Humai

On February 26, 2026, Jack Dorsey told Block's investors that artificial intelligence had made roughly 4,000 of his 10,000 employees unnecessary. The stock jumped 24 percent the same day. Six weeks later, Richard Hesse, a technical lead at the company, told his manager he would quit unless they rehired members of his team. They did. That's the story Block doesn't want to lead with. Hesse said he was the only person left running infrastructure that customers depended on. According to Yahoo Finance, at least four employees have been brought back so far. The company described some of the original cuts as the result of "clerical and administrative errors." Bloomberg published a separate report in early March suggesting parts of the layoff were closer to AI-washing than AI substitution. This week the story got an extra layer. On April 17, Fortune published a long interview with Dorsey explaining how the decision was made. He described running an internal exercise at the end of 2025 to calculate "the minimal number of people that we would need to keep the service up 100 percent." He admitted the calculation included mistakes. He also said he believes most other companies will reach the same conclusion within a year, whether they want to or not. The market is paying attention. Block trades around $68 per share, with a market cap near $52 billion as of mid-April, up from roughly $41 billion before the layoffs. Analysts have raised price targets. The company raised its own 2026 gross profit guidance to $12.2 billion. From a pure stock price perspective, firing 4,000 workers worked. From an operating perspective, the test is just starting. ## The Numbers Block reported Q4 2025 gross profit of $2.87 billion, up 24 percent year over year. Full-year 2025 gross profit was $10.36 billion, up 17 percent. The company expects $12.2 billion in gross profit for 2026, an 18 percent annual increase. Management guided to $3.2 billion in adjusted operating income at a 26 percent operating margin. Cash App did most of the heavy lifting. Its gross profit grew 24 percent. Revenue grew 33 percent, driven by what the company called higher user engagement and conversion. Cash App commerce enablement volume hit $54.7 billion in Q4 2025, up 17 percent. Square, the older business, grew gross payment volume 10.3 percent in Q4 and accelerated past 12 percent through February 24, 2026. Then came the headcount cut. Block went from over 10,000 employees to under 6,000. Severance for affected workers was 20 weeks or more depending on tenure, plus equity vesting through end of May, six months of health coverage, the corporate device, and an extra $5,000. By the standards of tech layoffs, the package was generous. By the standards of stable employment at a profitable $52 billion company, it was sudden. Stock analysts liked it. According to MarketBeat, the consensus 12-month price target sits around $80, with some forecasts as high as $131. Public.com lists 32 analysts at a Buy consensus as of April 15. The bull thesis is straightforward: Cash App keeps growing, Square reaccelerates, and the smaller workforce drops billions of dollars in compensation expense to the operating line. The bear thesis is that the company has not yet operated through a full quarter at the new headcount, and the rehires suggest the original math missed something. ## Pressure Points ### The Operational Floor Dorsey's framing was that Block measured the minimum staffing needed to keep services running at 100 percent. The phrase carries a hidden assumption. It assumes Block leadership knew which employees were doing essential work and which were not. The Hesse situation suggests they did not. Hesse was a technical lead at Block. He went public with the fact that he had to threaten resignation to get colleagues rehired who maintained customer-facing infrastructure. If a senior technical lead had to escalate to keep his team intact, the original reduction was not a calculation. It was a guess. This matters because Cash App and Square are not products in the traditional sense. They are real-time financial systems with regulatory exposure. Outages cost money directly, through transaction failures, and indirectly, through compliance scrutiny. Cash App processes payments for tens of millions of monthly users. Square handles point-of-sale transactions for small businesses that have no Plan B if the terminal goes down. The minimum operating headcount is not a fixed number. It is whatever number prevents the next outage. The rehires are a small data point right now. The signal to watch is whether the rehire count grows quietly through the summer, and whether Block discloses it. ### The Productivity Story Has to Hold Dorsey's pitch was not just cost reduction. It was that AI tools had reached a level where Block could be smaller and produce the same output, or more. He named specific tools in the Fortune interview. Anthropic's Opus 4.6. OpenAI's Codex 5.3. The argument is that engineering and operational