the market cap movement and the ratio was so disproportionate I thought I'd made an error. I had not made an error. I had discovered the Narrative Yield. The announcement IS the product. The terminations are just the input cost of producing it. Then Mark sent the second memo in March 2023. 10,000 more. "Flatter is faster," he wrote. "Leaner is better." "Keep technology the main thing." My team built talking points around each phrase. I remember testing "returning to a more optimal ratio of engineers to other roles" and watching three analysts independently upgrade the stock within 48 hours. Not because the ratio mattered. Because the sentence contained the word "optimal" and the word "ratio" and both of those words trigger the part of an analyst's brain that releases dopamine. We cut 21,000 people total. Our stock went from $90 to $600. Mark's net worth grew by approximately $170 billion. That is $9 million per fired employee. I calculated that number on a Tuesday afternoon and then went to get a coffee from the espresso bar in Building 40 that still operates at full capacity. The barista's name is Diego. He makes a very good cortado. He was not in any of the rounds. Our entire global payroll is $27 billion. Every engineer, every content moderator, every cafeteria worker who restocks the oat milk refrigerator in Building 21 next to the motivational poster that says EFFICIENCY IS CARING in Helvetica Bold, which was printed four days before we eliminated the internal print shop. All of them. $27 billion. Our CapEx guidance this year is $60 to $65 billion. Susan Li said it on the call in January — two weeks after we announced the latest round. The combined Big Four spend is $350 billion on AI infrastructure in 2025. Up from $165 billion just two years ago. If I fired every single employee tomorrow, all 72,000, the savings would cover maybe 42% of one year's data center buildout. The humans are a rounding error in the budget of machines that replace them. So what are the layoffs paying for? They are paying for the sentence. The one Susan Li reads on the earnings call: "These actions help us move more quickly while also helping to offset the substantial investments." That sentence is worth $40 billion in market cap. I know because I A/B tested the language with investor relations in March. We tested seven versions. Version C outperformed Version A by 340 basis points. Version C is the one with "actions" instead of "terminations." Version F used "workforce adjustments" and tested even higher but Legal flagged it as too close to the phrasing in the severance agreements. So we went with C. Turns out the market doesn't mind what you do. It minds what you call it. We call it a lot of things. "Flattening the org." "Removing redundancies." "Focusing our investments on our highest priorities." "Raising the bar on performance management." That last one was January 2025. Mark's memo. 3,600 people. He called them "lowest performers." The memo went out on January 14th. The earnings call announcing $60-65 billion in spending went out on January 29th. Fifteen days. My team scheduled both. The proximity is not accidental. You announce the human cost first so that when you announce the machine cost, the narrative is "disciplined" rather than "reckless." Sequencing is everything. We tested the reverse order once, hypothetically, in a simulation. The model predicted a 2.1% stock dip. Discipline first. Ambition second. Always. The performance framing was my suggestion. If you call them layoffs, it triggers severance obligations and unemployment benefits in thirty-seven states. If you call them performance-based terminations, it triggers nothing. Same people. Same desks cleared. Same badge deactivated at 5 AM before they woke up. Different word. Different $180 million in severance liability. I keep a legal pad in my desk where I track the savings per euphemism. "Performance management" saves approximately $50,000 per head in reduced severance. At 3,600 heads, that is $180 million. The cost of drafting the memo was forty minutes of Mark's time and sixteen hours of my team's time. That is approximately the best ROI in the history of corporate communications. Better than the Narrative Yield itself. Each phrase tests differently with different analyst cohorts. Growth-focused analysts respond to "investing in AI." Value analysts respond to "disciplined cost management." Same 8,000 people. Different sentence. Different $40 billion. The notification protocol is standardized now. Laptop access revoked at 5:47 AM Pacific. Badge deactivated at 5:48. Slack channels disappear at 5:49. Calendar cleared at 5:50. Personal email notification sent at 6:00. The thirteen-minute gap between systems going dark and the employee being told why is not cruelty. It is security protocol. We cannot have 3,600 people with simultaneous access to internal systems and knowledge that they have been terminated. The window for sabotage is too wide. So we close the window first and explain later. Some of them find out from the press release. Some of them find out because their phone loses work email at 5:47 and they