Our lat­est model, Claude Opus 4.7, is now gen­er­ally avail­able. Opus 4.7 is a no­table im­prove­ment on Opus 4.6 in ad­vanced soft­ware en­gi­neer­ing, with par­tic­u­lar gains on the most dif­fi­cult tasks. Users re­port be­ing able to hand off their hard­est cod­ing work—the kind that pre­vi­ously needed close su­per­vi­sion—to Opus 4.7 with con­fi­dence. Opus 4.7 han­dles com­plex, long-run­ning tasks with rigor and con­sis­tency, pays pre­cise at­ten­tion to in­struc­tions, and de­vises ways to ver­ify its own out­puts be­fore re­port­ing back.The model also has sub­stan­tially bet­ter vi­sion: it can see im­ages in greater res­o­lu­tion. It’s more taste­ful and cre­ative when com­plet­ing pro­fes­sional tasks, pro­duc­ing higher-qual­ity in­ter­faces, slides, and docs. And—although it is less broadly ca­pa­ble than our most pow­er­ful model, Claude Mythos Preview—it shows bet­ter re­sults than Opus 4.6 across a range of bench­marks:Last week we an­nounced Project Glasswing, high­light­ing the risks—and ben­e­fits—of AI mod­els for cy­ber­se­cu­rity. We stated that we would keep Claude Mythos Preview’s re­lease lim­ited and test new cy­ber safe­guards on less ca­pa­ble mod­els first. Opus 4.7 is the first such model: its cy­ber ca­pa­bil­i­ties are not as ad­vanced as those of Mythos Preview (indeed, dur­ing its train­ing we ex­per­i­mented with ef­forts to dif­fer­en­tially re­duce these ca­pa­bil­i­ties). We are re­leas­ing Opus 4.7 with safe­guards that au­to­mat­i­cally de­tect and block re­quests that in­di­cate pro­hib­ited or high-risk cy­ber­se­cu­rity uses. What we learn from the real-world de­ploy­ment of these safe­guards will help us work to­wards our even­tual goal of a broad re­lease of Mythos-class mod­els.Se­cu­rity pro­fes­sion­als who wish to use Opus 4.7 for le­git­i­mate cy­ber­se­cu­rity pur­poses (such as vul­ner­a­bil­ity re­search, pen­e­tra­tion test­ing, and red-team­ing) are in­vited to join our new Cyber Verification Program.Opus 4.7 is avail­able to­day across all Claude prod­ucts and our API, Amazon Bedrock, Google Cloud’s Vertex AI, and Microsoft Foundry. Pricing re­mains the same as Opus 4.6: $5 per mil­lion in­put to­kens and $25 per mil­lion out­put to­kens. Developers can use claude-opus-4-7 via the Claude API.Claude Opus 4.7 has gar­nered strong feed­back from our early-ac­cess testers:In early test­ing, we’re see­ing the po­ten­tial for a sig­nif­i­cant leap for our de­vel­op­ers with Claude Opus 4.7. It catches its own log­i­cal faults dur­ing the plan­ning phase and ac­cel­er­ates ex­e­cu­tion, far be­yond pre­vi­ous Claude mod­els. As a fi­nan­cial tech­nol­ogy plat­form serv­ing mil­lions of con­sumers and busi­nesses at sig­nif­i­cant scale, this com­bi­na­tion of speed and pre­ci­sion could be game-chang­ing: ac­cel­er­at­ing de­vel­op­ment ve­loc­ity for faster de­liv­ery of the trusted fi­nan­cial so­lu­tions our cus­tomers rely on every day.An­thropic has al­ready set the stan­dard for cod­ing mod­els, and Claude Opus 4.7 pushes that fur­ther in a mean­ing­ful way as the state-of-the-art model on the mar­ket. In our in­ter­nal evals, it stands out not just for raw ca­pa­bil­ity, but for how well it han­dles real-world async work­flows—au­toma­tions, CI/CD, and long-run­ning tasks. It also thinks more deeply about prob­lems and brings a more opin­ion­ated per­spec­tive, rather than sim­ply agree­ing with the user.Claude Opus 4.7 is the strongest model Hex has eval­u­ated. It cor­rectly re­ports when data is miss­ing in­stead of pro­vid­ing plau­si­ble-but-in­cor­rect fall­backs, and it re­sists dis­so­nant-data traps that even Opus 4.6 falls for. It’s a more in­tel­li­gent, more ef­fi­cient Opus 4.6: low-ef­fort Opus 4.7 is roughly equiv­a­lent to medium-ef­fort Opus 4.6.On our 93-task cod­ing bench­mark, Claude Opus 4.7 lifted res­o­lu­tion by 13% over Opus 4.6, in­clud­ing four tasks nei­ther Opus 4.6 nor Sonnet 4.6 could solve. Combined with faster me­dian la­tency and strict in­struc­tion fol­low­ing, it’s par­tic­u­larly mean­ing­ful for com­plex, long-run­ning cod­ing work­flows. It cuts the fric­tion from those multi-step tasks so de­vel­op­ers can stay in the flow and fo­cus on build­ing.Based on our in­ter­nal re­search-agent bench­mark, Claude Opus 4.7 has the strongest ef­fi­ciency base­line we’ve seen for multi-step work. It tied for the top over­all score across our six mod­ules at 0.715 and de­liv­ered the most con­sis­tent long-con­text per­for­mance of any model we tested. On General Finance—our largest mod­ule—it im­proved mean­ing­fully on Opus 4.6, scor­ing 0.813 ver­sus 0.767, while also show­ing the best dis­clo­sure and data dis­ci­pline in the group. And on de­duc­tive logic, an area where Opus 4.6 strug­gled, Opus 4.7 is solid.Claude Opus 4.7 ex­tends the limit of what mod­els can do to in­ves­ti­gate and get tasks done. Anthropic has clearly op­ti­mized for sus­tained rea­son­ing over long runs, and it shows with mar­ket-lead­ing per­for­mance. As en­gi­neers shift from work­ing 1:1 with agents to man­ag­ing them in par­al­lel, this is ex­actly the kind of fron­tier ca­pa­bil­ity that un­locks new work­flows.We’re see­ing ma­jor im­prove­ments in Claude Opus 4.7’s mul­ti­modal un­der­stand­ing, from read­ing chem­i­cal struc­tures to in­ter­pret­ing com­plex tech­ni­cal di­a­grams. The higher res­o­lu­tion sup­port is help­ing Solve Intelligence build best-in-class tools for life sci­ences patent work­flows, from draft­ing and pros­e­cu­tion to in­fringe­ment de­tec­tion and in­va­lid­ity chart­ing.Claude Opus 4.7 takes long-hori­zon au­ton­omy to a new level in Devin. It works co­her­ently for hours, pushes through hard prob­lems rather than giv­ing up, and un­locks a class of deep in­ves­ti­ga­tion work we could­n’t re­li­ably run be­fore.For Replit, Claude Opus 4.7 was an easy up­grade de­ci­sion. For the work our users do every day, we ob­served it achiev­ing the same qual­ity at lower cost—more ef­fi­cient and pre­cise at tasks like an­a­lyz­ing logs and traces, find­ing bugs, and propos­ing fixes. Personally, I love how it pushes back dur­ing tech­ni­cal dis­cus­sions to help me make bet­ter de­ci­sions. It re­ally feels like a bet­ter coworker.Claude Opus 4.7 demon­strates strong sub­stan­tive ac­cu­racy on BigLaw Bench for Harvey, scor­ing 90.9% at high ef­fort with bet­ter rea­son­ing cal­i­bra­tion on re­view ta­bles and no­tice­ably smarter han­dling of am­bigu­ous doc­u­ment edit­ing tasks. It cor­rectly dis­tin­guishes as­sign­ment pro­vi­sions from change-of-con­trol pro­vi­sions, a task that has his­tor­i­cally chal­lenged fron­tier mod­els. Substance was con­sis­tently rated as a strength across our eval­u­a­tions: cor­rect, thor­ough, and well-cited.Claude Opus 4.7 is a very im­pres­sive cod­ing model, par­tic­u­larly for its au­ton­omy and more cre­ative rea­son­ing. On CursorBench, Opus 4.7 is a mean­ing­ful jump in ca­pa­bil­i­ties, clear­ing 70% ver­sus Opus 4.6 at 58%.For com­plex multi-step work­flows, Claude Opus 4.7 is a clear step up: plus 14% over Opus 4.6 at fewer to­kens and a third of the tool er­rors. It’s the first model to pass our im­plicit-need tests, and it keeps ex­e­cut­ing through tool fail­ures that used to stop Opus cold. This is the re­li­a­bil­ity jump that makes Notion Agent feel like a true team­mate.In our evals, we saw a dou­ble-digit jump in ac­cu­racy of tool calls and plan­ning in our core or­ches­tra­tor agents. As users lever­age Hebbia to plan and ex­e­cute on use cases like re­trieval, slide cre­ation, or doc­u­ment gen­er­a­tion, Claude Opus 4.7 shows the po­ten­tial to im­prove agent de­ci­sion-mak­ing in these work­flows.On Rakuten-SWE-Bench, Claude Opus 4.7 re­solves 3x more pro­duc­tion tasks than Opus 4.6, with dou­ble-digit gains in Code Quality and Test Quality. This is a mean­ing­ful lift and a clear up­grade for the en­gi­neer­ing work our teams are ship­ping every day.For CodeRabbit’s code re­view work­loads, Claude Opus 4.7 is the sharpest model we’ve tested. Recall im­proved by over 10%, sur­fac­ing some of the most dif­fi­cult-to-de­tect bugs in our most com­plex PRs, while pre­ci­sion re­mained sta­ble de­spite the in­creased cov­er­age. It’s a bit faster than GPT-5.4 xhigh on our har­ness, and we’re lin­ing it up for our heav­i­est re­view work at launch.For Genspark’s Super Agent, Claude Opus 4.7 nails the three pro­duc­tion dif­fer­en­tia­tors that mat­ter most: loop re­sis­tance, con­sis­tency, and grace­ful er­ror re­cov­ery. Loop re­sis­tance is the most crit­i­cal. A model that loops in­def­i­nitely on 1 in 18 queries wastes com­pute and blocks users. Lower vari­ance means fewer sur­prises in prod. And Opus 4.7 achieves the high­est qual­ity-per-tool-call ra­tio we’ve mea­sured.Claude Opus 4.7 is a mean­ing­ful step up for Warp. Opus 4.6 is one of the best mod­els out there for de­vel­op­ers, and this model is mea­sur­ably more thor­ough on top of that. It passed Terminal Bench tasks that prior Claude mod­els had failed, and worked through a tricky con­cur­rency bug Opus 4.6 could­n’t crack. For us, that’s the sig­nal.Claude Opus 4.7 is the best model in the world for build­ing dash­boards and data-rich in­ter­faces. The de­sign taste is gen­uinely sur­pris­ing—it makes choices I’d ac­tu­ally ship. It’s my de­fault daily dri­ver now.Claude Opus 4.7 is the most ca­pa­ble model we’ve tested at Quantium. Evaluated against lead­ing AI mod­els through our pro­pri­etary bench­mark­ing so­lu­tion, the biggest gains showed up where they mat­ter most: rea­son­ing depth, struc­tured prob­lem-fram­ing, and com­plex tech­ni­cal work. Fewer cor­rec­tions, faster it­er­a­tions, and stronger out­puts to solve the hard­est prob­lems our clients bring us.Claude Opus 4.7 feels like a real step up in in­tel­li­gence. Code qual­ity is no­tice­ably im­proved, it’s cut­ting out the mean­ing­less wrap­per func­tions and fall­back scaf­fold­ing that used to pile up, and fixes its own code as it goes. It’s the clean­est jump we’ve seen since the move from Sonnet 3.7 to the Claude 4 se­ries.For the com­puter-use work that sits at the heart of XBOW’s au­tonomous pen­e­tra­tion test­ing, the new Claude Opus 4.7 is a step change: 98.5% on our vi­sual-acu­ity bench­mark ver­sus 54.5% for Opus 4.6. Our sin­gle biggest Opus pain point ef­fec­tively dis­ap­peared, and that un­locks its use for a whole class of work where we could­n’t use it be­fore.Claude Opus 4.7 is a solid up­grade with no re­gres­sions for Vercel. It’s phe­nom­e­nal on one-shot cod­ing tasks, more cor­rect and com­plete than Opus 4.6, and no­tice­ably more hon­est about its own lim­its. It even does proofs on sys­tems code be­fore start­ing work, which is new be­hav­ior we haven’t seen from ear­lier Claude mod­els.Claude Opus 4.7 is very strong and out­per­forms Opus 4.6 with a 10% to 15% lift in task suc­cess for Factory Droids, with fewer tool er­rors and more re­li­able fol­low-through on val­i­da­tion steps. It car­ries work all the way through in­stead of stop­ping halfway, which is ex­actly what en­ter­prise en­gi­neer­ing teams need.Claude Opus 4.7 au­tonomously built a com­plete Rust text-to-speech en­gine from scratch—neural model, SIMD ker­nels, browser demo—then fed its own out­put through a speech rec­og­nizer to ver­ify it matched the Python ref­er­ence. Months of se­nior en­gi­neer­ing, de­liv­ered au­tonomously. The step up from Opus 4.6 is clear, and the code­base is pub­lic.Claude Opus 4.7 passed three TBench tasks that prior Claude mod­els could­n’t, and it’s land­ing fixes our pre­vi­ous best model missed, in­clud­ing a race con­di­tion. It demon­strates strong pre­ci­sion in iden­ti­fy­ing real is­sues, and sur­faces im­por­tant find­ings that other mod­els ei­ther gave up on or did­n’t re­solve. In Qodo’s real-world code re­view bench­mark, we ob­served top-tier pre­ci­sion.On Databricks’ OfficeQA Pro, Claude Opus 4.7 shows mean­ing­fully stronger doc­u­ment rea­son­ing, with 21% fewer er­rors than Opus 4.6 when work­ing with source in­for­ma­tion. Across our agen­tic rea­son­ing over data bench­marks, it is the best-per­form­ing Claude model for en­ter­prise doc­u­ment analy­sis.For Ramp, Claude Opus 4.7 stands out in agent-team work­flows. We’re see­ing stronger role fi­delity, in­struc­tion-fol­low­ing, co­or­di­na­tion, and com­plex rea­son­ing, es­pe­cially on en­gi­neer­ing tasks that span tools, code­bases, and de­bug­ging con­text. Compared with Opus 4.6, it needs much less step-by-step guid­ance, help­ing us scale the in­ter­nal agent work­flows our en­gi­neer­ing teams run.Claude Opus 4.7 is mea­sur­ably bet­ter than Opus 4.6 for Bolt’s longer-run­ning app-build­ing work, up to 10% bet­ter in the best cases, with­out the re­gres­sions we’ve come to ex­pect from very agen­tic mod­els. It pushes the ceil­ing on what our users can ship in a sin­gle ses­sion.Be­low are some high­lights and notes from our early test­ing of Opus 4.7:Instruction fol­low­ing. Opus 4.7 is sub­stan­tially bet­ter at fol­low­ing in­struc­tions. Interestingly, this means that prompts writ­ten for ear­lier mod­els can some­times now pro­duce un­ex­pected re­sults: where pre­vi­ous mod­els in­ter­preted in­struc­tions loosely or skipped parts en­tirely, Opus 4.7 takes the in­struc­tions lit­er­ally. Users should re-tune their prompts and har­nesses ac­cord­ingly.Im­proved mul­ti­modal sup­port. Opus 4.7 has bet­ter vi­sion for high-res­o­lu­tion im­ages: it can ac­cept im­ages up to 2,576 pix­els on the long edge (~3.75 megapix­els), more than three times as many as prior Claude mod­els. This opens up a wealth of mul­ti­modal uses that de­pend on fine vi­sual de­tail: com­puter-use agents read­ing dense screen­shots, data ex­trac­tions from com­plex di­a­grams, and work that needs pixel-per­fect ref­er­ences.1Real-world work. As well as its state-of-the-art score on the Finance Agent eval­u­a­tion (see table above), our in­ter­nal test­ing showed Opus 4.7 to be a more ef­fec­tive fi­nance an­a­lyst than Opus 4.6, pro­duc­ing rig­or­ous analy­ses and mod­els, more pro­fes­sional pre­sen­ta­tions, and tighter in­te­gra­tion across tasks. Opus 4.7 is also state-of-the-art on GDPval-AA, a third-party eval­u­a­tion of eco­nom­i­cally valu­able knowl­edge work across fi­nance, le­gal, and other do­mains.Mem­ory. Opus 4.7 is bet­ter at us­ing file sys­tem-based mem­ory. It re­mem­bers im­por­tant notes across long, multi-ses­sion work, and uses them to move on to new tasks that, as a re­sult, need less up-front con­text.The charts be­low dis­play more eval­u­a­tion re­sults from our pre-re­lease test­ing, across a range of dif­fer­ent do­mains:Over­all, Opus 4.7 shows a sim­i­lar safety pro­file to Opus 4.6: our eval­u­a­tions show low rates of con­cern­ing be­hav­ior such as de­cep­tion, syco­phancy, and co­op­er­a­tion with mis­use. On some mea­sures, such as hon­esty and re­sis­tance to ma­li­cious “prompt in­jec­tion” at­tacks, Opus 4.7 is an im­prove­ment on Opus 4.6; in oth­ers (such as its ten­dency to give overly de­tailed harm-re­duc­tion ad­vice on con­trolled sub­stances), Opus 4.7 is mod­estly weaker. Our align­ment as­sess­ment con­cluded that the model is “largely well-aligned and trust­wor­thy, though not fully ideal in its be­hav­ior”. Note that Mythos Preview re­mains the best-aligned model we’ve trained ac­cord­ing to our eval­u­a­tions. Our safety eval­u­a­tions are dis­cussed in full in the Claude Opus 4.7 System Card.Overall mis­aligned be­hav­ior score from our au­to­mated be­hav­ioral au­dit. On this eval­u­a­tion, Opus 4.7 is a mod­est im­prove­ment on Opus 4.6 and Sonnet 4.6, but Mythos Preview still shows the low­est rates of mis­aligned be­hav­ior.In ad­di­tion to Claude Opus 4.7 it­self, we’re launch­ing the fol­low­ing up­dates:More ef­fort con­trol: Opus 4.7 in­tro­duces a new xhigh (“extra high”) ef­fort level be­tween high and max, giv­ing users finer con­trol over the trade­off be­tween rea­son­ing and la­tency on hard prob­lems. In Claude Code, we’ve raised the de­fault ef­fort level to xhigh for all plans. When test­ing Opus 4.7 for cod­ing and agen­tic use cases, we rec­om­mend start­ing with high or xhigh ef­fort.On the Claude Platform (API): as well as sup­port for higher-res­o­lu­tion im­ages, we’re also launch­ing task bud­gets in pub­lic beta, giv­ing de­vel­op­ers a way to guide Claude’s to­ken spend so it can pri­or­i­tize work across longer runs.In Claude Code: The new /ultrareview slash com­mand pro­duces a ded­i­cated re­view ses­sion that reads through changes and flags bugs and de­sign is­sues that a care­ful re­viewer would catch. We’re giv­ing Pro and Max Claude Code users three free ul­tra­reviews to try it out. In ad­di­tion, we’ve ex­tended auto mode to Max users. Auto mode is a new per­mis­sions op­tion where Claude makes de­ci­sions on your be­half, mean­ing that you can run longer tasks with fewer in­ter­rup­tions—and with less risk than if you had cho­sen to skip all per­mis­sions.Opus 4.7 is a di­rect up­grade to Opus 4.6, but two changes are worth plan­ning for be­cause they af­fect to­ken us­age. First, Opus 4.7 uses an up­dated to­k­enizer that im­proves how the model processes text. The trade­off is that the same in­put can map to more to­kens—roughly 1.0–1.35× de­pend­ing on the con­tent type. Second, Opus 4.7 thinks more at higher ef­fort lev­els, par­tic­u­larly on later turns in agen­tic set­tings. This im­proves its re­li­a­bil­ity on hard prob­lems, but it does mean it pro­duces more out­put to­kens. Users can con­trol to­ken us­age in var­i­ous ways: by us­ing the ef­fort pa­ra­me­ter, ad­just­ing their task bud­gets, or prompt­ing the model to be more con­cise. In our own test­ing, the net ef­fect is fa­vor­able—to­ken us­age across all ef­fort lev­els is im­proved on an in­ter­nal cod­ing eval­u­a­tion, as shown be­low—but we rec­om­mend mea­sur­ing the dif­fer­ence on real traf­fic. We’ve writ­ten a mi­gra­tion guide that pro­vides fur­ther ad­vice on up­grad­ing from Opus 4.6 to Opus 4.7.Score on an in­ter­nal agen­tic cod­ing eval­u­a­tion as a func­tion of to­ken us­age at each ef­fort level. In this eval­u­a­tion, the model works au­tonomously from a sin­gle user prompt, and re­sults may not be rep­re­sen­ta­tive of to­ken us­age in in­ter­ac­tive cod­ing. See the mi­gra­tion guide for more on tun­ing ef­fort lev­els.

