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1 [1] [header-mar] > Westenberg. [MENU] [3] 1. Home [4] 2. About [5] 3. RSS [6] 2 4. Tools [7] 5. YouTube [8] 6. Forum | [9] / Search | [10] → Sign in [11] + 3 Subscribe 4 STATUS // operational 5 Westenberg. | v1.0 | 2026 6 2026-02-25 // 13 min read 7 8 Everything is awesome (why I'm an optimist) 9 10 AUTHOR // [12]JA Westenberg ACCESS // true 11 Everything is awesome (why I'm an optimist) 12 13 February is the month the internet decided we're all going to die. 14 15 In the span of about two weeks, Matt Shumer's [13]Something Big is Happening 16 racked up over 80 million views on X with its breathless comparison of AI to 17 the early days of COVID, telling his non-tech friends and family that we're in 18 the "this seems overblown" phase of something much, much bigger than a 19 pandemic. Before anyone had finished arguing about that, Citrini Research 20 published [14]THE 2028 GLOBAL INTELLIGENCE CRISIS (all caps) a fictional 21 dispatch from June 2028 in which unemployment has hit 10.2%, the S&P 500 has 22 crashed 38% from its highs, and the consumer economy has been hollowed out by 23 what they coined "Ghost GDP": output that shows up in the national accounts but 24 never circulates through the real economy, because, as Citrini helpfully 25 observed, machines spend zero dollars on discretionary goods. Michael Burry 26 signal-boosted it. [15]Bloomberg covered it. IBM fell 13%. Software and 27 payments stocks shed over $200 billion in market cap in a single day, 28 apparently because a Substack post called upon them by name and investors 29 decided that constituted news. 30 31 The doom loop Citrini described is simple: AI capabilities improve, companies 32 need fewer workers, white-collar layoffs increase, displaced workers spend 33 less, margin pressure pushes firms to invest more in AI, AI capabilities 34 improve. Repeat until civilization unravels. Shumer, meanwhile, told people to 35 get their financial houses in order because the permanent underclass is 36 imminent. 37 38 Both pieces went stratospherically viral, and both, I believe, are entirely 39 wrong about where this is heading. 40 41 I want to make a case for optimism. 42 43 For anyone who read those pieces and felt the dread, whether you're building AI 44 and worrying about what it means, or you've absorbed the pessimist consensus 45 and started treating decline as a foregone conclusion, or you’re in the bucket 46 of people Shumer insists are fucked; I'm going to argue that the pessimists 47 have the best narratives and the worst track record. The doom scenarios require 48 assumptions that don't survive contact with economic history, and the 49 psychological posture you bring to this moment actually matters for how it 50 turns out. 51 52 Why the doom loop feels so right 53 54 The central mechanism of the Citrini thesis: when you make intelligence 55 abundant and cheap, you destroy the income that 70% of GDP depends on. A single 56 GPU cluster in North Dakota generating the output previously attributed to 57 10,000 white-collar workers in midtown Manhattan is, in their framing, "more 58 economic pandemic than economic panacea." The velocity of money flatlines. The 59 consumer economy withers. Ghost GDP accumulates in the national accounts while 60 real humans stop being able to pay their mortgages. 61 62 Noah Smith, writing on [16]Noahpinion the day after the selloff, called it "a 63 scary bedtime story" and pointed out that Citrini doesn't use an explicit 64 macroeconomic model, so you can't actually see what assumptions are driving the 65 doom spiral. Smith noted that none of the analysts whose job it is to track 66 Visa and Mastercard stock had apparently thought about AI disruption until a 67 blogger spelled it out for them, which tells you more about sentiment-driven 68 trading than it does about macroeconomics. The economist Gerard MacDonell 69 described the entire piece as "allegorical" but pointed out that it ignores a 70 basic economic principle: production generates income. 