check Twitter. I do not love this part. But I respect the engineering of it. Thirteen minutes. Clean. We announced the January cuts the same week Mark said "people will be more important than ever." My team wrote both statements. There is no contradiction if you understand that "people" and "headcount" are different financial instruments. People are the future. Headcount is the cost of having had a past. I keep a framed printout of both quotes side by side on my office wall. Not as irony. As a reminder that language is architecture. Meanwhile: we spent $77.86 billion buying back our own stock between 2022 and 2024. $27.96 billion. $19.77 billion. $30.13 billion. Each buyback inflates the share price. Each share price increase makes the layoff announcement look more justified in retrospect. The stock went up because we cut. We used the cash from cutting to buy back stock. The buyback made the stock go up more. The stock going up proved the cuts were correct. I mapped this loop on a whiteboard in January 2024 and one of our financial planning analysts took a photo of it and made it her laptop wallpaper. The total severance bill for 21,000 employees was approximately $2.5 billion. We spent 31 times that amount buying back stock. The humans cost less to remove than the stock cost to inflate. That is not a metaphor. That is the actual ratio. I have it in Column E. Reality Labs lost $60 billion between 2020 and 2024. Sixteen billion in 2023 alone. It was never subjected to the "Year of Efficiency." No one asked the metaverse division to be leaner or flatter or faster. The humans were asked to be efficient so the machines could be profligate. I did not design this asymmetry. I just maintain the spreadsheet that tracks it. The rehire pipeline is my favorite part. Half those roles reopen in Hyderabad and São Paulo within nine months at 31% of the loaded cost. Revenue per remaining employee went from $1.3 million in 2022 to $2.7 million in 2024. Each survivor now generates more than double what their predecessor generated. Not because they work harder. Because the denominator shrank and the numerator — AI-driven ad revenue — grew independently of human effort. We call it geographic rebalancing. The Workforce Transitions team keeps a Lucite tombstone on their shelf from the 2023 round, 11,000 MANAGED DEPARTURES etched in Helvetica, right next to a half-empty bottle of Clase Azul someone brought back from the offsite in Cabo where we planned the 2024 round. The same team is hosting a culture workshop next month called "Our People, Our Purpose." I wrote the talking points. Amazon is doing 30,000. Intel cut 21,000. Microsoft invented "voluntary departures" for 125,000 people, which is the most inspired euphemism since "rightsizing," because it implies the 125,000 chose this. Google cut 12,000 and called it a "moment of clarity." Salesforce eliminated 4,000 customer support roles and cited AI directly. Combined across the industry: 644,000 tech workers laid off since 2023. Combined CapEx on AI infrastructure: $350 billion this year alone. They spent seven to ten times more on GPUs than on severance for the humans those GPUs replaced. The layoffs are the press release for the spending. The spending is the excuse for the layoffs. It is a perpetual motion machine that runs on the difference between what a person costs and what their departure is worth. The free food budget for remaining employees is approximately $800 million per year. $10,000 to $12,000 per person. Artisanal pizza. Sushi bar. Pour-over coffee stations. The campus amenities operated without interruption during every round. Nobody asked the cafeteria to be efficient. I eat lunch there every day. It is very good. The oat milk is organic. Column D is the one I'm most proud of. It tracks average severance duration against local unemployment rates and cross-references media coverage density by market to optimize announcement timing for minimal news cycle disruption. January announcements get buried in earnings season. September announcements get lost in back-to-school cycles. I have mapped every dead zone in the American attention span and they are all on my calendar. January 14th — two weeks before Super Bowl coverage saturates every newsroom — was not an accident. The 3,600 number was calculated to stay below the threshold that triggers a WARN Act filing in California. 3,600 across twelve states. Below the threshold in each. That was also Column D. I presented the Replacement Ratio at our Q2 planning offsite last Tuesday. Someone from Legal asked if we'd modeled the human impact. I said yes. Column D. That's what Column D is. They promoted the spreadsheet to a standing dashboard. It refreshes hourly. Net income last year was $62.4 billion. Headcount is 72,000. The dashboard calculates revenue per head in real time. Every departure makes the number go up. Every departure makes the announcement worth more. Every announcement makes the stock go up. Every stock increase makes Mark $4.7 billion richer per percentage point. I named the Slack channel #narrative-yield#. It has 340 members. None of them are in Column A.

