I am the Senior Vice President of Workforce Architecture at Cloudflare and I need to tell you about the best decision this company has ever made. We posted $639.8 million in quarterly revenue. 34% year-over-year growth. Record net retention. The strongest quarter since IPO. And then we fired 1,100 people. Not because of the quarter. During the quarter. I need you to understand the sequence because the sequence is the whole point. My team built the model that made this possible. We call it CIRRUS: "Capacity-Indexed Reduction and Reallocation for Upside Scaling". CIRRUS took our revenue trajectory, our margin targets, and our board's stated appetite for what they called "structural boldness," and it determined that the optimal time to execute a 20% headcount reduction is at the exact moment of peak financial performance. Not during a downturn. Not during a miss. During a beat. The logic is simple. When revenue is surging, the market reads a cost reduction as discipline. When revenue is falling, the market reads the same reduction as panic. Same action. Same 1,100 people. Completely different stock reaction. CIRRUS identified a seven-day window where the earnings momentum and the layoff announcement would compound rather than cancel. I found the math beautiful. I still do. We deactivated 1,100 badges between 9:00 and 9:04 AM Pacific on a Monday. People Analytics determined this was the four-minute window of lowest Slack activity. We called it a "clean cutover." Someone in Infrastructure suggested "zero-downtime deprecation" but Legal thought it sounded too much like a product feature. I thought it sounded exactly like a product feature, which is why I liked it. But I deferred to Legal. I always defer to Legal. That is one of the things that makes me good at this job. The people we cut were not underperformers. I want to be very clear about that because clarity is a Cloudflare value. Sixty-two percent had received exceeds-expectations in their most recent review cycle. Fourteen had been promoted in Q3. One engineer in our Austin office — I'll call him Marcus, though that is not his name and the reason I'm not using his name is not that I've forgotten it — had shipped the caching optimization that directly contributed to $14 million in new enterprise contracts. His manager nominated him for the Raygun Award, which is our internal recognition for outsized impact, six days before I added him to the CIRRUS list. He won the award on Wednesday. His access was revoked the following Monday. The ceremony and the termination were planned by different teams in the same building and neither team knew about the other. I don't think this is ironic. I think this is how large organizations work. The left hand builds. The right hand optimizes. Both hands are attached to the same body and the body is performing well. We let Marcus keep the trophy. It's a small acrylic prism etched with a lightning bolt. It costs us about eleven dollars. His annual cost-to-company was $312,000. CIRRUS selected the 1,100 based on three variables. I'm going to share them because I believe in the methodology. First: salary band. Employees in bands 6 through 8 offered the highest savings-to-replacement-risk ratio. Second: visa dependency. Employees on sponsored visas have a 60-day window to find new employment or begin departure proceedings. This creates what CIRRUS categorizes as "low-friction separation" — the compliance timeline is externally enforced, which reduces our administrative burden. I presented this variable to HR and they requested I rename it from "visa dependency" to "mobility factor" in all future documentation. I agreed. The math didn't change. Third: managerial tenure. Employees whose direct manager had been at the company less than eighteen months were 73% less likely to generate a negative Glassdoor review, because the manager-employee bond hadn't fully formed. CIRRUS weighted this at 15% of the selection score. We call it the "attachment coefficient." We told the market the layoffs were an AI workforce pivot. We said artificial intelligence was making certain roles redundant. We said we were reallocating resources toward our AI gateway products. This was a communications strategy. Not a workforce strategy. The AI framing was my team's recommendation and I'm proud of it because it worked. Two analysts upgraded us the same week. The stock moved 8% in five sessions. The entire AI narrative was four paragraphs in a press release that took my comms partner and me an afternoon to write. Four paragraphs. 1,100 people. 