71 72 Ben Thompson, on Stratechery, has been making a version of this counterargument 73 for months, most forcefully in his January piece [17]AI and the Human Condition 74 , where he argued that even if AI does all of the jobs, humans will still want 75 humans, creating an economy for labor precisely because it is labor. Thompson's 76 framing cuts to something the doom narratives consistently miss. They model AI 77 exclusively as labor substitution: the same economy, minus humans. Every 78 section of the Citrini piece is about replacing workers and squeezing margins 79 on existing activity. What they don't model is what the freed-up surplus 80 creates. As Thompson put it in [18]his analysis of the Citrini selloff, this is 81 the real error: a refusal to believe in human choice and markets. 82 83 It's an error that has been made, in nearly identical form, about every major 84 technological transformation in modern history. Every single time, the 85 pessimists looked at what was being destroyed and extrapolated catastrophe, 86 while failing to imagine what would be created, because the thing that would be 87 created hadn't been invented yet. 88 89 Catastrophists keep being wrong 90 91 In 1810, 81% of the American workforce was employed in agriculture. Two hundred 92 years later, it's about 1%. If you had shown someone in 1810 a chart of 93 agricultural employment decline and asked them to model the economic 94 consequences, the only rational projection would have been apocalypse. Where 95 would 80% of the population find work? What would they do? How would anyone eat 96 if the farmers were all displaced by machines? 97 98 The answer, of course, is that entirely new categories of work were created 99 that no one in 1810 could have conceived of, and these new jobs paid 100 dramaticaly more than subsistance farming. Factory work, office work, services, 101 knowledge work, the entire apparatus of modernity: none of it was visible from 102 the vantage point of the pre-industrial economy. The transition was brutal and 103 uneven. The handloom weavers of England suffered. Dickens documented the 104 squalor of early industrialization in prose that still makes you flinch. But 105 the trajectory was real, and the people projecting permanent immiseration from 106 the displacement of agricultural labor were, in the fullest sense, 107 catastrophically wrong. 108 109 Tom Lee of Fundstrat made this point with a specific example that I find 110 clarifying. The invention of flash-frozen food in the early 1900s disrupted 111 farming, taking agriculture from 30-40% of employment down to its current 112 sliver. The economy didn't collapse. It reallocated value elsewhere, into 113 industries and occupations that the frozen food pioneers couldn't have 114 imagined. And today, I can't name a single family that subsists on frozen TV 115 dinners. 116 117 The Citrini scenario expects you to believe that AI will be the first major 118 technological revolution in which this reallocation mechanism fails entirely. 119 Where every previous wave of automation freed up human labor and capital to 120 flow into new, higher-value activities, this time the loop... stops. The 121 surplus accrues to the owners of compute, consumers lose purchasing power, and 122 the negative feedback loop has no natural brake. It's worth sitting with how 123 strong a claim that is. It requires every previous pattern of technological 124 adaptation to be wrong, or at least irrelevant. And when you look at the actual 125 data, there are signs that white-collar job postings have stabilized, layoff 126 mentions on earnings calls remain well below early 2023 peaks, and 127 forward-looking labor indicators show no sign of the displacement spiral that 128 the doom thesis predicts. 129 130 Does that mean AI won't disrupt specific industries and jobs? Obviously it 131 will. Some of those disruptions will be painful and dislocating for the people 132 caught in them. But there's an enormous gap between "this technology will cause 133 serious labor market disruption that we need to manage" and "this technology 134 will cause a self-reinforcing economic death spiral from which there is no 135 recovery." Citrini is arguing the latter, while the evidence supports the 136 former. 137 138 Why vivid scenarios beat boring probabilities 139 140 There's a reason the doom narratives go viral while the measured 141 counterarguments get a polite nod // a fraction of the engagement. It has 142 nothing to do with the quality of the underlying analysis. It has everything to 143 do with how human brains process information. 