For any­one who has been (inadvisably) tak­ing my pel­i­can rid­ing a bi­cy­cle bench­mark se­ri­ously as a ro­bust way to test mod­els, here are pel­i­cans from this morn­ing’s two big model re­leases—Qwen3.6-35B-A3B from Alibaba and Claude Opus 4.7 from Anthropic.

Here’s the Qwen 3.6 pel­i­can, gen­er­ated us­ing this 20.9GB Qwen3.6-35B-A3B-UD-Q4_K_S.gguf quan­tized model by Unsloth, run­ning on my MacBook Pro M5 via LM Studio (and the llm-lm­stu­dio plu­gin)—tran­script here:

And here’s one I got from Anthropic’s brand new Claude Opus 4.7 (transcript):

I’m giv­ing this one to Qwen 3.6. Opus man­aged to mess up the bi­cy­cle frame!

I tried Opus a sec­ond time pass­ing think­ing_level: max. It did­n’t do much bet­ter (transcript):

A lot of peo­ple are con­vinced that the labs train for my stu­pid bench­mark. I don’t think they do, but hon­estly this re­sult did give me a lit­tle glint of sus­pi­cion. So I’m burn­ing one of my se­cret backup tests—here’s what I got from Qwen3.6-35B-A3B and Opus 4.7 for “Generate an SVG of a flamingo rid­ing a uni­cy­cle”:

I’m giv­ing this one to Qwen too, partly for the ex­cel­lent SVG com­ment.

The pel­i­can bench­mark has al­ways been meant as a joke—it’s mainly a state­ment on how ob­tuse and ab­surd the task of com­par­ing these mod­els is.

The weird thing about that joke is that, for the most part, there has been a di­rect cor­re­la­tion be­tween the qual­ity of the pel­i­cans pro­duced and the gen­eral use­ful­ness of the mod­els. Those first pel­i­cans from October 2024 were junk. The more re­cent en­tries have gen­er­ally been much, much bet­ter—to the point that Gemini 3.1 Pro pro­duces il­lus­tra­tions you could ac­tu­ally use some­where, pro­vided you had a press­ing need to il­lus­trate a pel­i­can rid­ing a bi­cy­cle.

Today, even that loose con­nec­tion to util­ity has been bro­ken. I have enor­mous re­spect for Qwen, but I very much doubt that a 21GB quan­tized ver­sion of their lat­est model is more pow­er­ful or use­ful than Anthropic’s lat­est pro­pri­etary re­lease.

If the thing you need is an SVG il­lus­tra­tion of a pel­i­can rid­ing a bi­cy­cle though, right now Qwen3.6-35B-A3B run­ning on a lap­top is a bet­ter bet than Opus 4.7!