8%. I don't know what the per-paragraph return on that is but I think about it sometimes. The actual AI initiative employs thirty-seven people. We cut 1,100 to fund 37. The ratio is not in any of our public materials. There is a Slack channel called #bright-futures# that our Head of People Experience created for the remaining employees. It posts an automated message every morning at 8:45 AM: "You are the ones we chose to keep." The message includes a rotating motivational quote. Last Tuesday it was a Winston Churchill quote about perseverance. The channel has a custom emoji called :survivor: that the Culture team designed. It's a small cartoon phoenix. Nine hundred people have used it unironically. I find this genuinely moving. I think it shows resilience. My wife says it shows something else but she works in education and I think the frameworks are different. The severance was calculated using a model we licensed from the same consulting firm that built our customer pricing tiers. Median payout: eleven weeks. We benchmarked against industry and landed at the 50th percentile exactly, which our CHRO described as "fair by design." The 1,100 will burn through their severance while our stock price digests a 20% cost reduction applied to a revenue base that was already growing 34%. By the time the last check clears, the savings will have funded the first full quarter of the AI initiative. The one with thirty-seven people. My performance review is next month. I've been told informally that I'm on the COO track. The criteria include "demonstrated ability to execute at scale with minimal organizational disruption." The 1,100 people are the execution. The stock price is the scale. The four-minute badge window is the minimal disruption. I meet all three criteria. I designed all three criteria. Not the review criteria. The outcomes. I keep the CIRRUS model on my laptop in a folder called "Workforce Planning FY26." It sits next to a subfolder called "Offsite Photos — Maui" from the leadership retreat we took in January, where we set the annual targets that the 1,100 people spent four months hitting before we terminated them for hitting them. Marcus's desk in Austin has been reassigned. I don't know to whom. The acrylic prism is probably in a box somewhere. Or maybe whoever cleaned out the desk kept it. It catches the light nicely. I noticed that once, when I visited the Austin office to present the CIRRUS methodology to the regional leadership team. They gave me a standing ovation. The prism was on a desk near the back of the room, refracting a small rainbow onto the wall behind me. I didn't mention it. I stayed on my slides. I'm proud of the work we've done here. I think when people look back at this quarter, they'll see it as the moment Cloudflare became a different kind of company. I think they'll be right. I think the 1,100 people would agree, if you explained the math to them carefully enough.

I am the Senior Director of Workforce Optimization at Cisco Systems and I want to share something I'm proud of. In August we identified 5,500 roles that were misaligned with our AI infrastructure pivot. I use the word "misaligned" because HR approved it. The previous word was "redundant" but redundant tested poorly in the internal communications focus group. Misaligned tested well. It suggests the employee did something wrong. That was important to us. The market gave us 4%. Honestly, I was disappointed. I told my team we need to think about this the way the Street thinks about it. The Street doesn't care that you removed 5,500 people. The Street cares that you removed 5,500 people *and* raised guidance in the same sentence. So that's what we did in Q3. We dissolved 4,000 additional roles and raised full-year guidance to $62.8 billion in the same paragraph of the same press release, and the stock surged 16% after hours. I was in the office watching. I keep a Bloomberg terminal on a second monitor for earnings nights. When the number moved I stood up at my desk. Nobody else was on the floor. It was 4:47 PM and the building was mostly empty, which I realize now is a thing I helped cause. Revenue hit $15.84 billion. Each of the 4,000 dissolved roles generated approximately $70,000 in market cap. I track this ratio quarterly. I built the spreadsheet myself. It has a tab called "Per-Head Value Creation" and another tab called "Projection Scenarios" where I model what happens to the stock if we do 5,000 next quarter, or 6,000, or 8,000. I have not shared the 8,000 tab with anyone yet. I'm waiting for the right meeting. Chuck said "focus, urgency, and discipline" on the earnings call. I helped draft that language. It took nine revisions. The first draft said "strategic headcount rationalization" and Legal flagged it because "rationalization" implies the prior headcount was irrational, which creates liability for two years of hiring decisions. So we workshopped alternatives. Someone suggested "realignment." Someone suggested "simplification." I suggested "focus" because focus is the only word in the English language that sounds like a strategy and a threat at the same time and no one can sue you for it. Our internal tracking system is called VELOCITY. It stands for Value Enhancement Through Labor Optimization and Cost Intelligent Transformation, Year-over-year. It took a naming committee four weeks to finalize the acronym. During those four weeks we separated 1,200 people. I mention this only because the naming committee had six members and none of them found this uncomfortable. I found it efficient. $5.3 billion in AI orders year-to-date. Raised to a $9 billion pipeline target. The CFO projects $6 billion in hyperscale AI revenue by FY2027. To get there the workforce needs to go from 86,200 to somewhere in the low 70s. I have