When AI Prophecy Fails  ## Metadata - Author: [[pluralistic.net]] - Full Title: When AI Prophecy Fails - Category: #articles - Document Note: --- tags: [AI, Amazon, labor] author: Cory Doctorow source: pluralistic.net reference: [https://pluralistic.net/2025/10/29/worker-frightening-machines/] date created: 2025-10-29 00:00 --- # 🏷️ Title: When AI prophecy fails (permalink) ## 🧭 Table of Contents - [📝 Summary](#-summary) - [📖 Main Content](#-main-content) - [🗒️ Notes](#️-notes) - [📚 References](#-references) - [🗣️ Paraphrase](#️-paraphrase) - [📰 Newsletter](#-newsletter) - [✅ Action Items](#-action-items) - [🧪 Hypotheses](#-hypotheses) - [📊 Methodology](#-methodology) - [❓ Questions](#-questions) - [🔮 Future Research](#-future-research) - [💡 Implications](#-implications) - [🧠 Learning Styles Assessment](#-learning-styles-assessment) - [📊 Accessibility Assessment](#-accessibility-assessment) - [🌍 DEIB Assessment](#-deib-assessment) - [✅ Logical Validity](#-logical-validity) - [🛡️ DARVO Analysis](#-darvo-analysis) - [🎯 Conclusion](#-conclusion) ### 🔗 References - Include links cited in or relevant to the article. ## 📝 Summary - What happened: Amazon posts ~$35B profit, plans 14k–30k layoffs while touting AI readiness and massive AI capex. - Why it matters: Signals a marketing-led push to validate AI replacement of labor despite weak ROI. - Key stakeholders: Amazon workers, customers, AI vendors (e.g., Anthropic), cloud investors, regulators. - Risks and tradeoffs: Service degradation, safety issues, sunk-cost AI spending, market power enabling “too big to care.” - Bottom line: Layoffs function as theater to sell AI and buy time for overextended AI bets. ## 📖 Main Content - Core arguments: - AI layoffs are a performative signal to markets, not proven productivity gains. - Most AI deployments show poor or negative returns; firms misattribute failure to implementation. - Amazon already uses AI as a “digital whip” for labor control; replacing engineering is unrealistic due to context limits. - Enshittification lets dominant firms degrade quality without losing customers, sustaining the AI narrative. - Context/definitions: - Enshittification: platforms worsen for users/suppliers as they extract value. - MLM analogy: failing sellers blamed themselves; similarly, managers buy more AI training/consulting. - Uncertainties: - Timeline to economically viable, context-robust AI for complex engineering. - Investor patience for ongoing AI losses. ### 🗒️ Notes - Amazon: big profit, bigger AI spend (~$120B this year, ~$180B claimed overall); layoffs marketed as “AI ready.” - Bain cited: sector needs ~$2T revenue by 2030 to break even. - Evidence cited: 95% of AI projects produce no or negative ROI; little impact on wages/hours. - Engineering reality: code-generation ≠ software engineering; context maintenance is the bottleneck. - Customer service: firms that already underperform are likelier to swap humans for chatbots with no real capability loss. - Cloud reliance: Amazon’s AI customers prop up AWS; those AI firms bleed cash, need investor belief to persist. - Prime lock-in: K-shaped consumption + prepaid shipping reduce switching; enables quality degradation during peak season. - Conclusion: layoffs are marketing theater to sustain the AI investment story and delay reckoning. ## 📚 References - $2 trillion in new AI revenue needed by 2030 (Bain & Company): https://www.bain.com/about/media-center/press-releases/20252/$2-trillion-in-new-revenue-needed-to-fund-ais-scaling-trend—bain–companys-6th-annual-global-technology-report/ - MIT Tech Review analysis on AI ROI: https://www.technologyreview.com/2019/01/25/1436/we-analyzed-16625-papers-to-figure-out-where-ai-is-headed-next/ - Study: no significant impact on earnings/hours/wages: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5219933 - Ed Zitron on AWS dependence on AI spend: https://www.wheresyoured.at/costs/ - CNN on layoffs to be “AI ready”: https://www.cnn.com/2025/10/28/business/what-amazons-mass-layoffs-are-really-about - Guardian on Amazon degradation: https://www.theguardian.com/technology/2025/oct/05/way-past-its-prime-how-did-amazon-get-so-rubbish - Doctorow on delivery “digital whip”: https://pluralistic.net/2025/10/23/traveling-salesman-solution/#pee-bottles - Doctorow on hype/layoffs dynamic: https://pluralistic.net/2025/08/05/ex-princes-of-labor/#hyper-criti-hype ## 🗣️ Paraphrase - Paragraph A: Amazon is shedding tens of thousands of jobs while pitching AI as justification, despite enormous, unproven capex. - Paragraph B: Most AI initiatives don’t pay off; companies blame themselves, buy more consulting, and double down. ## 📰 Newsletter AI reality check: Amazon’s “AI-ready” layoffs show the gap between hype and delivery. For WordPress builders, focus on measurable value—ship docs, performance dashboards, and user-centered workflows. Useful reads: WordPress Performance Team, Core Editor Handbook, “Performance Lab” plugin, and WP-CLI. ## ✅ Action Items #### DevRel - Publish “AI in the loop” examples with measurable benchmarks and rollback plans. #### OSPO - Define AI-assisted contribution policy and provenance checks for generated code. #### Community - Run maintainer clinics on evaluating AI PRs and security pitfalls. #### WordPress - Core: add guardrails for AI-generated patches (tests, lint, ownership). - Core Performance: track perf regressions from AI-suggested changes. - Core AI: document responsible use, eval sets, red-team reviews. #### The WPCC - Pilot microgrants for testing AI claims with open benchmarks. ### FAIR - Require signed provenance for AI outputs; fund sunset clauses for pilots. ## 🧪 Hypotheses - Firms replacing customer support with chatbots see lower CSAT and higher churn within 2 quarters. - AI code generation increases defect rates unless paired with senior review and tests. - Prime lock-in reduces elasticity to delivery delays during peak season. - AI-heavy cloud revenue is disproportionately concentrated among loss-making customers. ### 📊 Methodology - Diff-in-diff on CSAT/churn pre/post chatbot rollout. - Repository mining: defect density vs. AI-tool adoption + reviewer seniority. - Panel data: Prime households’ switching behavior vs. delivery SLAs. - Segment AWS revenue by customer profitability; stress-test exposure. ### ❓ Questions - How long can investors subsidize AI losses? - What governance signals would trigger AI capex pullbacks? - Which tasks show persistent net gains from AI without quality loss? ### 🔮 Future Research - Longitudinal studies on AI-in-the-loop engineering outcomes. - Benchmarks for customer service resolution quality with/without AI. - Labor safety impacts under algorithmic management. ### 💡 Implications - Practice: treat AI as assistive, not replacement, with audits. - Policy: require service quality disclosures during mass AI-driven layoffs. - Security: scrutinize AI-generated code provenance and SBOMs. - Funding: tie AI spend to staged, independent evaluations. ### 🧠 Learning Styles Assessment - Reading level estimate: Flesch-Kincaid ≈ Grade 11–12. #### 👀 Visual learners - Improve: architecture/context diagrams of AI-in-the-loop workflows. #### 🔊 Aural learners - Improve: 3–5 minute audio summary of findings. #### 🗣️ Verbal learners - Present: vivid analogies (MLM, “digital whip”). #### 🧩 Kinesthetic learners - Improve: hands-on checklists for evaluating AI outputs. #### 🧠 Logical learners - Present: causal chains; add KPI tables/decision trees. #### 🧑‍🤝‍🧑 Social learners - Improve: moderated Q&A and cohort reviews. #### 🧘‍♀️ Solitary learners - Improve: self-check quizzes on AI claims. #### 🌿 Naturalistic learners - Improve: lifecycle cost/energy analyses of AI workloads. ### 📊 Accessibility Assessment - Improve: descriptive alt text for images; transcripts for media; avoid autoplay. - Ensure 4.5:1 contrast, visible focus, skip links, responsive at 200% zoom. - Map gaps to WCAG 2.2 AA. ### 🌍 DEIB Assessment - Improve: global labor perspectives, plain-language summaries, glossary of AI terms. - Balance quotes across roles; add content warnings for labor/safety topics. ### ✅ Logical Validity - Strong reasoning: causal link between dominance and tolerance for service degradation; supported by Prime lock-in dynamics. - Fallacies: watch f - Summary: Amazon made $35 billion in profit last year, so they're celebrating by laying off 14,000 workers (a number they say will rise to 30,000). - URL: https://pluralistic.net/2025/10/29/worker-frightening-machines/ [](https://pluralistic.net/2025/10/29/worker-frightening-machines/) * [When AI prophecy fails](https://pluralistic.net/2025/10/29/worker-frightening-machines/#robots-stole-your-jerb-kinda): Hating workers is a hell of a drug. * [Hey look at this](https://pluralistic.net/2025/10/29/worker-frightening-machines/#linkdump): Delights