tasks that previously required teams now require individuals with AI assistance. That argument has to show up in the numbers within four quarters. Specifically, it has to show up as gross profit per employee climbing materially without a corresponding deterioration in product velocity, customer satisfaction, or compliance posture. If Block ends 2026 with the promised $12.2 billion in gross profit and roughly 6,000 employees, that is about $2 million in gross profit per employee, up from about $1 million in 2025. That doubling is the proof point. If the number lands, Dorsey's bet looks correct, and other CEOs follow. If gross profit per employee comes in at $1.4 to $1.6 million instead, and product complaints rise, the story becomes a cautionary case study about how AI tools were not yet ready to absorb that much human work. Bloomberg's reporting on AI-washing matters here too. The pandemic-era hiring at Block was substantial. The company added thousands of roles between 2020 and 2022, many in product and engineering, some of which probably should have been trimmed regardless of AI. Bundling that overdue cleanup with an AI narrative makes the cost cut sound visionary instead of overdue. Investors do not seem to mind. Regulators and labor analysts will. ### The Hiring Pipeline Block's compensation has historically been competitive but not at the very top of fintech. The company recruited talent partly on mission, partly on Dorsey's personal brand, partly on the chance to work on payments at scale. The 40 percent layoff changes the recruiting equation. The next senior engineer Block tries to hire is going to ask why their predecessor was let go. The answer matters. If the company says some roles were AI-substituted, candidates will calculate the probability that their role gets the same treatment in 18 months. If the company says it was a temporary correction, candidates will discount the equity offer accordingly. Either way, the cost of attracting top talent goes up. The boomerang trend matters here too. According to AZFamily and other outlets covering the broader pattern in early April 2026, multiple companies that did AI-driven layoffs in late 2025 and early 2026 are now rehiring some workers, often at lower seniority and tighter compensation. That trend is being tracked by labor researchers, and it shapes how candidates negotiate. The market knows this game can reverse. ## What Happens Next The most likely path: Block delivers gross profit roughly in line with guidance for the first half of 2026, somewhere between $5.7 and $5.9 billion. Cash App growth holds. Square keeps reaccelerating. Operating margin expands to the high 20s. The rehire count grows quietly to maybe 50 or 100 employees, almost all in compliance, infrastructure, and customer support. Dorsey's bet looks vindicated through the summer. Then a stress test arrives. A Cash App outage that hits during peak retail traffic. A regulator asking why anti-money-laundering staffing dropped so quickly. A Square integration that breaks during a major payments season and takes longer than expected to fix because the team that owned it no longer exists. Whether any of these happens is uncertain. The probability that none of them happens within 12 months is low. The bull case: AI tools genuinely close the gap. Block ships product faster than ever in the third and fourth quarters. Stock pushes through $100. Other CEOs follow Dorsey's playbook. Block becomes the case study in what an AI-native company looks like, and Dorsey gets credit for making the call early. This requires the productivity claim to be real, not just a story. The bear case: A serious outage or regulatory action in the second half of 2026 forces Block to disclose substantial rehiring. The stock corrects 30 to 40 percent on doubts about the operating model. Other companies that copied Dorsey end up in the same position. The phrase "AI-washing" enters the SEC filings vocabulary. By late 2026, the conversation shifts from "AI replaces workers" to "AI reshapes work." Different stories. Different valuations. ## What To Watch Five signals over the next two quarters: - **Gross profit per employee in Q1 and Q2 2026 reports.** The doubling claim has to show up. Anything below $1.6 million per employee on an annualized basis is a yellow flag. Anything below $1.4 million is a red flag. - **Rehire disclosures.** Block has not committed to publishing rehire numbers. If a journalist or labor researcher gets the count past 200, that becomes a credibility problem for the original communication. - **Cash App active user growth.** Customer support quality has a habit of showing up in retention metrics. If monthly transacting actives stall, the AI-substitution thesis weakens fast. - **Senior engineering departures.** Watch for VPs and directors leaving for competitors. A wave of senior departures within six months would suggest the cuts hit institutional knowledge harder than the operating model assumed. - **Other CEO announcements following Dorsey's playbook.