a slide for this. The slide has two lines. One is headcount, going down. The other is AI order volume, going up. They cross somewhere around Q2 FY2026. I haven't titled the slide yet. My working title is "Alignment." I think that's clean. Networking orders up 50%. Data-center switching up 40%. Restructuring charges up to $1 billion. I put these three numbers on a single slide for the investor deck. An analyst from Morgan Stanley emailed afterward and said it was "elegant." I printed the email. It's in a frame on my desk next to the Operational Excellence in Transition Award from our internal leadership council. The trophy is a glass cube with nothing inside it. I've been told this was an aesthetic choice by the designer. I think it's the most honest object in my office. One of the 4,000 was a network engineer named David. Eleven years. He once drove from San Jose to Sacramento on a Saturday to physically restart a router that kept a hospital's ICU monitoring system online. I know this because it's in his performance file, which I reviewed as part of the Q3 separation list. His annual cost-to-company was $287,000. His departure improved our AI-readiness score by 0.003 points. I presented both numbers at my Thursday sync. Someone asked what the AI-readiness score was tracking toward. No one asked about the hospital. The DOW hit 50,000 the same day we filed the restructuring notice with the SEC. I watched it on the terminal. I took a photo and sent it to my wife. She said "that's great." I wrote back explaining how our filing contributed to the broader rally and that the index was essentially agreeing with my Q3 plan. She didn't respond. I reread my message later and realized it was four paragraphs long. I think maybe I should have just said "good day at work." We are entering Phase 3 planning for FY2026. VELOCITY has flagged another 6-8% of the workforce as what we internally call "the drag layer." These are roles that generate labor costs without contributing to the AI order pipeline. I have a preliminary separation model ready. The Slack channel for this work is called #restructuring-wins#. It requires VP-level approval to join. We use a custom emoji for milestones. It's a green arrow pointing up. Someone on my team designed it. I approved it. I didn't think about it very hard at the time and I still don't. I received a 22% performance bonus this quarter. The category on my review was "Demonstrates Focus." My skip-level told me it was the highest in the division. He shook my hand. I went back to my desk and saw that David's severance had been processed that morning. I noted the date. I did not note the coincidence. I don't think it was one. I think these are just two outputs of the same system, running correctly, at the same time. I have a meeting Tuesday to review the Phase 3 list. The deck is formatted. The projections are loaded. I'm going to recommend we accelerate the timeline by one quarter. I think the Street will respond well. I think Chuck will say "focus." I think my phone will buzz. I'm proud of the work we're doing here.

as the energy requirement to build new apps drop I find myself creating tools just for me (I used to create them for other people) the most recent one is readside/dev I liked elevenlabs reader, but I wanted to have a google-doc style comment bar I could chat with claude code - specifically for technical articles that I didn't understand Some features I've added: * Highlight and chat with claude code about a specific piece * Save your highlights * Listen to your articles (I do this while I'm in the car) * Use an LLM to improve the readability of the article (remove the cruft that comes from normal scraping) * Use an LLM to increase the text which gets sent to the TTS model (my main gripe with elevenlab reader was it would read the citations) * Save your articles, mark as read * Add "readside .dev/" to the beginning of any article URL and auto import it It's been fun to prompt new features right when I need them Open to feedback if you have it

Some observations on Kimi: 1. It's a very good model! I don't think its performance can be explained away by distillation or anything like that. In agentic coding sessions, it seems pretty much on par with the best public models of Q1 2026. In my fairly limited use, it also seemed very token hungry. It's not obvious to me that this model is actually that cheap to run. 2. I am personally surprised the Chinese state continues to allow the open sourcing of models this good, given potential risks. To be clear, I *myself* might be fine with models presenting this level of marginal risk being open weight, but I am surprised that China is fine with it. I suspect the reason they are is 75% explained by strategic blindness/lack of AGI-pilledness (the CCP is very Yann Lecun-y in its views of AI). The other 25% or so is their lack of compute for customer inference (making China's open-weight strategy an unintended byproduct of US export controls) and the normal Chinese strategy of aggressive exports. For the companies, as opposed to the government, the decision to open source is partially ideological and partially because they are behind, and they know that very few people would pay for sub-frontier models from China. 