to delectate. * [Object permanence](https://pluralistic.net/2025/10/29/worker-frightening-machines/#retro): SCOTUS lets the FBI kidnap Americans; Inequality perverts justice; Free the McFlurry! * [Recent appearances](https://pluralistic.net/2025/10/29/worker-frightening-machines/#recent): Where I've been. * [Latest books](https://pluralistic.net/2025/10/29/worker-frightening-machines/#latest): You keep readin' em, I'll keep writin' 'em. * [Upcoming books](https://pluralistic.net/2025/10/29/worker-frightening-machines/#upcoming-books): Like I said, I'll keep writin' 'em. A black and white image of an armed overseer supervising several chain-gang prisoners in stripes doing forced labor. The overseer's head has been replaced with the glaring red eye of HAL 9000 from Stanley Kubrick's '2001: A Space Odyssey.' The prisoners' heads have been replaced with hackers' hoodies. Amazon made $35 billion in profit last year, so they're celebrating by laying off 14,000 workers (a number they say will rise to 30,000). This is the kind of thing that Wall Street *loves*, and this layoff comes after a string of pronouncements from Amazon CEO Andy Jassy about how AI is going to let them fire *tons* of workers. That's the AI story, after all. It's not about making workers more productive or creative. The only way to recoup the $700 billion in capital expenditure to date (to say nothing of AI companies' rather fanciful coming capex commitments) is by displacing workers – a *lot* of workers. Bain & Co say the sector needs to be grossing $2 trillion by 2030 in order to break even, which is more than the combined grosses of Amazon, Google, Microsoft, Apple Nvidia and Meta: <https://www.bain.com/about/media-center/press-releases/20252/$2-trillion-in-new-revenue-needed-to-fund-ais-scaling-trend—bain–companys-6th-annual-global-technology-report/> Every investor who has put a nickel into that $700b capex is counting on bosses firing a *lot* of workers and replacing them with AI. Amazon is *also* counting on people buying a *lot* of AI from it after firing those workers. The company has sunk $120b into AI *this year alone*. There's just one problem: AI can't do our jobs. Oh, sure, an AI salesman can convince your boss to fire you and replace you with an AI that can't do your job, but that's the world's easiest sales-call. Your boss is relentlessly horny for firing you: <https://pluralistic.net/2025/03/18/asbestos-in-the-walls/#government-by-spicy-autocomplete> But there's a *lot* of AI buyers' remorse. 95% of AI deployments have either produced no return on capital, or have been money-losing: <https://www.technologyreview.com/2019/01/25/1436/we-analyzed-16625-papers-to-figure-out-where-ai-is-headed-next/> AI has "no significant impact on workers’ earnings, recorded hours, or wages": <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5219933> What's Amazon to do? How do they convince you to buy enough AI to justify that $180b in capital expenditure? Somehow, they have to convince you that an AI can do your workers' jobs. One way to sell that pitch is to fire a *ton* of Amazon workers and announce that their jobs have been given to a chatbot. This isn't a production strategy, it's a marketing strategy – it's Amazon deliberately taking an efficiency loss by firing workers in a desperate bid to convince you that you can fire *your* workers: <https://pluralistic.net/2025/08/05/ex-princes-of-labor/#hyper-criti-hype> Amazon *does* use a lot of AI in its production, of course. AI is the "digital whip" that Amazon uses to allow itself to control drivers who (nominally) work for subcontractors. This lets Amazon force workers into unsafe labor practices that endanger them and the people they share the roads with, while offloading responsibility onto "independent delivery service" operators and the drivers themselves: <https://pluralistic.net/2025/10/23/traveling-salesman-solution/#pee-bottles> Amazon leadership has announced that AI has or will shortly replace its coders as well. But chatbots can't do software engineering – sure, they can write code, but writing code is only a small part of software engineering. An engineer's job is to maintain a very deep and wide context window, one that considers how each piece of code interacts with the software that executes before it and after it, and with the systems that feed into it and accept its output. There's