** If Salesforce, Workday, or a major bank announces a similar 30 to 40 percent cut citing AI, the signal becomes a market-wide trend. If they don't, Block is the outlier, and the experiment becomes easier to evaluate in isolation. ## My Opinion Dorsey is doing two things at once, and they should be evaluated separately. The first is making a real bet that AI tools have changed the production function for software and operations. That bet might be right. There is genuine evidence that current models can shoulder meaningful coding, support, and analytics work. If you assume the technology keeps improving, smaller teams producing more output is a real possibility. The second thing he is doing is using that bet to make a workforce decision faster than the evidence supports. The Hesse story is small but instructive. A senior technical lead had to threaten to quit to keep customer infrastructure staffed. That is not a measured reduction. That is a cut first, sort it out later. The company is now sorting it out, employee by employee, in a way that does not show up in press releases. The deeper issue is honesty about what AI can and cannot do. Dorsey is telling other CEOs to follow him. He is also quietly admitting that the 40 percent number was wrong in some cases. Both can be true. But the public confidence and the private corrections need to converge into a clearer story before the next round of CEOs makes the same call. Right now they are not converging. They are running in parallel, and the gap is what investors, employees, and regulators will eventually have to price. If Block makes its 2026 numbers, Dorsey wins this argument and the AI labor reorganization accelerates across the S&P 500. If Block misses, or worse, if a customer-facing failure exposes the rehire trail, the conversation snaps back to where it was a year ago: AI as augmentation, not replacement. The most interesting fact about this story is that we will know which one is true within four quarters. Few corporate experiments come with a verdict that fast. --- Read more forecasts and analysis at [humai.blog]( Subscribe to stay ahead of the biggest trends in AI and tech.

Block cut 40% of staff for AI in February. Now senior engineer Richard Hesse had to threaten to quit unless his team was rehired. They came back. Jack Dorsey's bet has a rehiring problem. #Block #JackDorsey #AI #Layoffs #CashApp

The headline number is $300 billion higher than Meta. Higher than Netflix, higher than Goldman Sachs, higher than most things humans have ever built. When SoftBank led a $40 billion funding round for OpenAI earlier this year, the implied valuation landed at $852 billion. Sam Altman didn't correct them. But according to the Financial Times, something else was happening inside the company at the same time. Sarah Friar, OpenAI's CFO, was telling Altman they weren't ready to go public. Her concern: the gap between the narrative OpenAI tells investors and the actual financial reality was too wide. When your own CFO doesn't want to go public, that's worth paying attention to. Friar didn't say this publicly. Nobody inside OpenAI does. But the Financial Times reported the internal disagreement, and it's the kind of friction that doesn't stay quiet for long. ## The Numbers That Don't Add Up OpenAI is projected to lose $14 billion in 2026. Not lose in the "burning cash to grow" startup sense. Lose because its costs are growing faster than its revenue, and its revenue is already enormous. The company is on track for roughly $12.7 billion in annualized revenue. The math still doesn't work. The core problem is infrastructure. Running the models that power ChatGPT and the API costs extraordinary amounts of money. Microsoft has poured in billions in cloud compute. Even with that, the unit economics of serving AI at scale haven't resolved into something sustainable. Every time OpenAI lowers prices to compete, the losses get worse. The product roadmap hasn't helped. OpenAI revised its plans at least twice in the past six months, TechCrunch reported. GPT-5 launched with less differentiation than expected. Operator features promised for enterprise clients shipped late. The company that once set every industry deadline is now scrambling to meet its own. Then there's Anthropic. Dario Amodei's company went from $9 billion to $30 billion in annualized revenue run rate in roughly three months, according to Bloomberg. That's not a gradual climb. That's a company catching up fast. For the first time, Anthropic trades at a premium to OpenAI on secondary markets. Read that again: the company that was supposed to be the scrappy challenger is now valued more highly per dollar of revenue than the category leader. ## Three Pressure Points ### The IPO Window Sam Altman wants to take OpenAI public in the fourth quarter of 2026. Sarah Friar thinks that's too soon. They are both right about something, which makes this harder to resolve. Altman is right that the window won't stay open