I had cof­fee last year with a guy - I won’t use his real name - who told me he was “building a busi­ness.” I asked what it did. Dropshipping jade face rollers.

I made him say it twice.

He’d found them on Alibaba for $1.20 each, and started sell­ing them through Shopify for $29.99. Never used one him­self. Didn’t re­ally know what they were for - some­thing about lym­phatic drainage? Reducing puffi­ness? He said “lymphatic” the way you say a word you’ve only ever read and never heard out loud.

Some guy on YouTube said jade rollers were “trending,” the mar­gins looked in­sane on pa­per, so he’d “built” a web­site with stock pho­tos of a dewy-skinned woman rolling a green rock across her cheek­bone and started run­ning Facebook ads at $50 a day. Customers would email ask­ing where their stuff was - ship­ping from Guangzhou, three to six weeks, some­times way longer - and he’d copy-paste a re­sponse he found on a drop­ship­ping sub­red­dit. He had a Google Doc full of pre-writ­ten cus­tomer ser­vice replies.

Five months in, he was $800 in the hole.

He told me all this like he’d in­vented the wheel.

I bought him an­other cof­fee. I gen­uinely had no idea what else to do.

Jade Roller Guy has be­come my go-to ex­am­ple of some­thing that went dras­ti­cally, ter­ri­bly wrong with how a whole gen­er­a­tion of would-be en­tre­pre­neurs thought about work and money. A spe­cific ide­ol­ogy - I’ve been call­ing it Passive Income Brain - grabbed a huge chunk of the peo­ple who were, by tem­pera­ment and abil­ity, most likely to start real busi­nesses, and it gave them a com­pletely fucked set of pri­or­i­ties.

Somewhere be­tween 2015 and 2022, “passive in­come” stopped be­ing a bor­ing fi­nan­cial plan­ning term and be­came, I don’t know how else to put this, a sal­va­tion nar­ra­tive. I mean that lit­er­ally. There was an es­cha­tol­ogy if you want to get nerdy about it. The Rapture was the day your “passive in­come” ex­ceeded your monthly ex­penses and you could quit your job for­ever. People talked about it with that ex­act en­ergy.

But, of course, the folks mak­ing any ac­tual in­come, of any kind, were the ones sell­ing courses about mak­ing pas­sive in­come. It was an ouroboros. It was an ouroboros that had in­cor­po­rated in Delaware and was run­ning Facebook ads.

The pitch went some­thing like: you, a sucker, cur­rently trade your time for money. This is what em­ploy­ees do, and em­ploy­ees are suck­ers. (I’m para­phras­ing, but not by much.) Smart peo­ple build SYSTEMS. A sys­tem is any­thing that gen­er­ates rev­enue with­out your on­go­ing in­volve­ment. Write an ebook. Build a drop­ship­ping store. Create an on­line course. Set up af­fil­i­ate web­sites.

The spe­cific ve­hi­cle does­n’t mat­ter be­cause the im­por­tant thing is­n’t what you build, it’s the struc­ture. You want a ma­chine that gen­er­ates cash while you sleep, and once you have that ma­chine, you are free.

Free to do what? Sit on a beach, ap­par­ently. Every sin­gle one of these peo­ple wanted to sit on a beach. I’ve never un­der­stood this. Have they been to a beach? There’s sand. It gets every­where. You can sit there for maybe three hours be­fore you want to do lit­er­ally any­thing else.

The al­lure is real. Who does­n’t want money that shows up while you sleep?

I’d fuck­ing love that. I’d love it very much in­deed. But “passive in­come” as an or­ga­niz­ing phi­los­o­phy for your en­tire busi­ness life, for how you think about work, is al­most per­fectly de­signed to pro­duce garbage.

When you make “passivity” the thing you’re op­ti­miz­ing for, you stop car­ing about any­thing a cus­tomer might ac­tu­ally want. Caring is ac­tive. Caring takes time. Caring is work.

Giving a shit is, by de­f­i­n­i­tion, not pas­sive.

Between 2019 and 2021, roughly 700,000 new Shopify stores opened. The plat­form went from about a mil­lion mer­chants to 1.7 mil­lion in two years. About 90% of those stores failed within their first year. Which is re­ally more a meat grinder, than it is a busi­ness model…

We started drown­ing in a mil­lion busi­nesses no­body was ac­tu­ally run­ning. Dropshipping stores with six-week ship­ping times and cus­tomer ser­vice that was just copy-pasted tem­plates. Guys who’d put their “brand name” - usu­ally some­thing like ZENITHPRO or AXELVIBE, al­ways in all caps, al­ways vaguely ag­gres­sive - on a gar­lic press iden­ti­cal to four hun­dred other gar­lic presses on the same Amazon page. AXELVIBE! For a gar­lic press!

And the af­fil­i­ate blogs! Hundreds of thou­sands of them, pumped full of SEO-optimized re­views of prod­ucts the au­thors had never touched, never even seen in per­son. A frac­tal of bull­shit that tech­ni­cally qual­i­fies as com­merce but puts zero dol­lars of ac­tual value into the world.

Leverage is real; I’m not dis­put­ing that. There is a dif­fer­ence be­tween trad­ing hours for dol­lars and build­ing some­thing that scales. Software does this. Publishing does this. You write a book once, sell it many times, no­body calls that a scam. Fine! That part they got right!

Where it went wrong is that the whole move­ment con­fused “build a good prod­uct that scales” with “build any mech­a­nism that ex­tracts money with­out you be­ing in­volved.” I don’t think that con­fu­sion was ac­ci­den­tal. I think the con­fu­sion was the point. Because if you’re teach­ing peo­ple to build real busi­nesses, you have to sit with hard, bor­ing ques­tions about whether any­one ac­tu­ally wants what you’re sell­ing. But if you’re teach­ing peo­ple to build “passive in­come streams” you can skip all of that and go straight to the fun tac­ti­cal shit. How to run Facebook ads, how to set up a Shopify store in a week­end, how to write email se­quences that ma­nip­u­late peo­ple into buy­ing things they don’t need.

Nobody talks enough about what the pas­sive in­come move­ment did to the con­tent qual­ity of the en­tire in­ter­net. If you’ve tried to google “best [anything]” in the last five years and got­ten a wall of nearly iden­ti­cal lis­ti­cles, all with the same struc­ture (“We tested 47 blenders so you don’t have to!“), all mak­ing the same rec­om­men­da­tions, all link­ing to the same Amazon prod­ucts, you’ve ex­pe­ri­enced the re­sults.

Those ar­ti­cles weren’t writ­ten by peo­ple who cared whether you bought a good blender. They were writ­ten by peo­ple who cared whether you clicked their af­fil­i­ate link, be­cause that’s what gen­er­ated pas­sive in­come, and the in­cen­tives made hon­esty ac­tively coun­ter­pro­duc­tive.

The hon­est re­view of blenders is: “most blenders are fine, just get what­ev­er’s on sale, the dif­fer­ences be­low $100 are ba­si­cally mean­ing­less.” That re­view gen­er­ates zero af­fil­i­ate rev­enue. So no­body wrote it.

Instead you got “The Vitamix A3500 is our #1 pick!” with a nice af­fil­i­ate link, writ­ten by some­one who has never blended any­thing in their life. Multiply this across every prod­uct cat­e­gory and you start to un­der­stand the in­for­ma­tional desert we’ve been liv­ing in. We broke Google re­sults, at least partly, be­cause an army of pas­sive in­come seek­ers had an in­cen­tive to flood the in­ter­net with plau­si­ble-sound­ing garbage.

I’ve met dozens of smart, ca­pa­ble peo­ple who had ac­tual en­ergy, and who spent their en­tire twen­ties bounc­ing be­tween pas­sive in­come schemes in­stead of build­ing real skills // real busi­nesses // real ca­reers. The pat­tern was al­ways the same: six months on a drop­ship­ping store, it fails, pivot to Amazon FBA, that fails, pivot to cre­at­ing a course about drop­ship­ping (because of course), and then the course does­n’t sell ei­ther be­cause by 2021 there were ap­prox­i­mately forty thou­sand courses about drop­ship­ping and the mar­ket had been sat­u­rated since be­fore they started.

And the whole time they were get­ting fur­ther and fur­ther from the thing that ac­tu­ally cre­ates eco­nomic value, which is: find a real prob­lem, solve it for real peo­ple, care enough to stick around and keep im­prov­ing. The bor­ing thing. The thing that takes years. The thing that is, to be ab­solutely clear about this, not pas­sive.

I once saw a guy ask whether he should start a dog walk­ing busi­ness and the top re­sponse was some­thing like “dog walk­ing is­n’t scal­able, you should build a dog walk­ing plat­form in­stead.” This per­son liked dogs! He liked walk­ing! He lived in a neigh­bor­hood full of busy pro­fes­sion­als with dogs!

But the Passive Income Brain thing had got­ten so deep into how peo­ple talked about busi­ness on­line that “do the sim­ple ob­vi­ous thing that works for you” was con­sid­ered naive, and “build a tech­nol­ogy plat­form for an ac­tiv­ity you’ve never ac­tu­ally done as a busi­ness” was con­sid­ered smart.

The dog walk­ing guy could have been prof­itable in a week.

The app guy would have burned through his sav­ings in six months and ended up with a land­ing page and no users.

By 2020 the pas­sive in­come world was ab­solutely crawl­ing with grift: guys pos­ing with rented Lamborghinis in YouTube thumb­nails, “digital no­mads” whose ac­tual in­come came en­tirely from sell­ing the dream of be­ing a dig­i­tal no­mad to other as­pir­ing dig­i­tal no­mads, pod­cast hosts in­ter­view­ing each other in an end­less cir­cle of mu­tual pro­mo­tion where every­one claimed to make $30K/month and no­body could ex­plain what they ac­tu­ally pro­duced. By 2021 or so it started to look like a dis­trib­uted, so­cially ac­cept­able MLM. The prod­uct was the dream of not work­ing. The cus­tomers were peo­ple des­per­ate enough to pay for it.

Not every­one in this world was cyn­i­cal. I gen­uinely be­lieve that. A lot of the peo­ple sell­ing pas­sive in­come con­tent be­lieved their own pitch. They’d had some real suc­cess with a niche site - pulled $3,000/month for a while, it does hap­pen - read the same books every­one else read, fig­ured okay, I’ll teach other peo­ple my sys­tem. Why not. I would have done the same thing at 24. I’m al­most sure of it.

But zoom out and what you had was just an enor­mous ma­chine con­vert­ing hu­man am­bi­tion into noise. Affiliate spam // drop­shipped junk // ebooks about pas­sive in­come // courses about courses. An en­tire layer of the in­ter­net that was noth­ing but con­fi­dent-sound­ing bull­shit pro­duced by peo­ple who had op­ti­mized for every­thing ex­cept mak­ing some­thing worth buy­ing.

The peo­ple near the top made money. Everyone else spent months or years chas­ing a mi­rage and came out with noth­ing but a Shopify sub­scrip­tion they for­got to can­cel. They thought they’d failed. They had­n’t failed. The sys­tem, every sys­tem, failed them.

What ac­tu­ally makes money has­n’t changed. You find some­thing peo­ple need. You get good at pro­vid­ing it. You charge a fair price and you keep show­ing up even when it’s te­dious and even when you don’t want to. You build re­la­tion­ships over years. You build rep­u­ta­tion over years. None of it is pas­sive, and none of it has ever been pas­sive! All of it re­volves around giv­ing a shit, day af­ter day, about some­thing spe­cific. I don’t think any­one has ever found a way around that and I don’t think any­one will.

The pas­sive in­come thing was a fan­tasy about not hav­ing to give a shit.

This is a ter­ri­ble foun­da­tion for pretty much any­thing.