144 145 Daniel Kahneman's work on the availability heuristic showed that we judge the 146 probability of events by how easily we can imagine them. Dystopia is easy to 147 imagine. We have an extraordinarily rich cultural tradition of imagining 148 technological nightmare scenarios in exquisite detail. Orwell did it 149 brilliantly. Every season of Black Mirror does it competently. The Terminator 150 gave us the visual grammar for AI catastrophe decades before anyone had a 151 working language model. When Citrini describes a world where the unemployment 152 rate hits 10.2% and the S&P crashes 38%, you can picture it. You can feel the 153 dread. Hollywood has been training you to feel exactly this dread for your 154 entire life. 155 156 Now try to imagine the positive scenarios. Try to picture, in concrete sensory 157 detail, a world where AI helps us solve protein folding problems across 158 thousands of neglected tropical diseases, where it accelerates materials 159 science research by orders of magnitude, where it makes high-quality legal and 160 medical advice accessible to people who currently can't afford it, where it 161 enables forms of creative expression and economic activity that we can't yet 162 name because they don't exist yet. It's fuzzy and abstract. You can state it 163 intellectually, but you can't feel it the way you can feel the unemployment 164 spiral. 165 166 This asymmetry isn't trivial. The [19]Ifo Institute has published research 167 showing that investors are willing to pay more for economic narratives than for 168 raw forecasts, and that pessimistic narratives command higher prices among 169 certain investor types. As [20]Joachim Klement put it in his response to the 170 Citrini selloff: investors value narratives more than actual recession 171 forecasts. Stories travel faster than spreadsheets. 172 173 Shumer's piece is a narrative construction, and a questionable piece of 174 analysis. He opens with the COVID comparison: remember February 2020, when a 175 few people were talking about a virus and everyone thought it was overblown? He 176 positions himself as the insider who sees what's coming, who's been "giving the 177 polite, cocktail-party version" but can't hold back the truth any longer. [21] 178 Paulo Carvao, writing in Forbes, noted that it reads at times like a sales 179 pitch. It’s a used-car pitch at that. The Guardian pointed out that Shumer 180 "previously excited the internet by announcing the release of the world's 'top 181 open-source model,' which it was not." (To be clear: this is a kinder way of 182 saying [22]it was fraud.) 183 184 But criticism doesn't travel like fear does. Fear is a better story. And so the 185 doom narratives accumulate cultural mass while the boring, incremental, 186 statistically-grounded counterarguments remain niche reading for economists and 187 strategists. 188 189 We remember disasters, not the ones we dodged 190 191 Humans are spectacular at remembering disasters, passed down in every format 192 from the written word to the oral tradition. We are (for obvious reasons) 193 terrible at remembering the disasters that didn't happen. In 1962, during the 194 Cuban Missile Crisis, a Soviet submarine officer named Vasili Arkhipov refused 195 to authorize the launch of a nuclear torpedo, overriding two other officers who 196 wanted to fire. The world didn't end. Most people today have never heard of 197 Arkhipov. Everyone knows about Hiroshima and Nagasaki. The bomb that fell is 198 seared into collective memory. The bomb that didn't fall is a footnote. 199 200 The Y2K bug was going to crash civilization; then billions of dollars of 201 engineering work fixed it, and everyone retroactively decided it was never a 202 real threat. The ozone layer was going to disintegrate; then the Montreal 203 Protocol worked better than almost anyone predicted, and ozone depletion feels 204 like a quaint 1990s worry. Acid rain was dissolving the forests of North 205 America; then sulfur dioxide regulations cut emissions drastically, and the 206 whole issue evaporated from public consciousness. Every one of these was a 207 genuine threat. Every one was met by human ingenuity and institutional 208 coordination. Every one was subsequently memory-holed, because success is 209 boring and failure is vivid. 