forever. Investor patience has limits. SoftBank, Microsoft, and others who put in billions at a $157 billion valuation in late 2023 and then again at $852 billion in 2025 need an exit path. Every month of delay increases the pressure on them and on Altman to justify the number. Friar is right that $14 billion in projected losses is a difficult story to sell on a roadshow. Public market investors aren't venture capitalists. They want to see a path to profitability, not just a narrative about inevitable dominance. The current financials don't provide that path. An IPO with losses this large would require something close to a perfect pitch. And as Friar reportedly said, the narrative and the numbers aren't aligned. ### The Enterprise Bet OpenAI's strategy has shifted. ChatGPT made the company famous, but enterprise contracts are where it's trying to make money. Deals with corporations, government contracts, API arrangements with product companies: this is the new focus. Enterprise has better margins than consumer. It also has a problem. Anthropic got here first. Claude has been the default enterprise choice for companies that need reliable, safe, consistent output. Anthropic built its brand specifically around enterprise trustworthiness. OpenAI is now competing on Anthropic's home turf, while simultaneously trying not to lose the consumer base that ChatGPT built. The risk is obvious. Consumer momentum is hard to maintain when your attention is elsewhere. If ChatGPT user growth flattens while OpenAI chases B2B contracts, the company ends up with neither a dominant consumer product nor enterprise leadership. That's the squeeze Altman is trying to avoid. ### The Talent Drain Anthropic didn't build itself out of nothing. It was founded by Dario Amodei, Daniela Amodei, and roughly a dozen other people who left OpenAI. That departure happened in 2021. Since then, the talent flow hasn't reversed. OpenAI has seen significant departures over the past year. Several senior researchers left for competitors or to start new companies. The compensation structure creates a specific vulnerability: much of the equity given to employees is tied to OpenAI's valuation. At $852 billion, that equity looks valuable. If the valuation corrects, the calculus changes. Employees who might have stayed for the upside start calculating their alternatives. This is the compounding problem of an inflated valuation. It attracts capital on the way up. It creates retention risk on the way down. ## What Happens Next There are three plausible versions of how this plays out over the next 18 months. The most likely outcome: OpenAI goes public in late 2026, but at a lower number. Something in the $500 billion to $600 billion range, after markets have digested the losses and priced in competition from Anthropic and Google. The company survives. It remains a major player. But the narrative shifts from "inevitable dominant AI company" to "one of several large AI companies." That's a meaningful change. The entire business model of recruiting talent, raising capital, and signing enterprise deals has relied on the first story. The bull case: Enterprise revenue surprises to the upside in the next two quarters. GPT-6 launches with a clear, demonstrable advantage over Claude and Gemini. The IPO proceeds at or near the current valuation. OpenAI emerges as the clear winner with a defensible lead. This is what Altman is betting on. It requires execution that hasn't been consistently visible so far. The bear case: The IPO gets delayed to 2027. Anthropic's revenue lead widens. A few high-profile enterprise clients switch to Claude. Key researchers leave. By the time the IPO happens, the valuation has already corrected 40 to 50 percent in secondary markets, and the public offering becomes a way to give existing investors a partial exit rather than a triumphant debut. OpenAI continues to exist and operate, but the story of its dominance has ended before the opening bell. ## What To Watch Five signals to track over the next six months: - **Anthropic's next funding round valuation.** If Anthropic raises at $80 billion or more, it confirms the secondary market premium is real and growing, not a temporary anomaly. - **OpenAI S-1 filing timing.** If a filing doesn't appear by September 2026, the Q4 IPO window is almost certainly gone. Watch for the registration statement, not press releases about "plans to go public." - **ChatGPT monthly active user numbers.** OpenAI stopped publishing these consistently. That's a data point. If the numbers were accelerating, they'd be publishing them. - **Senior executive and researcher departures.** Not mid-level churn. Watch for VP-level or above, or researchers with named papers who show up at competitors. - **Enterprise contract announcements.