The af­fil­i­ate SEO blogs are be­ing slaugh­tered right now by AI-generated con­tent. The peo­ple who spent years pro­duc­ing al­go­rith­mi­cally op­ti­mized con­tent of no value to hu­mans are get­ting out­com­peted by soft­ware that does the ex­act same thing, faster and cheaper. Facebook ad costs went through the roof and took the drop­ship­ping gold rush with them. The biggest pas­sive in­come gu­rus have al­ready piv­oted to sell­ing AI courses. The ma­chine keeps run­ning. It just swaps out the brochure.

But I’ve no­ticed more peo­ple talk­ing about what I’d call “give a shit” busi­nesses - peo­ple who make fur­ni­ture, run plumb­ing com­pa­nies, write soft­ware they ac­tu­ally use them­selves. Stuff where the an­swer to “why does your busi­ness ex­ist?” is­n’t “to gen­er­ate pas­sive in­come for me.” This works a lot bet­ter than the lap­top-on-the-beach grind.

Jade Roller Guy, if you’re out there: I hope you found some­thing real.

I hope it keeps you busy.

A bill in­tro­duced by Representative Josh Gottheimer in the House on April 13 would re­quire Apple, Google, and every other op­er­at­ing sys­tem ven­dor to ver­ify the age of any­one set­ting up a new de­vice in the United States.

The leg­is­la­tion, H. R. 8250, trav­els un­der the friend­lier name of the Parents Decide Act, and it is among the most ag­gres­sive sur­veil­lance man­dates ever pro­posed for American con­sumer tech­nol­ogy.

We ob­tained a copy of the bill for you here.

The press re­leases de­scrib­ing it lead with chil­dren. The text de­scribes some­thing much larger. To con­firm a child is un­der 18, the sys­tem has to iden­tify every­one else, too, and the bill builds the in­fra­struc­ture to do ex­actly that.

This is child safety as a de­liv­ery mech­a­nism for mass iden­ti­fi­ca­tion. The pat­tern is fa­mil­iar by now. A gen­uine harm gets named, a sym­pa­thetic vic­tim gets cen­tered, and the so­lu­tion pro­posed re­shapes the dig­i­tal lives of three hun­dred mil­lion peo­ple who were not the prob­lem.

The Parents Decide Act fol­lows that tem­plate with un­usual pre­ci­sion. It takes the real suf­fer­ing of real chil­dren and uses it to jus­tify build­ing a na­tional iden­tity layer un­der­neath every de­vice sold in the coun­try, ad­min­is­tered by two pri­vate com­pa­nies, with the de­tails to be filled in later.

The man­date sits in Section 2(a)(1), which ob­lig­ates providers to “Require any user of the op­er­at­ing sys­tem to pro­vide the date of birth of the user” both to set up an ac­count and to use the de­vice at all. Adults in­cluded.

There is no carve-out for grown users, no opt-out for peo­ple who sim­ply want to turn on a phone with­out hand­ing a date of birth to Apple or Google first.

The age check is the en­try fee for own­ing a com­puter. What hap­pens to that data af­ter­ward gets handed off to the Federal Trade Commission to sort out later. A fed­eral bill that man­dates iden­ti­fi­ca­tion as a con­di­tion of us­ing a gen­eral-pur­pose com­put­ing de­vice rep­re­sents some­thing the United States has not pre­vi­ously had, which is a na­tional ID re­quire­ment for turn­ing on a de­vice.

Gottheimer framed the pro­posal at a Ridgewood news con­fer­ence on April 2, stand­ing out­side the lo­cal YMCA with a coali­tion of al­lies. “With each pass­ing day, the in­ter­net is be­com­ing more and more treach­er­ous for our kids. We’re not just talk­ing about so­cial me­dia any­more — we’re talk­ing about ar­ti­fi­cial in­tel­li­gence and plat­forms that are shap­ing how our kids think, feel, and act, of­ten with­out any real guardrails,” he said.

His di­ag­no­sis of the cur­rent sys­tem is ac­cu­rate enough. “Children are able to by­pass age re­quire­ments by en­ter­ing a dif­fer­ent birth­day and ac­cess­ing apps with­out any real ver­i­fi­ca­tion. Kids can by­pass age re­quire­ments by sim­ply typ­ing in a dif­fer­ent birth­day. That’s it. That’s the sys­tem,” he said.

The rem­edy he pro­poses just hap­pens to re­quire build­ing new sur­veil­lance plumb­ing un­der­neath every de­vice sold in the coun­try, and rout­ing that plumb­ing through two of the largest com­pa­nies on earth. The so­lu­tion cho­sen is dis­pro­por­tion­ate to the prob­lem, and dis­pro­por­tion­ate in a spe­cific di­rec­tion, which is the di­rec­tion of less pri­vacy and less anonymity for every­one.

Section 2(a)(3) di­rects op­er­at­ing sys­tem providers to “Develop a sys­tem to al­low an app de­vel­oper to ac­cess any in­for­ma­tion as is nec­es­sary” to ver­ify a user’s age.

Translated out of leg­isla­tive prose, Apple and Google be­come age bro­kers for the en­tire American app ecosys­tem. Every app that wants to check whether you are over 18, or over 13, or over 21, will be able to ping the op­er­at­ing sys­tem for an an­swer de­rived from the birth date you handed over at setup. The bill pre­sents this as a con­ve­nience. It is a new data pipeline be­tween the OS layer and every de­vel­oper who plugs into it, and the bill spends re­mark­ably lit­tle time ex­plain­ing how that pipeline will be con­strained.

Free speech im­pli­ca­tions travel through that same pipeline. Once the op­er­at­ing sys­tem knows your age with ver­i­fied cer­tainty, it can tell any app to de­liver, re­strict, or with­hold con­tent ac­cord­ingly. The bil­l’s sup­port­ers de­scribe this as parental con­trol. The in­fra­struc­ture it builds is a con­tent con­trol sys­tem, run­ning at the OS level, with Apple and Google as the gate­keep­ers of who sees what.

The First Amendment has his­tor­i­cally pro­tected the right to read, watch, and speak with­out first pre­sent­ing iden­ti­fi­ca­tion. This bill erodes that prin­ci­ple at its foun­da­tion. Once ver­i­fied age be­comes a stan­dard sig­nal flow­ing from the op­er­at­ing sys­tem to every app, the de­fault as­sump­tion shifts. Users are no longer pre­sump­tively anony­mous adults with full ac­cess to law­ful con­tent. They are iden­ti­fied sub­jects whose per­mis­sions are de­ter­mined by the data Apple or Google holds about them.

An age-ver­i­fi­ca­tion layer built to block AI chat­bots from mi­nors is also ca­pa­ble of block­ing jour­nal­ism a state deems too vi­o­lent, po­lit­i­cal com­men­tary an ad­min­is­tra­tion deems too in­flam­ma­tory, re­port­ing on drugs or protest tac­tics, or any other sub­ject a fu­ture reg­u­la­tor de­cides re­quires age gat­ing.

The in­fra­struc­ture is neu­tral about con­tent. It cares only that the user has been iden­ti­fied. Every fu­ture fight over what Americans are al­lowed to see on­line will start from a po­si­tion where the iden­ti­fi­ca­tion layer al­ready ex­ists, and the only re­main­ing ques­tion is who qual­i­fies for ac­cess. That is a pro­found change in how speech works, and the bill en­acts it while point­ing at chil­dren.

What the bill says about data pro­tec­tion is ef­fec­tively a to-do list for the FTC. Section 2(d)(1)(B) tells the Commission it must even­tu­ally is­sue rules en­sur­ing that birth dates are “collected in a se­cure man­ner to main­tain the pri­vacy of the user” and are “not stolen or breached.”

Those are out­comes, not mech­a­nisms. The leg­is­la­tion sets no re­ten­tion lim­its, no min­i­miza­tion re­quire­ments, no re­stric­tions on sec­ondary uses, and no pro­hi­bi­tion on link­ing age data to other iden­ti­fiers Apple and Google al­ready hold. It of­fers no guid­ance on how providers should ver­ify the age of a par­ent or guardian be­yond in­struct­ing the FTC to fig­ure that out within 180 days of en­act­ment. The en­tire ar­chi­tec­ture of the sys­tem is to be drawn up af­ter the fact by reg­u­la­tors work­ing un­der a safe-har­bor pro­vi­sion that shields op­er­at­ing sys­tem providers from li­a­bil­ity as long as they fol­low what­ever rules even­tu­ally emerge.

Congress is be­ing asked to au­tho­rize a sur­veil­lance sys­tem it has not de­signed, whose op­er­a­tion it does not un­der­stand, and whose safe­guards do not yet ex­ist.

The Parents Decide Act solves the self-re­ported-birth­day prob­lem by de­mand­ing some­thing ver­i­fi­able, which in prac­tice means a gov­ern­ment ID, a credit card, a bio­met­ric scan, or some com­bi­na­tion.

However, Gottheimer has not spec­i­fied which. The bill does not ei­ther. It’s up to the FTC to de­cide.

Operating sys­tem providers will, and the in­cen­tives point to­ward what­ever is cheap­est to de­ploy at scale. Facial analy­sis is cheap. ID up­loads are cheap. What is ex­pen­sive is build­ing a ver­i­fi­ca­tion sys­tem that does not also cre­ate a per­sis­tent, cross-ref­er­enced data­base of every­one who has ever ac­ti­vated a phone. The in­cen­tives run di­rectly against user pri­vacy, and the bill pro­vides no mean­ing­ful coun­ter­weight.

The bill also dep­u­tizes a du­op­oly. Requiring “operating sys­tem providers” to per­form na­tion­wide age ver­i­fi­ca­tion is a re­quire­ment only two com­pa­nies can eas­ily sat­isfy in the mo­bile space, and a hand­ful more across desk­top and con­sole plat­forms.

Smaller OS de­vel­op­ers, open-source pro­jects, Linux dis­tri­b­u­tions, cus­tom Android forks, pri­vacy-fo­cused al­ter­na­tives, all face a com­pli­ance bur­den de­signed around the as­sump­tion that the provider is a tril­lion-dol­lar firm with le­gal staff and bio­met­ric-scan­ning part­ner­ships al­ready in place.

The safe har­bor in Section 2(b) pro­tects providers who fol­low the rules, but fol­low­ing the rules re­quires in­fra­struc­ture only the in­cum­bents can build. A law nom­i­nally aimed at tech com­pa­nies en­trenches the two tech com­pa­nies most re­spon­si­ble for the sta­tus quo.

Apple and Google be­come the manda­tory iden­tity check­points for every app de­vel­oper in the coun­try, which is a com­mer­cial po­si­tion worth a great deal of money and a great deal of lever­age. Any fu­ture com­peti­tor that wants to build a pri­vacy-re­spect­ing op­er­at­ing sys­tem will dis­cover the law has made that ef­fec­tively il­le­gal.

There is also an­other change buried in the text. The de­f­i­n­i­tion of “operating sys­tem” in Section 2(g)(4) cov­ers “software that sup­ports the ba­sic func­tions of a com­puter, mo­bile de­vice, or any other gen­eral pur­pose com­put­ing de­vice.” That lan­guage reaches well be­yond phones and tablets.

Laptops run op­er­at­ing sys­tems. Desktop com­put­ers run op­er­at­ing sys­tems. Gaming con­soles, smart TVs, cars with in­fo­tain­ment soft­ware, and a grow­ing cat­a­log of am­bi­ent de­vices all qual­ify un­der a plain read­ing of the de­f­i­n­i­tion. The bill does not dis­tin­guish be­tween the fam­ily iPad and the lap­top a col­lege stu­dent uses for course­work. Every de­vice with an OS be­comes a de­vice that ver­i­fies age at setup, and by ex­ten­sion, a de­vice that iden­ti­fies its user at setup. The scope creep is built into the de­f­i­n­i­tions.

Gottheimer cited cases of teenagers al­legedly harmed by AI chat­bots and by al­go­rith­mi­cally pro­moted con­tent about self-harm.