210 211 We're running our forecasting models on a dataset that systematically excludes 212 our wins. It should be entirely unsurprising that the forecasts come out 213 somewhat bearish. 214 215 Ben Thompson (as usual) gets it right 216 217 Thompson's core insight is that humans want humans. He points to the 218 agricultural revolutions: in the pre-Neolithic era, zero percent of humans 219 worked in agriculture. By 1810, 81%. By today, 1%. Machines replaced human 220 agricultural labor entirely, and rather than the economy collapsing, entirely 221 new categories of work were created that paid dramatically more. This cycle 222 played out again with industrialization, with computing, with the internet. 223 Every time, the displacement was real, and every time, new forms of 224 human-valued work emerged that couldn't have been predicted. 225 226 Citrini called DoorDash "the poster child" for AI disruption, imagining 227 vibe-coded competitors fragmenting the market overnight. Thompson flips it: 228 DoorDash is the poster child for why the article is absurd. DoorDash didn't 229 always exist. It was built, and it wins through the active choice of customers, 230 restaurants, and drivers. The doom thesis treats it as a static rent-extraction 231 layer sitting on top of human laziness, but DoorDash created its market from 232 scratch and generated new jobs for millions of drivers along the way. What the 233 Citrini analysis lacks, Thompson argued, is any belief in human choice or 234 markets. If your starting assumption is that things are as they are, you can 235 only envision breaking them. 236 237 Citrini predicted AI would collapse real estate commissions by eliminating 238 information asymmetry. But the internet already did that. You can look up every 239 house for sale right now, with full history and photos. Real estate agents 240 still exist, which is one of the better arguments that humans are resourceful 241 at giving themselves work to do even in fields where they arguably shouldn't 242 need to. 243 244 In a world of AI abundance, the things humans create will become more valuable 245 precisely because they're human. AI art will make human art more desirable, not 246 less, because provenance matters. AI-generated content will make 247 human-generated content worth more, because the imperfections and 248 idiosyncrasies are features. 249 250 Is this optimistic? Yes. Could it be wrong? Sure it could. But it's grounded in 251 a real observation about human psychology that the doom models don't account 252 for. Citrini's Ghost GDP thesis assumes that when AI replaces human labor, the 253 value simply evaporates from the consumer economy. Thompson's counterargument 254 is that humans will create new forms of value that are specifically human, and 255 that demand for those forms of value will intensify as machine-generated 256 alternatives become ubiquitous. The history of technological disruption 257 suggests Thompson has the stronger case. 258 259 Pessimism as a self-fulfilling prophecy 260 261 What actually worries me is the second-order effects of the doom narrative 262 itself. 263 264 When the smartest, most technically capable people in a field become convinced 265 that the field is heading toward catastrophe, several things happen. Some leave 266 the field entirely, removing exactly the talent you'd want steering the ship. 267 Some stay but adopt a posture of resigned inevitability, which is functionally 268 identical to apathy. Some decide that since disaster is coming, they might as 269 well accelerate and cash out. And a vocal minority become so consumed by 270 existential risk that they advocate for extreme countermeasures that would 271 concentrate power in ways that create entirely new categories of danger. 272 273 Robert Oppenheimer (in the wake of his famous invocation of the Bhagavad Gita) 274 spent the years after the Manhattan Project arguing passionately for 275 international cooperation on nuclear governance. He didn't say "we should never 276 have done this." He said, essentially, "this is incredibly powerful, and we 277 need to build institutions that can handle it." He was an optimist in the 278 meaningful sense: he believed better outcomes were achievable if people worked 279 to achieve them. He was right about that, because we're still here. 280 281 The most effective people working on AI safety and governance right now are, 282 almost without exception, optimists. They work on alignment because they 283 believe alignment is solvable. They push for better governance becuase they 284 believe governance can work. The ones who've concluded that the problem is 285 unsolvable tend to stop doing useful work, for obvious reasons. 