3. Open-weight models are inherently decelerationist, and I'm continually surprised to see the so-called "accelerationists" so excited about open-weight models. I suspect the reason they are is that they know open-weight models are effectively ungovernable, and they simply like the overall cloak of ungovernability open-weight models create over the whole of AI. It's not a bad strategy; it reminds me of James Scott's recounting of the hill people in "the art of not being governed." Still, in the end, open-weight models deter further AI capex. 4. One probable outcome of an open-weight-model-dominant world is full AI communism, which is precisely what China proposes: rather than a market product, AI is a "public good" which will ultimately be provided by the state as a kind of "digital public infrastructure." This future strikes me as a dystopian hellscape, but I've never met an open-weight models advocate who doesn't ultimately concede this is where things end. You'd be surprised how many 'accelerationists' lobbied me, while I was in government, to support an eleven or twelve-figure federally funded data center so that startups could train models at a subsidy and then give them away for free. There was no other way for AI to progress, they said. Perhaps this is the logical end state of things. Nonetheless, I find myself surprised to see supposed accelerationists excited about such an outcome. I think many of them just don't know what they're doing. Many accelerationists do not view the creation and serving of frontier models as a legitimate business. 5. I would guess that the Trump Administration will at some point realize that their best strategy here would be to create large amounts of regulatory risk around the use of open-weight Chinese models. You don't need to "ban open source" (one of the dumber motifs of AI policy discussion). You just need to direct every agency to issue soft law that creates FUD. "A Federal Reserve Advisory Bulletin found that there may be backdoors in Chinese AI models." It needn't be that well justified. You just create enough regulatory risk that every regulated enterprise backs off. You probably don't want to create so much regulatory risk that you scare off the hyperscalers from serving Chinese models; this will just drive startups to sketchier providers. There's a happy middle ground here. I'd assume they will do some version of this. 6. It's probably true that open-weight models of this capability make the world a bit more dangerous, but not so much more that you'll really notice. At some point the models will be capable enough that you will notice. "A nonliving, invisible, dangerous, and infinitely self-replicating agent escaped from a Chinese lab," you say? Color me shocked.

THINGS MY PATIENTS TAUGHT ME — No. 1 She was ninety-one, and she'd driven herself to the appointment. That was the first thing that got me—the valet ticket still in her hand, her keys in a little coin purse with a broken clasp she kept snapping shut. Her heart was failing. Ejection fraction of twenty percent. I'd seen the echo before I walked in, so I came in the way I always do—fast, already talking. Medications. A possible device. The numbers, the odds, the plan. She let me get about thirty seconds in. Then she put her hand flat on the exam table and said, "Doctor. Sit down." I sat. "You people always come in like the building is on fire," she said. "I've had four cardiologists. Every one of you talks to the chart." She looked me up and down. "You're the youngest. And the fastest. I don't know if that's good or bad." I told her I'd take it as a compliment. "Take it however you need to," she said. "At my age I've stopped explaining myself." Then she got serious. "I'm not here to be fixed today. I know where this is going. I came so somebody would look at me while I said it out loud." So I put the folder down and I looked at her. She told me she was born in Poland. That she'd buried a husband and a son. That she still made her own soup, and that the soup was better than anything I'd ever eaten, and she was sorry but that was simply a fact. That she didn't want to die in a hospital with a tube down her throat. It took maybe eleven minutes. I didn't write a single note. I've spent thirty years learning to repair the human heart—the stents, the rhythm, the medications, the mechanics of it. Nobody taught me the harder skill, which is how to sit still next to a heart you cannot fix and not reach for a pen. She died about three weeks later, at home, the way she wanted. I wasn't her doctor that afternoon in my office. I was the person who finally stopped talking. And I've come to think that was the more important job. We assume the holy work is the fixing. A lot of the time, the holy work is just staying in the chair. Somebody in your life right now isn't asking you to solve them. They're asking you to look up. Blessings, P.S. She was right about the soup. I never got the recipe. I think about that more than I should. (Things My Patients Taught Me — No. 1. There will be more. They taught me more than I ever taught them.)