What the bill does with those harms is use them as jus­ti­fi­ca­tion for an iden­tity sys­tem that ap­plies to every user. The tem­plate is con­sis­tent: a child is hurt, leg­is­la­tion is drafted, the leg­is­la­tion re­shapes the dig­i­tal en­vi­ron­ment of every­one, child and adult, sub­ject and by­stander alike.

Less in­va­sive al­ter­na­tives ex­ist and have ex­isted for years.

Device-level parental con­trols al­ready ship with iOS and Android. Family Sharing and Google Family Link al­ready let par­ents con­fig­ure age-ap­pro­pri­ate re­stric­tions. App stores al­ready al­low per-app age rat­ings.

None of these re­quire every user in the coun­try to prove their age to Apple or Google when turn­ing on a phone. The bill skips past those op­tions in fa­vor of a man­date that treats uni­ver­sal age ver­i­fi­ca­tion as the base­line con­di­tion of de­vice own­er­ship.

Protecting chil­dren does not re­quire build­ing any of this. The bil­l’s au­thors chose to build it any­way, and the choice tells you what the bill is ac­tu­ally for.

Last year, I was telegraphed a sub­lim­i­nal man­date from the in­die rock pow­ers that be: I was sup­posed to like Geese. The young Brooklynites make good mu­sic, but are they the sav­iors of rock and roll, the defin­ing rock band of Gen Z, the sec­ond com­ing of The Strokes?

The buzz around the band would sug­gest so. After their al­bum “Getting Killed” came out in September, the band was un­avoid­able if you’re the kind of per­son who refers to con­certs as “shows.” When front­man Cameron Winter played an “extremely sold-out” solo set at Carnegie Hall, peo­ple in the au­di­ence seemed con­vinced that they’d be able to look back on that night in 50 years and tell their grand­chil­dren that they wit­nessed a sem­i­nal mo­ment in American mu­si­cal his­tory — the birth of the next Bob Dylan. How could any­one live up to that hype?

That’s why, when Wired re­ported that Geese’s pop­u­lar­ity was a psyop, I felt vin­di­cated — I was right! I knew it! I was smarter than every­one for only ca­su­ally en­joy­ing Geese!

But it’s never that sim­ple. The real story is that Geese worked with a mar­ket­ing firm called Chaotic Good, which cre­ates thou­sands of so­cial me­dia ac­counts de­signed to man­u­fac­ture trends on be­half of their clients, which also in­clude TikTok fa­vorites Alex Warren and Zara Larsson. This rev­e­la­tion has in­spired a range of re­ac­tions, from feel­ings of be­trayal to con­fu­sion at why any­one is mad about a band do­ing mar­ket­ing, a nor­mal thing that bands do.

“On TikTok, it’s re­ally easy to get views. You just post trend­ing au­dios. But artists can’t do that, be­cause they want to pro­mote their own mu­sic,” ex­plained Chaotic Good co-founder Andrew Spelman in an in­ter­view with Billboard. “So a big part of what we are do­ing is post­ing enough vol­ume across enough ac­counts with enough im­pres­sions to try to sim­u­late the idea that the song is trend­ing or mov­ing.”

When you learn how preva­lent these mar­ket­ing strate­gies are, it kind of feels like you’re a kid who just learned that the Tooth Fairy is­n’t real — you prob­a­bly had a hunch that some­thing was up, but you want to be­lieve in the fan­tasy that a flut­ter­ing fae is sneak­ing into your room, and every vi­ral suc­cess story is a fairy tale.

It’s not just the mu­sic in­dus­try tak­ing ad­van­tage of this mar­ket­ing strat­egy — young startup founders are fol­low­ing the same play­book.

While prepar­ing for an in­ter­view with the Gen Z founders of the fash­ion app Phia, I searched TikTok to see what real peo­ple were say­ing about the app. I found videos re­peat­ing the same talk­ing points about how Bill Gates’ daugh­ter cre­ated an app that helps you save money on lux­ury prod­ucts, or how us­ing Phia is like hav­ing a per­sonal shop­ping as­sis­tant that wants you to get the best deals. When I clicked on these ac­counts, I found that many of them only ever posted videos about Phia.

It’s not like I caught Phia in some “gotcha” mo­ment. Founders Phoebe Gates and Sophia Kianni aren’t try­ing to hide their so­cial me­dia strat­egy — this is just how mar­ket­ing works now.

“One thing we’ve been try­ing lately is ba­si­cally run­ning a cre­ator farm, so we have a ton of dif­fer­ent col­lege stu­dents that we pay to make videos about Phia on their own ac­counts,” Kianni said on her pod­cast. “This is an ap­proach that’s re­ally fo­cused on vol­ume. We have like ten cre­ators, they post twice a day, and we ul­ti­mately reach like 600 videos to­tal.”

On TikTok-like feeds, peo­ple watch videos in a vac­uum, sep­a­rate from the rest of a cre­ator’s ac­count. Few view­ers will stop to look at what else that per­son is post­ing, so they won’t sus­pect that the post about this cool new app could be an in­or­ganic pro­mo­tion.

Creators will sim­i­larly pay armies of teenagers on Discord to make clips of their streams and post them en masse.

“That’s been go­ing on for a bit,” Karat Financial co-founder Eric Wei told TechCrunch last year. “Drake does it. A lot of the biggest cre­ators and stream­ers in the world have been do­ing it — Kai Cenat [a top Twitch streamer] has done it — hit­ting mil­lions of im­pres­sions … If it’s al­go­rith­mi­cally de­ter­mined, clip­ping sud­denly makes sense, be­cause it can come from any ran­dom ac­count that just has re­ally good clips.”

Marketing firms like Chaotic Good scale that same ap­proach — in­stead of pay­ing col­lege stu­dents or teenage fans to make videos, they buy hun­dreds of iPhones and make a bunch of so­cial me­dia ac­counts that they can use to fab­ri­cate a vi­ral trend. Spelman told Billboard that Chaotic Good’s of­fice is “overrun with iPhones,” and that they have so many phones that they’re treated like VIPs at Verizon.

“Unfortunately, a lot of the in­ter­net is ma­nip­u­la­tion … Everything on the in­ter­net is fake. One thing that we al­ways say is all opin­ions are formed in the TikTok com­ments,” Chaotic Good co-founder Jesse Coren noted.

This is the same line of think­ing that fu­els the Dead Internet Theory, which ar­gues that bot-gen­er­ated con­tent dom­i­nates the web.

If Chaotic Good’s con­tent armies aren’t post­ing trend­ing au­dio, they’re com­ment­ing on posts about the com­pa­ny’s clients to con­trol the nar­ra­tive. Instead of wait­ing to see how fans will re­spond to a new song, they can use their ac­counts to flood the com­ments of videos and talk about how much they love the song.

For Geese, it’s an in­sult to be called an in­dus­try plant. After song­writer Eliza McLamb wrote the blog post that first con­nected Geese and Chaotic Good, the firm re­moved men­tion of Geese and “narrative cam­paigns” from its web­site. (The com­pany told Wired that it did this to pro­tect artists from be­ing “wrapped up in false ac­cu­sa­tions or mis­con­cep­tions about how their mu­sic was dis­cov­ered.”)

But like the un­apolo­getic mar­ket­ing be­hind some Gen Z star­tups, the global girl group Katseye has been in­cred­i­bly clear that they are the de­f­i­n­i­tion of in­dus­try plants — there’s lit­er­ally a Netflix do­cuseries, “Pop Star Academy,” that il­lus­trates how a room full of global record ex­ec­u­tives turned these six young women into su­per­stars, even pit­ting po­ten­tial mem­bers against each other in a sur­prise K-pop-style sur­vival show.

When “Pop Star Academy” came out, I watched it in a state of hor­ror — HYBE and Geffen treated these as­pir­ing teenage pop stars like cat­tle to mold into hu­man bill­boards that they could use to sell Erewhon smooth­ies and hair serums. But over the course of the eight-episode se­ries, I be­came deeply in­vested in these girls’ lives. I wanted to watch them thrive in the face of un­re­lent­ing in­dus­try pres­sure.

I’m sure that this is ex­actly what Katseye’s man­age­ment wanted from the doc­u­men­tary — to cul­ti­vate a fer­vent sense of sup­port and de­fen­sive­ness over the girls, even if it means paint­ing the ex­ec­u­tives as the bad guys. Fast-forward a few years, and Katseye is per­form­ing a song called “Gnarly” at the Grammys — a track that fans hated at first un­til, sud­denly, they did­n’t.

It’s hard not to think about Chaotic Good’s “narrative cam­paigns,” flood­ing com­ment sec­tions to con­trol dis­course. Though I hated “Gnarly” when it came out, I de­cided over time that it’s ac­tu­ally an avant-garde mas­ter­piece. Did I change my mind on my own, or was it changed for me? For as much pride as I took in re­sist­ing the hype around Geese, I am so wrapped up in Katseye that I’ve spent hours spec­u­lat­ing on Reddit fo­rums about the real story be­hind Manon’s hia­tus.

Maybe Geese is a psyop, and maybe Katseye is an in­dus­try plant, but do we ac­tu­ally care?

This is not a rhetor­i­cal ques­tion. The Geese dis­course (which could also be man­u­fac­tured, now that I think about it!) has in­spired such var­ied re­sponses be­cause we have not es­tab­lished clear so­cial norms around what is nec­es­sary mar­ket­ing and what is in­au­then­tic growth hack­ing.

We, the fans, get to de­cide now where we draw the line.

Simple Made Easy (2011) — Rich’s fa­mous talk from Strange Loop 2011. Defines the dis­tinc­tion be­tween “simple” and “easy.”

Clojure at LispNYC (2007) - the first pub­lic talk about Clojure.

Sierra’s Blog on LispNYC Presentation — 2007. An early pub­lic in­tro­duc­tion to Clojure.

Are We There Yet? (2009) - The Clojure state model and a dis­sec­tion of time in pro­gram­ming.

Hammock Driven Development (2010) — On think­ing deeply about prob­lems be­fore writ­ing code.

The Value of Values (2012) — The case for im­mutable val­ues over mu­ta­ble ob­jects.

Writing Datomic in Clojure (2012) - An overview of Datomic and how Clojure was the per­fect lan­guage to write it in.

Expert to Expert: Rich Hickey and Brian Beckman - Inside Clojure (2013) - a long-form in­ter­view with Rich about Clojure.

Effective Programs - 10 Years of Clojure (2017) - Rich re­flects on the first 10 years of Clojure and the pri­or­i­ti­za­tion of Clojure’s fea­tures for solv­ing real-world prob­lems.

Talk Transcripts — Community-maintained tran­scripts of Clojure talks by Rich Hickey and oth­ers.

Rich Hickey Talks - A video playlist of many of Rich’s talks.

As Android de­vel­op­ers, you have many choices when it comes to the agents, tools, and LLMs you use for app de­vel­op­ment. Whether you are us­ing Gemini in Android Studio, Gemini CLI, Antigravity, or third-party agents like Claude Code or Codex, our mis­sion is to en­sure that high-qual­ity Android de­vel­op­ment is pos­si­ble every­where.

Today, we are in­tro­duc­ing a new suite of Android tools and re­sources for agen­tic work­flows — Android CLI with Android skills and the Android Knowledge Base. This col­lec­tion of tools is de­signed to elim­i­nate the guess­work of core Android de­vel­op­ment work­flows when you di­rect an agen­t’s work out­side of Android Studio, mak­ing your agents more ef­fi­cient, ef­fec­tive, and ca­pa­ble of fol­low­ing the lat­est rec­om­mended pat­terns and best prac­tices.

Whether you are just start­ing your de­vel­op­ment jour­ney on Android, are a sea­soned Android de­vel­oper, or man­ag­ing apps across mo­bile and web plat­forms, build­ing your apps with the lat­est guid­ance, tools, and AI-assistance is eas­ier than ever. No mat­ter which en­vi­ron­ment you be­gin with these re­sources, you can al­ways tran­si­tion your de­vel­op­ment ex­pe­ri­ence to Android Studio—where the state-of-the-art tools and agents for Android de­vel­op­ment are avail­able to help your app ex­pe­ri­ence truly shine.