one thing AI struggles with beyond all else: maintaining context. Each linear increase in context that you demand from AI results in an *exponential* increase in computational expense. AI has no object permanence. It doesn't know where it's been and it doesn't know where it's going. It can't remember how many fingers it's drawn, so it doesn't know when to stop. It can write a routine, but it can't engineer a system. When tech bosses dream of firing coders and replacing them with AI, they're fantasizing about getting rid of their highest-paid, most self-assured workers and transforming the insecure junior programmers leftover into AI babysitters whose job it is to evaluate and integrate that code at a speed that no one – much less a junior programmer – can meet if they are to do a careful and competent job: <https://www.bloodinthemachine.com/p/how-ai-is-killing-jobs-in-the-tech-f39> The jobs that *can* be replaced with AI are the jobs that companies already gave up on doing well. If you've already outsourced your customer service to an overseas call-center whose workers are not empowered to solve any of your customers' problems, why not fire those workers and replace them with chatbots? The chatbots also can't solve anyone's problems, and they're even cheaper than overseas call-center workers: <https://pluralistic.net/2025/08/06/unmerchantable-substitute-goods/#customer-disservice> Amazon CEO Andy Jassy wrote that he "is convinced" that firing workers will make the company "AI ready," but it's not clear what he means by that. Does he mean that the mass firings will save money while maintaining quality, or that mass firings will help Amazon recoup the $180,000,000,000 it spent on AI this year? Bosses *really* want AI to work, because they *really, really* want to fire you. As Allison Morrow writes for *CNN* bosses are firing workers *in anticipation* of the savings AI will produce…someday: <https://www.cnn.com/2025/10/28/business/what-amazons-mass-layoffs-are-really-about> All this can feel improbable. Would bosses really fire workers on the promise of eventual AI replacements, leaving themselves with big bills for AI and falling revenues as the absence of those workers is felt? The answer is a resounding *yes*. The AI industry has done such a good job of convincing bosses that AI can do their workers' jobs that each boss for whom AI fails assumes that *they've* done something wrong. This is a familiar dynamic in con-jobs. The people who get sucked into pyramid schemes all think that they are the only ones failing to sell any of the "merchandise" they shell out every month to buy, and that no one else has a garage full of unsold leggings or essential oils. They don't know that, to a first approximation, the MLM industry has *no* sales, and relies entirely on "entrepreneurs" lying to themselves and one another about the demand for their wares, paying out of their own pocket for goods that no one wants. The MLM industry doesn't just rely on this deception – they capitalize on it, by selling those self-flagellating "entrepreneurs" all kinds of expensive training courses that promise to help them overcome the personal defects that stop them from doing as well as all those desperate liars boasting about their incredible MLM sales success: <https://pluralistic.net/2025/05/05/free-enterprise-system/#amway-or-the-highway> The AI industry has its own version of those sales coaching courses – there's a whole secondary industry of management consultancies and business schools offering high-ticket "continuing education" courses to bosses who think that the only reason the AI they've purchased isn't saving them money is that they're doing AI wrong. Amazon *really* needs AI to work. Last week, Ed Zitron published an extensive analysis of leaked documents showing how much Amazon is making from AI companies who are buying cloud services from it. His conclusion? Take away AI and Amazon's cloud division is in steep decline: <https://www.wheresyoured.at/costs/> What's more, those big-money AI customers – like Anthropic – are losing *tens of billions of dollars per year*, relying on investors to keep handing them money to incinerate. Amazon *needs* bosses to believe they can fire workers and replace them with AI, because that way, investors will keep giving Anthropic the money *it* needs to keep Amazon in the black. Amazon firing 30,000 workers in the