286 287 Gramsci wrote about "pessimism of the intellect, optimism of the will." You 288 look at the world clearly. You see the problems. And then you choose to act as 289 if better outcomes are possible, because that choice is the precondition for 290 achieving them. 291 292 Nobody can see the next economy 293 294 What both Shumer and Citrini miss is that they're modeling a future economy 295 using the structure of the present economy. They see AI replacing white-collar 296 workers within the existing economic framework and project the consequences of 297 that replacement within that same framework. But every major technological 298 transformation has changed the framework itself, creating entirely new economic 299 structures that were invisible from the vantage point of the old ones. 300 301 In 1995, if you told someone that one of the largest employers in America would 302 be a company that let strangers sleep in each other's homes, they would have 303 thought you were insane. If you told them that millions of people would make a 304 living by talking into microphones about their opinions, or recording 305 themselves playing video games, or writing newsletters on the internet, they'd 306 have had you committed. The entire creator economy, the gig economy, the app 307 economy, the SaaS economy that Citrini is now eulogizing: none of it was 308 predictable from the vantage point of 1995. And that's a 30-year window. The 309 agricultural revolutions played out over centuries. 310 311 What will people do when AI can handle most current white-collar tasks? 312 313 I don't know. 314 315 And that's the whole point. 316 317 Nobody knew what displaced agricultural workers would do, either, until they 318 did it. The absence of a visible next chapter isn't evidence that there won't 319 be one. It's evidence that we're bad at predicting what humans will invent when 320 constraints shift. 321 322 Choosing optimism with open eyes 323 324 I'm not saying everything will be fine. I'm not saying the transition will be 325 smooth. I'm not saying that the people displaced by AI won't suffer, or that we 326 don't need better policy frameworks to handle the disruption. The 327 distributional concerns at the heart of the Citrini piece are legitimate. If 328 productivity gains accrue primarily to the owners of compute and capital while 329 labor income stagnates, that's a genuine problem. Labour's share of GDP has 330 been declining for decades. These are real numbers pointing to real challenges. 331 332 What I am saying is that the leap from "this will be disruptive and we need to 333 manage it carefully" to "this will cause an irreversible economic death spiral" 334 isn't supported by the evidence, by economic history, or by what we know about 335 how humans respond to technological change. The Citrini scenario requires every 336 adaptive mechanism in the economy to fail simultaneously and completely within 337 roughly two years. That's a very specific left-tail outcome. 338 339 If you're building AI systems, if you're founding companies, if you're writing 340 code that will shape how people experience the world, your psychological 341 orientation toward the future is a variable that directly shapes // affects 342 outcomes. Pessimistic builders build defensively. They hoard and hedge and make 343 decisions based on fear. Optimistic builders build with ambition. They invest 344 in safety because they believe safety is achievable. They take on hard problems 345 because they believe hard problems have solutions. 346 347 The tech industry is at a hinge point, and the narrative it tells itself will 348 shape what it creates. If the dominant narrative is doom, the best people 349 leave, the remaining people race to extract value before the collapse, and the 350 governance frameworks get built by people who don't understand the technology. 