Your agents per­form best when they have a light­weight, pro­gram­matic in­ter­face to in­ter­act with the Android SDK and de­vel­op­ment en­vi­ron­ment. So, at the heart of this new work­flow is a re­vi­tal­ized Android CLI. The new Android CLI serves as the pri­mary in­ter­face for Android de­vel­op­ment from the ter­mi­nal, fea­tur­ing com­mands for en­vi­ron­ment setup, pro­ject cre­ation, and de­vice man­age­ment—with more mod­ern ca­pa­bil­i­ties and easy up­data­bil­ity in mind.

In our in­ter­nal ex­per­i­ments, Android CLI im­proved pro­ject and en­vi­ron­ment setup by re­duc­ing LLM to­ken us­age by more than 70%, and tasks were com­pleted 3X faster than when agents at­tempted to nav­i­gate these tasks us­ing only the stan­dard toolsets.

Key ca­pa­bil­i­ties avail­able to you in­clude:

* SDK man­age­ment: Use an­droid sdk in­stall to down­load only the spe­cific com­po­nents needed, en­sur­ing a lean de­vel­op­ment en­vi­ron­ment.

* Snappy pro­ject cre­ation: The an­droid cre­ate com­mand gen­er­ates new pro­jects from of­fi­cial tem­plates, en­sur­ing the rec­om­mended ar­chi­tec­ture and best prac­tices are ap­plied from the very first line of code.

* Rapid de­vice cre­ation and de­ploy­ment: Create and man­age vir­tual de­vices with an­droid em­u­la­tor and de­ploy apps us­ing an­droid run, elim­i­nat­ing the guess­work in­volved in man­ual build and de­ploy cy­cles.

* Updatability: Run an­droid up­date to en­sure that you have the lat­est ca­pa­bil­i­ties avail­able.

While Android CLI will em­power your agen­tic de­vel­op­ment flows, it’s also been de­signed to stream­line CI, main­te­nance, and any other scripted au­toma­tion for the in­creas­ingly dis­trib­uted na­ture of Android de­vel­op­ment. Download and try out the Android CLI to­day!

Traditional doc­u­men­ta­tion can be de­scrip­tive, con­cep­tual, and high-level. While per­fect for learn­ing, LLMs of­ten re­quire pre­cise, ac­tion­able in­struc­tions to ex­e­cute com­plex work­flows with­out us­ing out­dated pat­terns and li­braries.

To bridge this gap, we are launch­ing the Android skills GitHub repos­i­tory. Skills are mod­u­lar, mark­down-based (SKILL.md) in­struc­tion sets that pro­vide a tech­ni­cal spec­i­fi­ca­tion for a task and are de­signed to trig­ger au­to­mat­i­cally when your prompt matches the skil­l’s meta­data, sav­ing you the has­sle of man­u­ally at­tach­ing doc­u­men­ta­tion to every prompt.

Android skills cover some of the most com­mon work­flows that some Android de­vel­op­ers and LLMs may strug­gle with—they help mod­els bet­ter un­der­stand and ex­e­cute spe­cific pat­terns that fol­low our best prac­tices and guid­ance on Android de­vel­op­ment.

In our ini­tial re­lease, the repos­i­tory in­cludes skills like:

If you’re us­ing Android CLI, you can browse and set up your agent work­flow with our grow­ing col­lec­tion of skills us­ing the an­droid skills com­mand. These skills can also live along­side any other skills you cre­ate, or third-party skills cre­ated by the Android de­vel­oper com­mu­nity. Learn more about get­ting started with Android skills.

The third com­po­nent we are launch­ing to­day is the Android Knowledge Base. Accessible through the an­droid docs com­mand and al­ready avail­able in the lat­est ver­sion of Android Studio, this spe­cial­ized data source en­ables agents to search and fetch the lat­est au­thor­i­ta­tive de­vel­oper guide­lines to use as rel­e­vant con­text.

By ac­cess­ing the fre­quently up­dated knowl­edge base, agents can ground their re­sponses in the most re­cent in­for­ma­tion from Android de­vel­oper docs, Firebase, Google Developers, and Kotlin docs. This en­sures that even if an LLM’s train­ing cut­off is a year old, it can still pro­vide guid­ance on the lat­est frame­works and pat­terns we rec­om­mend to­day.

In ad­di­tion to em­pow­er­ing de­vel­op­ers and agents to han­dle pro­ject setup and boil­er­plate code, we’ve also de­signed these new tools and re­sources to make it eas­ier to tran­si­tion to Android Studio. That means you can start a pro­to­type quickly with an agent us­ing Android CLI and then open the pro­ject in Android Studio to fine-tune your UI with vi­sual tools for code edit­ing, UI de­sign, deep de­bug­ging, and ad­vanced pro­fil­ing that scale with the grow­ing ca­pa­bil­i­ties of your app.

And when it is time to build a high-qual­ity app for large-scale pub­li­ca­tion across var­i­ous de­vice types, our agent in Android Studio is here to help, while lever­ag­ing the lat­est de­vel­op­ment best prac­tices and li­braries. Beyond the pow­er­ful Agent and Planning Modes for ac­tive de­vel­op­ment, we have in­tro­duced an AI-powered New Project flow, which pro­vides an en­try point to rapidly pro­to­typ­ing your next great idea for Android.

These built-in agents make it sim­ple to ex­tend your app ideas across phones, fold­ables, tablets, Wear OS, Android Auto, and Android TV. Equipped with full con­text of your pro­jec­t’s source code and a com­pre­hen­sive suite of de­bug­ging, pro­fil­ing, and em­u­la­tion tools, you have an end-to-end, AI-accelerated toolkit at your dis­posal.

Android CLI is avail­able in pre­view to­day, along with a grow­ing set of Android skills and knowl­edge for agents. To get started, head over to d.an­droid.com/​tools/​agents to down­load Android CLI.

Hundreds of pre­vi­ously redacted records re­veal how Amazon has put pres­sure on in­de­pen­dent sell­ers us­ing its plat­form into rais­ing their prices on the sites of com­peti­tors such as Walmart and Target, so that Amazon can ap­pear to have lower prices, California au­thor­i­ties al­lege.

The global con­glom­er­ate be­came con­cerned even if a com­peti­tor was sell­ing an item for as lit­tle as a penny less, ac­cord­ing to one seg­ment of the newly unredacted ev­i­dence.

The doc­u­ments — which have never pre­vi­ously been re­ported on — in­clude in­ter­nal emails, de­po­si­tion tes­ti­mony and con­fi­den­tial cor­po­rate pre­sen­ta­tions that the California at­tor­ney gen­eral, Rob Bonta, ob­tained as part of a civil case his of­fice launched in 2022 ac­cus­ing Amazon of large-scale price-fix­ing.

The Guardian ob­tained and re­viewed the cache of ev­i­dence, which has been filed in San Francisco county su­pe­rior court but has not yet be­come pub­licly avail­able. Within the doc­u­ments, lawyers for the state of California have un­masked key de­tails, para­graphs and some­times whole pages that had pre­vi­ously been blacked out. A judge per­mit­ted some redac­tions to re­main at Amazon’s re­quest.

In a state­ment, Bonta said the newly un­veiled ev­i­dence re­in­forced his of­fice’s claims that Amazon’s ac­tions “unlawfully pun­ishes sell­ers whose prod­ucts are sold at lower prices by other on­line re­tail­ers”.

“Especially while con­sumers face an af­ford­abil­ity cri­sis, there is no room for il­le­gal prac­tices that im­pede com­pe­ti­tion and raise prices,” Bonta said. “California looks for­ward to our trial in January 2027.”

Amazon has called the claims in the law­suit “entirely false and mis­guided”.

“Amazon is con­sis­tently iden­ti­fied as America’s low­est-priced on­line re­tailer, and it is ironic that the at­tor­ney gen­eral seeks to have us fea­ture higher prices in ways that would harm con­sumers and com­pe­ti­tion,” the com­pany said in a state­ment.

For years, the state al­leges, Amazon has used au­to­mated tools to track how in­de­pen­dent ven­dors on its plat­form price their goods on com­peti­tor sites, then lever­aged its dom­i­nant po­si­tion in e-com­merce to en­sure that those prices do not fall be­low those on Amazon, even though Amazon of­ten charges ven­dors far more in fees.

The state’s law­suit claims that Amazon pun­ishes ven­dors that dare to of­fer dis­counts on their own sites or com­peti­tor sites like Walmart, sup­press­ing their sales on Amazon by tak­ing away the ven­dors’ ac­cess to crit­i­cal fea­tures, such as its site’s “Buy Box” — the panel on the right side of the site where cus­tomers see but­tons like “Add to cart” and “Buy Now”.

In one pre­vi­ously redacted de­po­si­tion, marked “highly con­fi­den­tial”, Mayer Handler, owner of a cloth­ing com­pany called Leveret, tes­ti­fied that he re­ceived an email in October 2022 from Amazon no­ti­fy­ing him that one of his prod­ucts was “no longer el­i­gi­ble to be a fea­tured of­fer” through Amazon’s Buy Box.

The tech gi­ant, he tes­ti­fied, had sup­pressed the item, a tiger-themed, tod­dler’s pa­jama set, be­cause his com­pany was sell­ing it for $19.99 on Amazon, a sin­gle cent higher than what his com­pany was of­fer­ing it for on Walmart.

A. That Amazon — the price on Amazon was higher than the price was on Walmart.

Q. And how much higher?

A. One penny.

Afterwards, Handler tes­ti­fied, his com­pany “changed pric­ing on Walmart to match or ex­ceed Amazon’s price” or changed the item’s prod­uct code to try to throw off Amazon’s price track­ing sys­tem.

We changed pric­ing on Walmart to match or ex­ceed Amazon’s price. Or we changed the code.

In re­sponse to a ques­tion from the Guardian, Handler crit­i­cized Amazon for track­ing prices across the in­ter­net and “shadow” block­ing his com­pa­ny’s prod­ucts — tac­tics which he said were de­priv­ing con­sumers of “lower prices”.

“Maybe that’s cap­i­tal­ism,” he wrote. “Or that’s a mo­nop­oly caus­ing price hikes on the con­sumer.”

In an­other un­sealed de­po­si­tion, Terry Esbenshade, a Pennsylvania gar­den store sup­plier, tes­ti­fied in October 2024 that when­ever his prod­ucts lost Amazon’s Buy Box be­cause of lower prices else­where on the in­ter­net, his sales on Amazon would plum­met by about 80%. This fi­nan­cial re­al­ity forced him to try to raise his prod­ucts’ prices with other re­tail­ers else­where, he said.

In one in­stance, Esbenshade tes­ti­fied, he dis­cov­ered that one of his com­pa­ny’s bet­ter-sell­ing pa­tio ta­bles had “become sup­pressed” on Amazon.

Esbenshade was­n’t sure why, he re­called, un­til some­one at Amazon sug­gested he look at Wayfair, an­other on­line re­tailer that hap­pened to be sell­ing his pa­tio table be­low Amazon’s price.

The busi­ness­man went on­line and set up a new min­i­mum ad­ver­tised price for the table on Wayfair to en­sure it was higher than Amazon’s.

“So that raised the price up, and, voila, my prod­uct came back” on Amazon, he said, thanks to the re­in­state­ment of the Buy Box.

Amazon has ar­gued that its prac­tices ac­tu­ally pro­mote, in­cen­tivize and re­ward com­pe­ti­tion. The com­pany said it works “to en­sure its cus­tomers see of­fers with low, com­pet­i­tive prices” and pro­vide “the best pos­si­ble” cus­tomer ex­pe­ri­ence for on­line shop­pers.

“Just like any store owner who would­n’t want to pro­mote a bad deal to their cus­tomers, we don’t high­light or pro­mote of­fers that are not com­pet­i­tively priced,” the com­pany said in its state­ment. “It’s part of our com­mit­ment to fea­tur­ing low prices to earn and main­tain cus­tomer trust.”