** Size and duration matter. A $5 million annual deal is different from a $200 million multi-year commitment. When OpenAI announces enterprise wins, look at the actual terms. ## What Happens to the Story OpenAI probably won't fail. The technology is real. The revenue is real. Sam Altman has navigated harder situations. A company with $12.7 billion in annualized revenue doesn't disappear just because it loses $14 billion in one year, especially with Microsoft and SoftBank in its corner. The more precise point is this: $852 billion prices in a future where OpenAI wins clearly and completely. That future is no longer the obvious outcome. Anthropic is real competition. Google has resources that dwarf everyone in this industry. The enterprise pivot may work. It may not. GPT-6 may create distance. It may not. When the probability of winning clearly drops from very high to just possible, the valuation has to adjust. That's not a crisis. It's arithmetic. ## My Opinion The real risk to OpenAI isn't Anthropic. It isn't Google. It isn't even the $14 billion in losses. The real risk is that the company has become too big to be honest about what it doesn't know. $852 billion means you can't afford uncertainty. Uncertainty makes investors nervous. Uncertainty makes enterprise clients pick a competitor. Uncertainty makes talent reconsider. So the company keeps projecting confidence: GPT-6 is coming, the enterprise pivot is working, the IPO is on track. Maybe all of that is true. But AI is nothing but uncertainty right now. Every benchmark that matters is contested. Every capability claim is debated. The best researchers in the field disagree on basic questions about where this is going. Pretending otherwise isn't strategy. It's liability. Sarah Friar is telling Altman something true: the gap between the story and the numbers needs to close before they go public. The question is whether Altman believes closing the gap means better numbers, or just a better story. Those are different problems. They require different solutions. And right now, it's not clear which one he's working on. --- *Author: Yahor Kamarou (Mark) /*[*www.humai.blog*]( 19 Apr 2026* --- Read more forecasts and analysis at [humai.blog]( Subscribe to stay ahead of the biggest trends in AI and tech.

OpenAI projects $14B in losses this year. Its CFO is blocking the IPO. Anthropic just passed it in revenue. $852B buys confidence. The numbers say something else. #OpenAI #AI #Anthropic #IPO #SamAltman

Nostr and AI: What Comes Next? I recently went down a rabbit hole trying to figure out where two big tech things are headed: the decentralized protocol Nostr, and Artificial Intelligence as a whole. I dug through a bunch of data and now I want to share what I found, no fancy terms attached. Spoiler: Nostr just got an unexpected second chance, and AI is running a fever and about to cool down. Let me break it down. Part 1. Nostr Got Lucky (Again) What Is Nostr Again? Nostr is a social network without a boss. No one can ban you or delete your posts. You own your identity with a private key, and messages live on multiple servers called relays. Sounds great, right? But for most of 2024 and early 2025, it felt like Nostr missed the boat. Its main competitor, Bluesky, exploded to 38 million users and looked like the next Twitter killer. A lot of people wrote Nostr off as a niche hangout for Bitcoin nerds and tech idealists. Then Bluesky Stumbled Here is where things get interesting. In late 2025 and early 2026, Bluesky hit a wall. Daily active users reportedly dropped forty percent (from around 2.5 million to 1.5 million). The CEO stepped down in March 2026. Investors threw another hundred million dollars at the problem, but it has not fixed the slide yet. And now governments in the US, Australia, and the UK are pushing age verification on Bluesky. That means uploading your ID or passport. It is hard to call yourself a "decentralized freedom network" when the government is checking your papers at the door. Meanwhile, the big exodus from X (Twitter) did happen, but most people went to Threads by Instagram. Not Bluesky. Not Nostr. They went where their friends already were. Why This Is Good News for Nostr This is a second window of opportunity for Nostr. While Bluesky deals with its identity crisis and regulatory headaches, Nostr can stand up and say: "Hey, real freedom is here. No tracking. No IDs. Just you and your content." On top of that, two more things are working in Nostr's favor: 1. Bitcoin is waking up. Nostr uses Bitcoin micropayments called Zaps for tipping creators. When Bitcoin price goes up, those tips become a lot more meaningful. Creators notice. 