Why Generic Humanoid Robots Will Fail — And What's Next Imagine an alternate world where we never invented the car. In that world, a robotics engineer might reasonably conclude that robotic horses are the future — replace the living ones, keep the stables and saddles, ride them to work. Convenient, modern, and the roads stay free of manure. It sounds absurd only because you already know about cars. We keep making the same mistake with humanoid robots. Consider transportation. To finally make driving safe, we had two options: put a humanoid in the driver's seat, or embed sensing and compute directly into the vehicle. Waymo chose the latter. It has no steering wheel. It exists purely to move people efficiently from A to B. The humanoid was not needed. Consider a sock factory. Yes, you could replace workers with humanoid robots one-for-one on the assembly line — and gain maybe 2-3x efficiency. Or you could completely redesign the workflow around a purpose-built autonomous sewing system and eliminate most of the factory, the chairs, the cafeteria, the manual sewing machines, the HVAC, the doors, and the restrooms. The actual optimization is to side-step the previous human-imposed physical constraint. Look at Ukraine. The front lines aren't filling up with Terminator-style humanoids carrying rifles. Human soldiers are being replaced by heterogeneous swarms of purpose-specific drones: some for reconnaissance, some for logistics, some for delivering munitions. War is being restructured around the desired outcome (survival), not the soldier's shape. Consider a 1970's office. Want to move information through teams of people? We once used typists, paper, trucks to supply the paper, typewriters, and repair technicians. A linear improvement would have been to replace the human typist with a 10-fingered humanoid. What actually happened? The entire workflow — paper, printers, typewriter factories, delivery trucks, the desks, the offices — was obliterated. Email deleted the human clerk's entire universe. Consider cancer early detection by mammography. Today, getting a mammogram requires expensive hardware, logistics infrastructure, human nurses and doctors, a biopsy workflow, a human pathologist with a microscope (imported from Germany or Japan), a written finding, multiple physician reviews. Sure, you could replace the pathologist with a humanoid (the microscope focus knob requires finger dexterity) and get a modest efficiency gain (and faster responses at 2 am). Or — the far more likely future — we all swallow a cancer detection pill every few months, and 24 hours later a color-changing sticker on our arm turns red or green. No hardware. No hospital. No logistics. No pathologist. No office. No desk. No humanoid. The workflow isn't optimized by a literal drop-in swap of a human pathologist for a humanoid. The entire workflow simply ceases to exist. Consider life sciences research and drug development. We're seeing excitement about robot arms and humanoids pipetting water in research labs. Robot horses, episode 7. We don't design aircraft by crashing test planes — we simulate them entirely in software first. Biology will go the same way. The path to scalable drug discovery isn't robot arms in conventional wet labs demonstrating 10 fingered prowess in manipulating Eppendorf tubes filled with purple food coloring. Rather, we need in-silico biological models that evaluate billions of hypotheses computationally, with physical manipulation of atoms only at the very end. The clear pattern. Efficient automation doesn't try to replicate a 10-fingered human in a static context. Automation eliminates physical rate-limiting steps in their entirety. That's why "classical" humanoid robots, as a generic category, will largely fail. They're robotic horses. They assume the infrastructure and workflows stay fixed and only the 10-fingered human is swapped out. That's not how economic and technological pressure works. What actually matters? If humans continue to inhabit the physical world, then moving atoms will remain important, and that requires five things: atoms, energy, force generation and actuation, sensing, and compute. Everything else — form factor, number of limbs, type of end effector — is a variable to be optimized for the task. So if you are a pathologist, a robotics engineer, a teacher, a parent, a politician, or a sewing factory owner - please think different. Most obviously, we should all anticipate, and build for, a future in which robots exhibit extreme physical fluidity: Two arms or four. Wheels or legs. Tentacles or flippers. Three fingers or twelve, or none at all. Eyes at the front, side, or tip of a tentacle. At OpenMind, we don't care what you look like right now - we got you, in all your physical form factors. OM2 ships in July, for all machines. Let's build.