The com­pany has also de­nied that it had ever tried to shield it­self from com­pe­ti­tion through its agree­ments with in­de­pen­dent sell­ers.

“Amazon de­nies that the in­tent or ef­fect of any agree­ment it has en­tered into with third-party sell­ers or ven­dors is to in­su­late it­self from price com­pe­ti­tion” or “entrench any po­si­tion of ‘dominance’”, the com­pany as­serted in an an­swer to the state’s law­suit.

But Bonta’s of­fice said that the newly unredacted ex­hibits show Amazon em­ploy­ees have proac­tively sought to un­der­mine mar­ket com­pe­ti­tion and were aware of the ef­fects of their ac­tions on prices.

In one ex­am­ple, the state al­leged, an Amazon en­gi­neer de­scribed the com­pa­ny’s use of Buy Box sup­pres­sion and an in­ter­nal pro­gram, known as SC-FOD, to un­der­mine ven­dors’ will­ing­ness to sell prod­ucts on Temu, a com­pet­ing e-com­merce site.

map them, FOD them, and they move out of Temu

But ye hua hai toh its a huge suc­cess for us

In an­other ex­am­ple, a se­nior Amazon em­ployee sent an in­ter­nal email in August 2023 de­scrib­ing how the com­pa­ny’s Buy Box sup­pres­sions were caus­ing an Indiana-based home goods and fur­ni­ture seller to reg­u­larly raise his prices on other sites.

“When this hap­pens, they claim they search for the lower price, and when they find it, they raise it to match the price on Amazon,” the em­ployee wrote, which was read aloud in a con­fi­den­tial de­po­si­tion last year.

Amazon, which re­cently over­took Walmart to be­come the world’s largest com­pany by rev­enue, is America’s No 1 on­line re­tailer by a huge mar­gin.

By the end of 2022, Amazon ac­counted for nearly half of US e-com­merce re­tail spend­ing, com­pared with less than 8% for Walmart, its near­est com­peti­tor, ac­cord­ing to num­bers com­piled by PYMTS.com, an an­a­lyt­ics firm. In the third quar­ter of 2025, Amazon took in 56% of on­line re­tail spend­ing com­pared with Walmart’s 9.6%, PYMTS found.

Amazon did not im­me­di­ately pro­vide an­swers to ques­tions from the Guardian ahead of pub­li­ca­tion. The Guardian will up­date this ar­ti­cle when it re­ceives a re­sponse.

The trial in the California at­tor­ney gen­er­al’s law­suit against Amazon is cur­rently sched­uled to be­gin on 19 January 2027.

The last ques­tion was asked for the first time, half in jest, on May 21, 2061, at a time when hu­man­ity first stepped into the light. The ques­tion came about as a re­sult of a five dol­lar bet over high­balls, and it hap­pened this way:

Alexander Adell and Bertram Lupov were two of the faith­ful at­ten­dants of Multivac. As well as any hu­man be­ings could, they knew what lay be­hind the cold, click­ing, flash­ing face — miles and miles of face — of that gi­ant com­puter. They had at least a vague no­tion of the gen­eral plan of re­lays and cir­cuits that had long since grown past the point where any sin­gle hu­man could pos­si­bly have a firm grasp of the whole.

Multivac was self-ad­just­ing and self-cor­rect­ing. It had to be, for noth­ing hu­man could ad­just and cor­rect it quickly enough or even ad­e­quately enough — so Adell and Lupov at­tended the mon­strous gi­ant only lightly and su­per­fi­cially, yet as well as any men could. They fed it data, ad­justed ques­tions to its needs and trans­lated the an­swers that were is­sued. Certainly they, and all oth­ers like them, were fully en­ti­tled to share In the glory that was Multivac’s.

For decades, Multivac had helped de­sign the ships and plot the tra­jec­to­ries that en­abled man to reach the Moon, Mars, and Venus, but past that, Earth’s poor re­sources could not sup­port the ships. Too much en­ergy was needed for the long trips. Earth ex­ploited its coal and ura­nium with in­creas­ing ef­fi­ciency, but there was only so much of both.

But slowly Multivac learned enough to an­swer deeper ques­tions more fun­da­men­tally, and on May 14, 2061, what had been the­ory, be­came fact.

The en­ergy of the sun was stored, con­verted, and uti­lized di­rectly on a planet-wide scale. All Earth turned off its burn­ing coal, its fis­sion­ing ura­nium, and flipped the switch that con­nected all of it to a small sta­tion, one mile in di­am­e­ter, cir­cling the Earth at half the dis­tance of the Moon. All Earth ran by in­vis­i­ble beams of sun­power.

Seven days had not suf­ficed to dim the glory of it and Adell and Lupov fi­nally man­aged to es­cape from the pub­lic func­tion, and to meet in quiet where no one would think of look­ing for them, in the de­serted un­der­ground cham­bers, where por­tions of the mighty buried body of Multivac showed. Unattended, idling, sort­ing data with con­tented lazy click­ings, Multivac, too, had earned its va­ca­tion and the boys ap­pre­ci­ated that. They had no in­ten­tion, orig­i­nally, of dis­turb­ing it.

They had brought a bot­tle with them, and their only con­cern at the mo­ment was to re­lax in the com­pany of each other and the bot­tle.

“It’s amaz­ing when you think of it,” said Adell. His broad face had lines of weari­ness in it, and he stirred his drink slowly with a glass rod, watch­ing the cubes of ice slur clum­sily about. “All the en­ergy we can pos­si­bly ever use for free. Enough en­ergy, if we wanted to draw on it, to melt all Earth into a big drop of im­pure liq­uid iron, and still never miss the en­ergy so used. All the en­ergy we could ever use, for­ever and for­ever and for­ever.”

Lupov cocked his head side­ways. He had a trick of do­ing that when he wanted to be con­trary, and he wanted to be con­trary now, partly be­cause he had had to carry the ice and glass­ware. “Not for­ever,” he said.

“Oh, hell, just about for­ever. Till the sun runs down, Bert.”

“All right, then. Billions and bil­lions of years. Twenty bil­lion, maybe. Are you sat­is­fied?”

Lupov put his fin­gers through his thin­ning hair as though to re­as­sure him­self that some was still left and sipped gen­tly at his own drink. “Twenty bil­lion years is­n’t for­ever.”

“Will, it will last our time, won’t it?”

“So would the coal and ura­nium.”

“All right, but now we can hook up each in­di­vid­ual space­ship to the Solar Station, and it can go to Pluto and back a mil­lion times with­out ever wor­ry­ing about fuel. You can’t do THAT on coal and ura­nium. Ask Multivac, if you don’t be­lieve me.”

“I don’t have to ask Multivac. I know that.”

“Then stop run­ning down what Multivac’s done for us,” said Adell, blaz­ing up. “It did all right.”

“Who says it did­n’t? What I say is that a sun won’t last for­ever. That’s all I’m say­ing. We’re safe for twenty bil­lion years, but then what?” Lupov pointed a slightly shaky fin­ger at the other. “And don’t say we’ll switch to an­other sun.”

There was si­lence for a while. Adell put his glass to his lips only oc­ca­sion­ally, and Lupov’s eyes slowly closed. They rested.

Then Lupov’s eyes snapped open. “You’re think­ing we’ll switch to an­other sun when ours is done, aren’t you?”

“Sure you are. You’re weak on logic, that’s the trou­ble with you. You’re like the guy in the story who was caught in a sud­den shower and Who ran to a grove of trees and got un­der one. He was­n’t wor­ried, you see, be­cause he fig­ured when one tree got wet through, he would just get un­der an­other one.”

“I get it,” said Adell. “Don’t shout. When the sun is done, the other stars will be gone, too.”

“Darn right they will,” mut­tered Lupov. “It all had a be­gin­ning in the orig­i­nal cos­mic ex­plo­sion, what­ever that was, and it’ll all have an end when all the stars run down. Some run down faster than oth­ers. Hell, the gi­ants won’t last a hun­dred mil­lion years. The sun will last twenty bil­lion years and maybe the dwarfs will last a hun­dred bil­lion for all the good they are. But just give us a tril­lion years and every­thing will be dark. Entropy has to in­crease to max­i­mum, that’s all.”

“I know all about en­tropy,” said Adell, stand­ing on his dig­nity.

“I know as much as you do.”

“Then you know every­thing’s got to run down some­day.”

“All right. Who says they won’t?”

“You did, you poor sap. You said we had all the en­ergy we needed, for­ever. You said ’forever.’”

“It was Adell’s turn to be con­trary. “Maybe we can build things up again some­day,” he said.

“You ask Multivac. I dare you. Five dol­lars says it can’t be done.”

Adell was just drunk enough to try, just sober enough to be able to phrase the nec­es­sary sym­bols and op­er­a­tions into a ques­tion which, in words, might have cor­re­sponded to this: Will mankind one day with­out the net ex­pen­di­ture of en­ergy be able to re­store the sun to its full youth­ful­ness even af­ter it had died of old age?

Or maybe it could be put more sim­ply like this: How can the net amount of en­tropy of the uni­verse be mas­sively de­creased?

Multivac fell dead and silent. The slow flash­ing of lights ceased, the dis­tant sounds of click­ing re­lays ended.

Then, just as the fright­ened tech­ni­cians felt they could hold their breath no longer, there was a sud­den spring­ing to life of the tele­type at­tached to that por­tion of Multivac. Five words were printed: INSUFFICIENT DATA FOR MEANINGFUL ANSWER.

By next morn­ing, the two, plagued with throb­bing head and cot­tony mouth, had for­got­ten about the in­ci­dent.

Jerrodd, Jerrodine, and Jerrodette I and II watched the starry pic­ture in the visi­plate change as the pas­sage through hy­per­space was com­pleted in its non-time lapse. At once, the even pow­der­ing of stars gave way to the pre­dom­i­nance of a sin­gle bright mar­ble-disk, cen­tered.

“That’s X-23,” said Jerrodd con­fi­dently. His thin hands clamped tightly be­hind his back and the knuck­les whitened.

The lit­tle Jerrodettes, both girls, had ex­pe­ri­enced the hy­per­space pas­sage for the first time in their lives and were self-con­scious over the mo­men­tary sen­sa­tion of in­side-out­ness. They buried their gig­gles and chased one an­other wildly about their mother, scream­ing, “We’ve reached X-23 — we’ve reached X-23 — we’ve —”

“Quiet, chil­dren,” said Jerrodine sharply. “Are you sure, Jerrodd?”

“What is there to be but sure?” asked Jerrodd, glanc­ing up at the bulge of fea­ture­less metal just un­der the ceil­ing. It ran the length of the room, dis­ap­pear­ing through the wall at ei­ther end. It was as long as the ship.

Jerrodd scarcely knew a thing about the thick rod of metal ex­cept that it was called a Microvac, that one asked it ques­tions if one wished; that if one did not it still had its task of guid­ing the ship to a pre­ordered des­ti­na­tion; of feed­ing on en­er­gies from the var­i­ous Sub-galactic Power Stations; of com­put­ing the equa­tions for the hy­per­spa­cial jumps.

Jerrodd and his fam­ily had only to wait and live in the com­fort­able res­i­dence quar­ters of the ship.

Someone had once told Jerrodd that the “ac” at the end of “Microvac” stood for “analog com­puter” in an­cient English, but he was on the edge of for­get­ting even that.

Jerrodine’s eyes were moist as she watched the visi­plate. “I can’t help it. I feel funny about leav­ing Earth.”

“Why for Pete’s sake?” de­manded Jerrodd. “We had noth­ing there. We’ll have every­thing on X-23. You won’t be alone. You won’t be a pi­o­neer. There are over a mil­lion peo­ple on the planet al­ready. Good Lord, our great grand­chil­dren will be look­ing for new worlds be­cause X-23 will be over­crowded.”

Then, af­ter a re­flec­tive pause, “I tell you, it’s a lucky thing the com­put­ers worked out in­ter­stel­lar travel the way the race is grow­ing.”