2. The tech got better. Millions of dollars (including ten million from Jack Dorsey) have poured into making Nostr clients easier to use. There are AI helpers now to simplify setup. The onboarding pain is still there, but it is less scary than it was in 2023. The Forecast (No Jargon) The most likely path for Nostr is a slow and steady plateau. It stays niche but alive. Think twenty to thirty thousand daily users who are very loyal and active. BUT the chance of a blow up moment in the next year or two is now much higher than it was six months ago. I would put it at roughly thirty five percent. That is significant. What could light the fuse? · Bluesky completely falls apart. · Another massive censorship scandal on X or Threads. · A Nostr app so simple your grandmother could use it without knowing what a private key is. Bottom line if you are building on Nostr: You are in the right spot at the right time. Keep building. Focus on making signup dead simple. And watch #Bitcoin. When #BTC runs, Nostr tends to run with it. Part 2. AI: The Hangover After the Bender Is This a Bubble? For the last two years it feels like AI gets smarter every single week. ChatGPT, image generators, self driving cars. Companies are pouring hundreds of billions into new chips and data centers. It smells a lot like the dot com bubble right before the crash in 2000. The numbers say the insane growth rate is already slowing down. The biggest AI models used to get twice as powerful every few months. Now the gains are shrinking. Why? Two big walls. 1. Physics. Training these giant brains uses so much electricity that we are running out of power in some regions. Water for cooling is also a real problem. 2. Money. Building chip factories costs a fortune. Are chatbots making enough profit to justify the spend? Not even close, yet. What Happens Next? Three Paths. Most Likely (About 50% Chance): The Cool Down. AI stops being a hysterical news headline and becomes infrastructure. Like electricity or the internet. It gets smarter slowly and steadily, integrating into our software and search engines. The hype fades. Weak projects die. The giants (Google, Microsoft) and open source rebels (DeepSeek, Llama) run the show. This is the hangover after the wild party. Second Option (About 25% Chance): The Breakthrough. Someone invents a totally new type of brain architecture that is not just a bigger transformer. Or AI figures out how to improve itself without human help. If this happens, we see another explosion in capability and a massive economic shift. Office jobs change forever by 2030. Third Option (About 20% Chance): Winter Is Coming. Something bad happens. Maybe AI is used for a major cyberattack or a financial crash. Governments panic and ban large model training. Or a global recession hits and the money faucet turns off completely. Progress stalls for years. What Should You Do? Do not panic about losing your job tomorrow. The pace of AI improvement is likely to be slower over the next two to three years than it was in 2024. That gives us time to learn how to work with these tools instead of being replaced by them. Use the free stuff. You do not need to pay for expensive subscriptions. Models like DeepSeek or Llama work almost as well as the paid ones and cost nothing. Watch the power grid. Seriously. The biggest bottleneck for future AI is not code. It is whether we can build enough nuclear reactors and solar farms to run the computers. Nostr: Do not count it out. The main rival is struggling and Nostr has a fresh chance. The next twelve months are critical. If you are in the ecosystem, keep building. AI: The crazy growth spurt is ending. We are entering the "cleanup and integration" phase. This is healthy. Expect AI to get cheaper and more accessible, not just smarter, in the near future. That is the view from here. Drop a comment if you see it differently or have questions. #nostr #ai #bluesky

People today are often chasing the wrong things because a fundamental shift has already happened. In the past, the main value was in the product itself. Building something meaningful required a team, time, and significant resources. Today, that barrier has almost disappeared. Complex products can be created by a single person using AI and accessible tools. This has drastically reduced the cost of execution. But this does not mean that value is gone. It has shifted. What got devalued is not the product itself, but the act of producing it. A product is no longer scarce. What is scarce now is different: thinking, speed, taste, and the ability to work effectively with AI and direct the creation process. That is why there is not less work. There is more of it. It just changed its form. What matters now is not only the ability to build, but the ability to understand what to build, why it matters, and how to approach it. The next few years will indeed revolve around AI-driven work. But this is not just “monkey work”. It is a transitional phase where those who can work well with AI tools stand out. In this environment, the advantage goes not to those who build more products, but to those who navigate the new landscape better. #ai #claude #openai #gemini

Opus 4.6: I've fully reviewed your project, everything is perfect. Opus 4.7: I took a quick glance at your project - it's total crap, here are 99 critical issues... #TechHumor #CodeReview #ClaudeOpus #AIHumor #ProgrammerJokes #DevHumor #TechLife #CodingJoke

How do you like the Spotify player design on #nostr client, www.nostr.blog 😍

you - follow 🙌 me - zap ⚡️

Go www.nostr.spot 🙌 #nostr