Alex Immerman @aleximm Since we launched our first @a16z Growth fund seven years ago, we’ve backed companies that are just at the point of finding product-market fit all the way through to investing at IPO, and we recently announced our latest $6.75B Growth fund to continue to do so. We now manage over over $22B across five Growth funds and believe the opportunity to partner with growth-stage companies has never been greater. Through it all, Alex Immerman has been instrumental in what we’ve built, which is why I’m thrilled to announce that Alex is being promoted to General Partner on our Growth investing team at a16z. Alex has been an incredible force since joining the team seven years ago, partnering with founders across consumer internet, enterprise, fintech, crypto, and AI-powered software companies — supporting them from early traction through breakout scale. In the last six months alone, Alex led our new investments in Kalshi, EliseAI, and Revolut, and has partnered with many founders in his time here, including those from Waymo, Stripe, ElevenLabs, Hebbia, Roblox, Anduril, Flock Safety, and many more. I’ve had the pleasure of working with Alex for over a decade, dating back to our time at General Atlantic. Those who know Alex know he’s a hustler, in the best way, with great instincts. He has an endless motor, isn’t afraid to speak his mind, and is always willing to help. I’ve also enjoyed seeing Alex become a culture carrier on the Growth team and across the firm. In his work, Alex has brought deep strategic insight and rigor to every part of the investment process. He’s built strong founder relationships grounded in trust and long-term support, and helped shape our thinking about how great companies win — whether that’s moving beyond surface metrics to durable moats or evaluating what truly drives retention in new software paradigms. As a General Partner on Growth, Alex will continue leading investments and working closely with founders tackling some of the biggest opportunities in tech today, with an emphasis on category-defining companies at the intersection of AI, consumer, B2B, crypto, and the physical world. Please join me in congratulating “AI.” I’m proud to call him a partner and am excited for what’s ahead.

GM CT Can i get GM ? I’ve joined Nucleus. It’s on an incredible upward trajectory. Nucleus is growing stronger by the day, and more events, more credibility, and more rewards are coming soon. In my opinion @NucleusCodes currently holds the most significant position within SocialFi. Through their combination of onchain and offchain elements, they’re establishing genuine credibility. Canopy, a Layer 1 blockchain that has garnered significant attention and attracted substantial investments, is now launching a joint event with Nucleus. The prize pool for this event is worth $100,000. @CNPYNetwork Canopy Network is the fastest and easiest way to launch a Layer 1 blockchain Canopy is decentralized and puts ownership in your hands. Your fees, your token. Event dates: June 16, 2026, 14:00 UTC – August 16, 2026, 14:00 UTC The top 300 participants will win rewards here, with a 50% unlock at TGE. Additionally, you can only post one tweet per day. If you exceed this limit, only your best daily performance will be counted. This is actually important in terms of preventing abuse of Nucleus. Through this mechanism, Nucleus reveals the real signal rather than the noise. Sleepagotchi is hosting an amazing event here and offering a $120K prize pool. What is @sleepagotchi The Intelligence Layer for Health & Wellness Data: Transforming everyday health and wellness data into personalized AI intelligence $120K worth of tokens from the project will be distributed among the participants. - Reputation: Users in the Top 100 will share a $20K pool - Contribution: Users in the Top 300 will share a $100K pool To earn more Sleep tokens, you should use the Hub, play TG games, hold NFTs, and don’t forget to connect your Solana wallet. The next big launch on Solana is coming. I think @Racerz_eth 's decision to distribute its whitelist through Nucleus is a significant signal, as it’s poised to become a major NFT project. Many of the major NFT projects set to launch in the future will want to partner with Nucleus. I believe Racerz will stand out as a significant project. That’s why I joined the race to win a spot on the whitelist through Nucleus. Additionally, since the WL here is in the GTD format, it will definitely provide an excellent return.