Jerrodette I said promptly, “Our Microvac is the best Microvac in the world.”

“I think so, too,” said Jerrodd, tou­sling her hair.

It was a nice feel­ing to have a Microvac of your own and Jerrodd was glad he was part of his gen­er­a­tion and no other. In his fa­ther’s youth, the only com­put­ers had been tremen­dous ma­chines tak­ing up a hun­dred square miles of land. There was only one to a planet. Planetary ACs they were called. They had been grow­ing in size steadily for a thou­sand years and then, all at once, came re­fine­ment. In place of tran­sis­tors had come mol­e­c­u­lar valves so that even the largest Planetary AC could be put into a space only half the vol­ume of a space­ship.

Jerrodd felt up­lifted, as he al­ways did when he thought that his own per­sonal Microvac was many times more com­pli­cated than the an­cient and prim­i­tive Multivac that had first tamed the Sun, and al­most as com­pli­cated as Earth’s Planetary AC (the largest) that had first solved the prob­lem of hy­per­spa­tial travel and had made trips to the stars pos­si­ble.

“So many stars, so many plan­ets,” sighed Jerrodine, busy with her own thoughts. “I sup­pose fam­i­lies will be go­ing out to new plan­ets for­ever, the way we are now.”

“Not for­ever,” said Jerrodd, with a smile. “It will all stop some­day, but not for bil­lions of years. Many bil­lions. Even the stars run down, you know. Entropy must in­crease.”

“Entropy, lit­tle sweet, is just a word which means the amount of run­ning-down of the uni­verse. Everything runs down, you know, like your lit­tle walkie-talkie ro­bot, re­mem­ber?”

“Can’t you just put in a new power-unit, like with my ro­bot?”

“The stars are the power-units, dear. Once they’re gone, there are no more power-units.”

Jerrodette I at once set up a howl. “Don’t let them, daddy. Don’t let the stars run down.”

“Now look what you’ve done, “ whis­pered Jerrodine, ex­as­per­ated.

“How was I to know it would frighten them?” Jerrodd whis­pered to Jerrodine. “It will quiet them down.” (Jerrodette II was be­gin­ning to cry, also.)

Jarrodd shrugged. “Now, now, hon­eys. I’ll ask Microvac. Don’t worry, he’ll tell us.”

Jerrodd cupped the strip of thin cel­lu­film and said cheer­fully, “See now, the Microvac says it will take care of every­thing when the time comes so don’t worry.”

Jerrodine said, “and now chil­dren, it’s time for bed. We’ll be in our new home soon.”

Jerrodd read the words on the cel­lu­film again be­fore de­stroy­ing it: INSUFFICIENT DATA FOR A MEANINGFUL ANSWER.

He shrugged and looked at the visi­plate. X-23 was just ahead.

VJ-23X of Lameth stared into the black depths of the three-di­men­sional, small-scale map of the Galaxy and said, “Are we ridicu­lous, I won­der, in be­ing so con­cerned about the mat­ter?”

MQ-17J of Nicron shook his head. “I think not. You know the Galaxy will be filled in five years at the pre­sent rate of ex­pan­sion.”

Both seemed in their early twen­ties, both were tall and per­fectly formed.

“Still,” said VJ-23X, “I hes­i­tate to sub­mit a pes­simistic re­port to the Galactic Council.”

“I would­n’t con­sider any other kind of re­port. Stir them up a bit. We’ve got to stir them up.”

VJ-23X sighed. “Space is in­fi­nite. A hun­dred bil­lion Galaxies are there for the tak­ing. More.”

“A hun­dred bil­lion is not in­fi­nite and it’s get­ting less in­fi­nite all the time. Consider! Twenty thou­sand years ago, mankind first solved the prob­lem of uti­liz­ing stel­lar en­ergy, and a few cen­turies later, in­ter­stel­lar travel be­came pos­si­ble. It took mankind a mil­lion years to fill one small world and then only fif­teen thou­sand years to fill the rest of the Galaxy. Now the pop­u­la­tion dou­bles every ten years —”

VJ-23X in­ter­rupted. “We can thank im­mor­tal­ity for that.”

“Very well. Immortality ex­ists and we have to take it into ac­count. I ad­mit it has its seamy side, this im­mor­tal­ity. The Galactic AC has solved many prob­lems for us, but in solv­ing the prob­lems of pre­vent­ing old age and death, it has un­done all its other so­lu­tions.”

“Yet you would­n’t want to aban­don life, I sup­pose.”

“Not at all,” snapped MQ-17J, soft­en­ing it at once to, “Not yet. I’m by no means old enough. How old are you?”

“I’m still un­der two hun­dred. —But to get back to my point. Population dou­bles every ten years. Once this Galaxy is filled, we’ll have an­other filled in ten years. Another ten years and we’ll have filled two more. Another decade, four more. In a hun­dred years, we’ll have filled a thou­sand Galaxies. In a thou­sand years, a mil­lion Galaxies. In ten thou­sand years, the en­tire known Universe. Then what?”

VJ-23X said, “As a side is­sue, there’s a prob­lem of trans­porta­tion. I won­der how many sun­power units it will take to move Galaxies of in­di­vid­u­als from one Galaxy to the next.”

“A very good point. Already, mankind con­sumes two sun­power units per year.”

“Most of it’s wasted. After all, our own Galaxy alone pours out a thou­sand sun­power units a year and we only use two of those.”

“Granted, but even with a hun­dred per cent ef­fi­ciency, we can only stave off the end. Our en­ergy re­quire­ments are go­ing up in geo­met­ric pro­gres­sion even faster than our pop­u­la­tion. We’ll run out of en­ergy even sooner than we run out of Galaxies. A good point. A very good point.”

“We’ll just have to build new stars out of in­ter­stel­lar gas.”

“There may be some way to re­verse en­tropy. We ought to ask the Galactic AC.”

VJ-23X was not re­ally se­ri­ous, but MQ-17J pulled out his AC-contact from his pocket and placed it on the table be­fore him.

“I’ve half a mind to,” he said. “It’s some­thing the hu­man race will have to face some­day.”

He stared somberly at his small AC-contact. It was only two inches cubed and noth­ing in it­self, but it was con­nected through hy­per­space with the great Galactic AC that served all mankind. Hyperspace con­sid­ered, it was an in­te­gral part of the Galactic AC.

MQ-17J paused to won­der if some­day in his im­mor­tal life he would get to see the Galactic AC. It was on a lit­tle world of its own, a spi­der web­bing of force-beams hold­ing the mat­ter within which surges of sub-mesons took the place of the old clumsy mol­e­c­u­lar valves. Yet de­spite its sub-etheric work­ings, the Galactic AC was known to be a full thou­sand feet across.

MQ-17J asked sud­denly of his AC-contact, “Can en­tropy ever be re­versed?”

VJ-23X looked star­tled and said at once, “Oh, say, I did­n’t re­ally mean to have you ask that.”

“We both know en­tropy can’t be re­versed. You can’t turn smoke and ash back into a tree.”

“Do you have trees on your world?” asked MQ-17J.

The sound of the Galactic AC star­tled them into si­lence. Its voice came thin and beau­ti­ful out of the small AC-contact on the desk. It said: THERE IS INSUFFICIENT DATA FOR A MEANINGFUL ANSWER.

The two men there­upon re­turned to the ques­tion of the re­port they were to make to the Galactic Council.

Zee Prime’s mind spanned the new Galaxy with a faint in­ter­est in the count­less twists of stars that pow­dered it. He had never seen this one be­fore. Would he ever see them all? So many of them, each with its load of hu­man­ity — but a load that was al­most a dead weight. More and more, the real essence of men was to be found out here, in space.

Minds, not bod­ies! The im­mor­tal bod­ies re­mained back on the plan­ets, in sus­pen­sion over the eons. Sometimes they roused for ma­te­r­ial ac­tiv­ity but that was grow­ing rarer. Few new in­di­vid­u­als were com­ing into ex­is­tence to join the in­cred­i­bly mighty throng, but what mat­ter? There was lit­tle room in the Universe for new in­di­vid­u­als.

Zee Prime was roused out of his reverie upon com­ing across the wispy ten­drils of an­other mind.

“I am Dee Sub Wun. Your Galaxy?”

“We call it only the Galaxy. And you?”

“We call ours the same. All men call their Galaxy their Galaxy and noth­ing more. Why not?”

“True. Since all Galaxies are the same.”

“Not all Galaxies. On one par­tic­u­lar Galaxy the race of man must have orig­i­nated. That makes it dif­fer­ent.”

AutoProber is the hard­ware hack­er’s fly­ing probe au­toma­tion stack for giv­ing your agent every­thing it needs to go from “there’s a new tar­get on the plate” to prob­ing in­di­vid­ual pins in a safe way.

Tell the agent to in­gest the pro­ject.

Tell the agent to con­firm that all parts are func­tion­ing.

Have it run hom­ing and then cal­i­bra­tion.

Tell the agent that there is a new tar­get on the plate.

It will find where the tar­get is on the plate, then take in­di­vid­ual frames,

keep­ing a record of the XYZ while not­ing pads, pins, chips, and other

in­ter­est­ing fea­tures.

It will stitch the frames to­gether and an­no­tate the map, in­clud­ing pins and

in­ter­est­ing com­po­nents it iden­ti­fied.

It will add probe tar­gets to the web dash­board for you to ap­prove or deny.

It will probe the ap­proved tar­gets and re­port back.

All hard­ware can be con­trolled through the web dash­board, Python scripts, or by the agent it­self.

This repo is a self-con­tained source-avail­able re­lease can­di­date. It con­tains the Python con­trol code, dash­board, CAD files, and doc­u­men­ta­tion needed to cre­ate your own AutoProber.

This pro­ject can move phys­i­cal hard­ware. Treat it as a ma­chine-con­trol sys­tem, not a nor­mal web app.

* GRBL Pn:P is ig­nored. The CNC probe pin is not a trusted end­stop.

* The in­de­pen­dent safety end­stop is read from os­cil­lo­scope Channel 4.

* Channel 4 must be con­tin­u­ously mon­i­tored dur­ing any mo­tion.

* The agent/​op­er­a­tor must stop and re­port. Recovery mo­tion is not au­to­matic.

* Optical end­stop wired to an ex­ter­nal 5V sup­ply and os­cil­lo­scope Channel 4

Default run­time as­sump­tions are doc­u­mented in the de­vice docs. Replace them with your own lab set­tings be­fore use.

These are the spe­cific parts or part classes used for the pro­to­type re­lease. Verify cur­rent list­ings, di­men­sions, volt­age, and con­nec­tor com­pat­i­bil­ity be­fore buy­ing.

uv sync

PYTHONPATH=. python3 apps/​dash­board.py

Start from con­fig/​au­to­prober.ex­am­ple.env. Do not pub­lish lab-spe­cific IPs, host­names, cre­den­tials, cal­i­bra­tion files, or cap­tured tar­get im­ages un­less you in­tend to re­lease them.

Do not com­mit lo­cal en­vi­ron­ment files that con­tain lab-spe­cific hosts, paths, or tar­get data.

Home and cal­i­brate only when the phys­i­cal setup is ready.

Execute any probe mo­tion only af­ter mi­cro­scope-to-probe off­set is mea­sured

and stored.

This pro­ject is source-avail­able un­der the PolyForm Noncommercial License 1.0.0.

You may use, mod­ify, and share this pro­ject for non­com­mer­cial pur­poses.

* The mi­cro­scope-to-pogo XY off­set must be mea­sured be­fore real prob­ing.

* Calibration must not be fab­ri­cated; the run­time cal­i­bra­tion file should be

gen­er­ated on the ma­chine that will move.

* The dash­board is a lab-con­trol tool and should not be ex­posed to un­trusted

net­works.

This pro­ject is in­tended for con­trolled lab work on equip­ment and tar­gets you are au­tho­rized to test. Do not use it to probe, dam­age, or an­a­lyze sys­tems with­out per­mis­sion.