run-up to Christmas is a great milestone in enshittification. America's K-shaped recovery means that nearly all of the consumption is coming from the wealthiest American households, and these households overwhelmingly subscribe to Prime. Prime-subscribing households *do not* comparison shop. After all, they've already prepaid for a year's shipping in advance. These households start and end nearly every shopping trip in the Amazon app. If Amazon fires 30,000 workers and tanks its logistics network and e-commerce systems, if it allows itself to drown in spam and scam reviews, if it misses its delivery windows and messes up its returns, that will be *our* problem, not Amazon's. In a world of commerce where Amazon's predatory pricing, lock-in, and serial acquisitions has left us with few alternatives, Amazon can truly be "too big to care": <https://www.theguardian.com/technology/2025/oct/05/way-past-its-prime-how-did-amazon-get-so-rubbish> From that enviable position, Amazon can afford to enshittify its services in order to sell the big AI lie. Killing 30,000 jobs is a small price to pay if it buys them a few months before a reckoning for its wild AI overspending, keeping the AI grift alive for just a little longer. (*Image: [Cryteria](https://commons.wikimedia.org/wiki/File:HAL9000.svg), [CC BY 3.0](https://creativecommons.org/licenses/by/3.0/deed.en), modified*)  * Eugene Debs and All Of Us <https://www.hamiltonnolan.com/p/eugene-debs-and-all-of-us> * US Business Cycles 1954-2020 <https://www.youtube.com/watch?v=vXRC3RrngcI> * Ed Zitron Gets Paid to Love AI. He Also Gets Paid to Hate AI <https://www.wired.com/story/ai-pr-ed-zitron-profile/> * Worried About AI Monopoly? Embrace Copyright’s Limits [https://www.lawfaremedia.org/article/worried-about-ai-monopoly–embrace-copyright-s-limits](https://www.lawfaremedia.org/article/worried-about-ai-monopoly--embrace-copyright-s-limits) A shelf of leatherbound history books with a gilt-stamped series title, 'The World's Famous Events.' #10yrsago Librarian of Congress puts impossible conditions on your right to jailbreak your 3D printer <https://michaelweinberg.org/post/132021560865/unlocking-3d-printers-ruling-is-a-mess> #10yrsago The two brilliant, prescient 20th century science fiction novels you should read this election season <https://memex.craphound.com/2015/10/28/the-two-brilliant-prescient-20th-century-science-fiction-novels-you-should-read-this-election-season/> #10yrsago Hundreds of city police license plate cams are insecure and can be watched by anyone <https://www.eff.org/deeplinks/2015/10/license-plate-readers-exposed-how-public-safety-agencies-responded-massive> #10yrsago Appeals court holds the FBI is allowed to kidnap and torture Americans outside US borders <https://www.techdirt.com/2015/10/28/court-your-fourth-fifth-amendment-rights-no-longer-exist-if-you-leave-country/> #10yrsago South Carolina sheriff fires the school-cop who beat up a black girl at her desk <https://www.theguardian.com/us-news/2015/oct/28/south-carolina-parents-speak-out-school-board> #10yrsago The more unequal your society is, the more your laws will favor the rich <https://web.archive.org/web/20151028133814/http://america.aljazeera.com/opinions/2015/10/the-more-unequal-the-country-the-more-the-rich-rule.html> #5yrsago Trump abandons supporters to freeze <https://pluralistic.net/2020/10/28/trumpcicles/#omaha> #5yrsago RIAA's war on youtube-dl <https://pluralistic.net/2020/10/28/trumpcicles/#yt-dl> #1yrago The US Copyright Office frees the McFlurry <https://pluralistic.net/2024/10/28/mcbroken/#my-milkshake-brings-all-the-lawyers-to-the-yard> A photo of me onstage, giving a speech, pounding the podium. * Miami: Enshittification at Books & Books, Nov 5 <https://www.eventbrite.com/e/an-evening-with-cory-doctorow-tickets-1504647263469> * Miami: Cloudfest, Nov 6 <https://www.cloudfest.com/usa/> * Burbank: Burbank Book Festival, Nov 8 <https://www.burbankbookfestival.com/> * Lisbon: A post-American, enshittification-resistant internet, with Rabble (Web Summit), Nov 12 <https://websummit.com/sessions/lis25/92f47bc9-ca60-4997-bef3-006735b1f9c5/a-post-american-enshittification-resistant-internet/> * Cardiff: Hay Festival After Hours, Nov 13 <https://www.hayfestival.com/c-203-hay-festival-after-hours.aspx> * Oxford: Enshittification and Extraction: The Internet Sucks Now with Tim Wu (Oxford Internet Institute), Nov 14 <https://www.oii.ox.ac.uk/news-events/events/enshittification-and-extraction-the-internet-sucks-now/> * London: Enshittification with Sarah Wynn-Williams and Chris Morris, Nov 15 <https://www.barbican.org.uk/whats-on/2025/event/cory-doctorow-with-sarah-wynn-williams> * London: Downstream IRL with Aaron Bastani (Novara Media), Nov 17 <https://dice.fm/partner/tickets/event/oen5rr-downstream-irl-aaron-bastani-in-conversation-with-cory-doctorow-17th-nov-earth-london-tickets> * London: Enshittification with Carole Cadwalladr (Frontline Club), Nov 18 <https://www.eventbrite.co.uk/e/in-conversation-enshittification-tickets-1785553983029> * Virtual: Enshittification with Vass Bednar (Vancouver Public Library), Nov 21 <https://www.crowdcast.io/@bclibraries-present> * Seattle: Neuroscience, AI and Society (University of Washington), Dec 4 <https://compneuro.washington.edu/news-and-events/neuroscience-ai-and-society/> * Madison, CT: Enshittification at RJ Julia, Dec 8 <https://rjjulia.com/event/2025-12-08/cory-doctorow-enshittification> A screenshot of me at my desk, doing a livecast. * Enshittification and the Rot Economy with Ed Zitron (Clarion West) <https://www.youtube.com/watch?v=Tz71pIWbFyc> * Amanpour & Co (New Yorker Radio Hour) <https://www.youtube.com/watch?v=I8l1uSb0LZg> * Enshittification is Not Inevitable (Team Human) <https://www.teamhuman.fm/episodes/339-cory-doctorow-enshittification-is-not-inevitable> * The Great Enshittening (The Gray Area) <https://www.reddit.com/r/philosophypodcasts/comments/1obghu7/the_gray_area_the_great_enshittening_10202025/> * Enshittification (Smart Cookies) <https://www.youtube.com/watch?v=-BoORwEPlQ0> A grid of my books with Will Stahle covers.. * "Canny Valley": A limited edition collection of the collages I create for Pluralistic, self-published, September 2025 * "Enshittification: Why Everything Suddenly Got Worse and What to Do About It," Farrar, Straus, Giroux, October 7 2025 <https://us.macmillan.com/books/9780374619329/enshittification/> * "Picks and Shovels": a sequel to "Red Team Blues," about the heroic era of the PC, Tor Books (US), Head of Zeus (UK), February 2025 (<https://us.macmillan.com/books/9781250865908/picksandshovels>). * "The Bezzle": a sequel to "Red Team Blues," about prison-tech and other grifts, Tor Books (US), Head of Zeus (UK), February 2024 ([the-bezzle.org](http://the-bezzle.org)). * "The Lost Cause:" a solarpunk novel of hope in the climate emergency, Tor Books (US), Head of Zeus (UK), November 2023 (<http://lost-cause.org>). * "The Internet Con": A nonfiction book about interoperability and Big Tech (Verso) September 2023 (<http://seizethemeansofcomputation.org>). Signed copies at Book Soup (<https://www.booksoup.com/book/9781804291245>). * "Red Team Blues": "A grabby, compulsive thriller that will leave you knowing more about how the world works than you did before." Tor Books <http://redteamblues.com>. * "Chokepoint Capitalism: How to Beat Big Tech, Tame Big Content, and Get Artists Paid, with Rebecca Giblin", on how to unrig the markets for creative labor, Beacon Press/Scribe 2022 <https://chokepointcapitalism.com> A cardboard book box with the Macmillan logo. * "Unauthorized Bread": a middle-grades graphic novel adapted from my novella about refugees, toasters and DRM, FirstSecond, 2026 * "Enshittification, Why Everything Suddenly Got Worse and What to Do About It" (the graphic novel), Firstsecond, 2026 * "The Memex Method," Farrar, Straus, Giroux, 2026 * "The Reverse-Centaur's Guide to AI," a short book about being a better AI critic, Farrar, Straus and Giroux, 2026  Today's top sources: **Currently writing:** * "The Reverse Centaur's Guide to AI," a short book for Farrar, Straus and Giroux about being an effective AI critic. FIRST DRAFT COMPLETE AND SUBMITTED. * A Little Brother short story about DIY insulin PLANNING This work – excluding any serialized fiction – is licensed under a Creative Commons Attribution 4.0 license. That means you can use it any way you like, including commercially, provided that you attribute it to me, Cory Doctorow, and include a link to pluralistic.net. <https://creativecommons.org/licenses/by/4.0/> Quotations and images are not included in this license; they are included either under a limitation or exception to copyright, or on the basis of a separate license. Please exercise caution. 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