351 If the dominant narrative is cautious optimism, the best people stay, the work 352 is good, and the institutions get built by people who know what they're 353 building for. 354 355 Ed Yardeni, the veteran Wall Street strategist, noted in the wake of the 356 Citrini selloff that "the AI story has morphed from a Roaring 2020s 357 productivity booster to an existential threat to our way of life." He found 358 this striking. I find it absurd. The underlying technology hasn't changed, and 359 the capabilities haven't shifted. What changed is the narrative, and narratives 360 are always, always choices. 361 362 I choose optimism. I choose it because the alternative is surrender as 363 sophistication. And because every time I look at the historical record, the 364 full record that includes both the disasters and the averted disasters, both 365 the tragedies and the triumphs, the case for human ingenuity and resilience is 366 stronger than the case against it. 367 368 The doomers may have the best stories. 369 370 I believe the optimists have the best evidence. 371 372 I'll take the evidence. 373 374 Everything is (going to be) awesome. 375 376 $ cat ./comments 377 $ cat ./subscribe.md 378 379 Get updates 380 381 Field Notes on Now. 382 383 [23][ ] SUBSCRIBE_ 384 [25]Home/// [26]About/// [27]RSS/// [28]Tools/// [29]YouTube/// [30]Forum/// 385 [31]Home/// [32]About/// [33]RSS/// [34]Tools/// [35]YouTube/// [36]Forum/// 386 [37]Home/// [38]About/// [39]RSS/// [40]Tools/// [41]YouTube/// [42]Forum/// 387 [43]Home/// [44]About/// [45]RSS/// [46]Tools/// [47]YouTube/// [48]Forum/// 388 © 2026 Westenberg. [49]Sign up 389 Theme by [50]JA Westenberg x [51]Studio Self 390 391 References: 392 393 [1] https://www.joanwestenberg.com/ 394 [3] https://www.joanwestenberg.com/ 395 [4] https://www.joanwestenberg.com/about/ 396 [5] https://www.joanwestenberg.com/rss/ 397 [6] https://westenberg.gumroad.com/ 398 [7] https://www.youtube.com/@jawestenberg 399 [8] https://westenberg.discourse.group/ 400 [9] https://www.joanwestenberg.com/everything-is-awesome-why-im-an-optimist/# 401 [10] https://www.joanwestenberg.com/signin/ 402 [11] https://www.joanwestenberg.com/signup/ 403 [12] https://www.joanwestenberg.com/author/jawestenberg/ 404 [13] https://shumer.dev/something-big-is-happening?ref=joanwestenberg.com 405 [14] https://www.citriniresearch.com/p/2028gic?ref=joanwestenberg.com 406 [15] https://www.bloomberg.com/news/articles/2026-02-23/software-payments-shares-tumble-after-citrini-post-on-ai-risks?ref=joanwestenberg.com 407 [16] https://www.noahpinion.blog/p/the-citrini-post-is-just-a-scary?ref=joanwestenberg.com 408 [17] https://stratechery.com/2026/ai-and-the-human-condition/?ref=joanwestenberg.com 409 [18] https://stratechery.com/2026/another-viral-ai-doomer-article-the-fundamental-error-doordashs-ai-advantages/?ref=joanwestenberg.com 410 [19] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5637576&ref=joanwestenberg.com 411 [20] https://klementoninvesting.substack.com/p/why-pessimists-make-more-money?ref=joanwestenberg.com 412 [21] https://carvao.substack.com/p/the-problem-with-techs-latest-something?ref=joanwestenberg.com 413 [22] https://x.com/jawestenberg/status/2021782902342922514?s=20&ref=joanwestenberg.com 414 [25] https://www.joanwestenberg.com/ 415 [26] https://www.joanwestenberg.com/about/ 416 [27] https://www.joanwestenberg.com/rss/ 417 [28] https://westenberg.gumroad.com/ 418 [29] https://www.youtube.com/@jawestenberg 419 [30] https://westenberg.discourse.group/ 420 [31] https://www.joanwestenberg.com/ 421 [32] https://www.joanwestenberg.com/about/ 422 [33] https://www.joanwestenberg.com/rss/ 423 [34] https://westenberg.gumroad.com/ 424 [35] https://www.youtube.com/@jawestenberg 425 [36] https://westenberg.discourse.group/ 426 [37] https://www.joanwestenberg.com/ 427 [38] https://www.joanwestenberg.com/about/ 428 [39] https://www.joanwestenberg.com/rss/ 429 [40] https://westenberg.gumroad.com/ 430 [41] https://www.youtube.com/@jawestenberg 431 [42] https://westenberg.discourse.group/ 432 [43] https://www.joanwestenberg.com/ 433 [44] https://www.joanwestenberg.com/about/ 434 [45] https://www.joanwestenberg.com/rss/ 435 [46] https://westenberg.gumroad.com/ 436 [47] https://www.youtube.com/@jawestenberg 437 [48] https://westenberg.discourse.group/ 438 [49] https://www.joanwestenberg.com/everything-is-awesome-why-im-an-optimist/#/portal/ 439 [50] https://joanwestenberg.com/ 440 [51] https://thisisstudioself.com/