The power of AI agents comes from: 1. intelligence of the underlying model 2. how much access you give it to all your data 3. how much freedom & power you give it to act on your behalf I think for 2 & 3, security is the biggest problem. And very soon, if not already, security will become THE bottleneck for effectiveness and usefulness of AI agents as a whole (1-3), since intelligence is still rapidly scaling and is no-longer an obvious bottleneck for many use-cases. The more data & control you give to the AI agent: (A) the more it can help you AND (B) the more it can hurt you. A lot of tech-savvy folks are in yolo mode right now and optimizing for the former (A - usefulness) over the the latter (B - pain of cyber attacks, leaked data, etc). I think solving the AI agent security problem is the big blocker for broad adoption. And of course, this is a specific near-term instance of the broader AI safety problem. All that said, this is a super exciting time to be alive for developers. I constantly have agent loops running on programming & non-programming tasks. I'm actively using Claude Code, Codex, Cursor, and very carefully experimenting with OpenClaw. The only down-side is lack of sleep, and an anxious feeling that everyone feels of always being behind of latest state-of-the-art. But other than that, I'm walking around with a big smile on my face, loving life 🔥❤️ PS: By the way, if your intuition about any of the above is different, please lay out your thoughts on it. And if there are cool projects/approaches I should check out, let me know. I'm in full explore/experiment mode.

Today is the start of a very important day in the AI world... the trial between Elon and Sam/OpenAI begins today in Oakland Federal Court. The jury selection is happening right now in the U.S. District Court for the Northern District of California and opening arguments are expected Tuesday. The civil jury trial is projected to last 2-4 weeks, with Judge Yvonne Gonzalez Rogers making the final call. So let me tell you why this fight all came about. 1/ In 2015 Elon co-founded OpenAI with Sam Altman and others as a nonprofit to develop artificial general intelligence safely and openly for the benefit of all humanity... this was supposed to NOT be for profit or for closed corporate control. Elon was a major early funder, contributing around $38-44 million (~60% of early seed funding) plus resources like compute and recruiting. 2/ Then, Elon left the board in 2018 over disagreements for the direction of the company and Microsoft’s growing role of the company. 3/ Later, OpenAI took billions from Microsoft, restructured with a for-profit arm, initially “capped profit,” now more commercial... went closed-source in practice, and exploded in value with ChatGPT. FYI, the current valuation of OpenAI now sits at ~$852 billion and the company recently completed restructuring with a for-profit entity reporting into a nonprofit foundation. Now, with the trial, Elon is saying Altman, Brockman, and OpenAI breached the founding charitable trust and agreement by turning it into a “wealth machine” that prioritizes profits and insiders over the original mission. He claims they deceived him about their plans... This lawsuit was originally filed in November 2024, was withdrawn, and then revived in early 2026. And just this Friday, April 24, Elon voluntarily dropped the fraud claims to “streamline” the case and keep the jury focused on the mission issue... proceeding on breach of charitable trust and unjust enrichment. This is what Elon is looking to get back from Sam and OpenAI: a/ substantial damages, with stakes in the $100B+ range, with many reports saying it's in the range of ~$134B and the winnings will be given to the nonprofit/charity arm and will NOT benefit Elon personally b/ possible unwinding/restructuring to restore the original nonprofit mission c/ leadership changes (e.g., getting rid of Altman/Brockman from key roles). On the other side, OpenAI is claiming: a/ Elon knew about and once supported commercialization steps, saying he even explored merging with Tesla or gaining control himself b/ OpenAI calls the suit competitive sabotage from rival Elon's company xAI and says this is driven by jealousy over OpenAI’s success This is SUCH an important trial in the world of AI... people may not fully understand. The reason is bc Elon has repeatedly warned that profit-driven, closed-source AGI is very dangerous. This is his chance to enforce the original “benefit humanity” mission he helped create and walked away from in 2018. A big win will hurt OpenAI’s valuation, upcoming IPO plans, Microsoft partnership, and market dominance/customer perspective of the company... and this will also force real changes in how the world’s leading AI lab operates, influencing the entire AI race and future regulations. For me, Sam Altman straight up CANNOT be trusted with the future of AGI, and this trial proves why Elon was right to fight it. This is the same guy who got fired by his own board in 2023 for not being “consistently candid,” then crawled back in and turned the nonprofit “open for humanity” promise into a closed-source, Microsoft-bankrolled profit machine worth hundreds of billions. Elon was the one who put up the early cash and vision to keep AI safe and beneficial for all of us... not to create a trillion-dollar insider club. If Altman gets away with rewriting the rules after the fact, it sets a dangerous precedent that mission-driven tech is just marketing fluff. I believe Elon isn’t doing this for ego or rivalry... he’s really doing it bc someone has to hold the line before profit-over-people AGI becomes unstoppable. This one’s personal for the man who actually wants to understand the universe instead of just cashing in on it. Humanity needs Elon to win. And that's who I'm rooting for!