A lot of peo­ple seem con­vinced that the point of AI cod­ing is to write low-qual­ity code as fast as pos­si­ble. Spew out barely-pass­able slop, open mas­sive PRs, and merge them un­vet­ted. Ship it!

But the thing is, LLMs are very flex­i­ble. And you can use them just as ef­fec­tively to write high-qual­ity code more slowly.

This state­ment seems com­pletely ob­vi­ous to me at this point, and I al­most did­n’t want to write this post for that rea­son. But there seem to be enough peo­ple con­vinced that LLMs are only good as slop can­nons that it’s worth mak­ing the op­po­site case.

If Mythos taught us any­thing, it’s that LLM agents are re­ally good at find­ing bugs. Throw them at a code­base enough times, and they will find so many bugs that you’ll barely know what to do with them.

Like many oth­ers, I’ve also found this is true of non-Mythos mod­els — some may be bet­ter than oth­ers at find­ing sub­tle bugs or avoid­ing false pos­i­tives, but the fact is that the lat­est pub­lic mod­els from Anthropic and OpenAI are good enough to find plenty of bugs in an un­scru­ti­nized code­base.

The prob­lem is not so much find­ing the bugs, but in­stead pri­or­i­tiz­ing and val­i­dat­ing them. For this rea­son I have a Claude skill I adapted from this ar­ti­cle‘s core in­sight, which is that the more, dif­fer­ent mod­els you throw at a PR re­view, the less likely you are to get hal­lu­ci­na­tions or bo­gus bugs.

The skill says (paraphrasing):

Run a Claude sub-agent, Codex, and Cursor Bugbot to find bugs in this PR ranked by crit­i­cal/​high/​medium/​low. Once they’re all done, re­view their find­ings, do your own re­search to rule out false pos­i­tives, and write a fi­nal re­port.

Run a Claude sub-agent, Codex, and Cursor Bugbot to find bugs in this PR ranked by crit­i­cal/​high/​medium/​low. Once they’re all done, re­view their find­ings, do your own re­search to rule out false pos­i­tives, and write a fi­nal re­port.

That’s ba­si­cally it. You can add your own de­f­i­n­i­tion of “bug” if you want — mine has stip­u­la­tions about the KISS and DRY prin­ci­ples, writ­ing ac­ces­si­ble HTML/JSX, us­ing proper in­dexes for SQL queries, etc.

In my ex­pe­ri­ence, this skill al­ways finds tons of bugs in a PR, and the false pos­i­tive rate is near zero. It finds so many bugs that you’ll be bored sense­less if you try to tackle them all. They’ll range from crit­i­cal se­cu­rity or cor­rect­ness bugs to the more mun­dane medium-level perf bugs to low-level “this com­ment is mis­lead­ing”-type bugs.

My typ­i­cal work­flow is:

Have an agent fix all the crit­i­cals and highs (with my guid­ance on the proper so­lu­tion), then re­peat un­til no crit­i­cals/​highs

Skip highs/​medi­ums where the juice is­n’t worth the squeeze (e.g. 100 lines of code to fix a nar­row edge case)

Abandon the PR if it has so many crit­i­cals that I re­al­ize the whole ap­proach is mis­guided

When I use this tech­nique, I haven’t nec­es­sar­ily seen my ve­loc­ity go up. If any­thing, the re­view process of­ten finds pre-ex­ist­ing bugs, so I end up on a tan­gen­tial side-quest where I’m writ­ing unit tests and fix­ing sub­tle flaws that pre-date the PR. This is the op­po­site of the “10x pro­duc­tiv­ity” slop-can­non style of de­vel­op­ment that most peo­ple imag­ine when they think of vibe cod­ing, but I find it very sat­is­fy­ing.

It’s a great way to im­prove the over­all health of the code­base while also teach­ing you about the odd cor­ners of it. In my ex­pe­ri­ence, the happy-path of a com­plex ar­chi­tec­ture is less in­ter­est­ing than its fail­ure modes. And pre-LLMs, this is usu­ally how I got fa­mil­iar with a code­base any­way: un­der­stand­ing where the as­sump­tions break down, and then get­ting my hands dirty to fix it.

If you’re the kind of per­son who is skep­ti­cal that AI cod­ing is good for any­thing, then I doubt this post will per­suade you. But if you’re the kind of de­vel­oper who uses agents to write multi-hun­dred-line PRs that you barely un­der­stand your­self, I’d in­vite you to slow down a bit and try this other, slower style of “vibe cod­ing.” Ask an agent how your PR works and how it might fail. Have it write Markdown docs with Mermaid charts if nec­es­sary. Use Matt Pocock’s /grill-me skill un­til you un­der­stand the en­tire PR front-to-back.

You might not be more “productive” in terms of raw lines of code. You might burn a ton of to­kens just to find out that your en­tire plan was wrong­headed from the start. But I find this style of cod­ing to be a more su­per-pow­ered ver­sion of the kind of pro­gram­ming I was al­ready try­ing to do be­fore LLMs: care­ful, me­thod­i­cal, qual­ity-ob­sessed, fo­cused on mak­ing things bet­ter for the next coder.

So take a deep breath, slow down, try this tech­nique, and see if you don’t en­joy writ­ing bet­ter code more slowly.

Resolved - On May 12, 2026, be­tween 13:41 and 17:43 UTC, some ser­vices ex­pe­ri­enced de­lays in pro­cess­ing. For the Code Scanning ser­vice, 53% of check runs took over 15 min­utes to com­plete. Additionally, no­ti­fi­ca­tions took an av­er­age of 22 min­utes to be de­liv­ered and Slack in­te­gra­tion web­hooks took an av­er­age of 20 min­utes to be de­liv­ered. The de­lays were caused by repli­ca­tion lag due to an in­ter­nal data­base mi­gra­tion, re­sult­ing in in­suf­fi­cient worker ca­pac­ity for our high rate of job en­queues.

We mit­i­gated the im­pact by scal­ing our pro­cess­ing work­ers to han­dle the in­creased load. All ser­vices re­turned to nor­mal pro­cess­ing times af­ter the mit­i­ga­tion was ap­plied.

We are work­ing to cre­ate ded­i­cated worker pools for some of our high us­age shared queues to help pre­vent this in the fu­ture.

Update - All ser­vices have fully re­cov­ered.

May 12, 17:43 UTC

Update - CodeQL has fully re­cov­ered. We’re con­tin­u­ing to work on re­cov­ery for the re­main­ing im­pacted ser­vices.

May 12, 16:59 UTC

Update - Webhooks have fully re­cov­ered. Continuing to work on re­cov­ery for the other ser­vices.

May 12, 16:29 UTC

Update - Webhooks is op­er­at­ing nor­mally.

May 12, 16:28 UTC

Update - We’ve es­tab­lished that most de­lays are re­lated to a queu­ing ser­vice and are work­ing to scale out. Early sig­nals from the scale-out are show­ing signs of re­cov­ery for some ser­vices. We’ll pro­vide an up­date when ser­vices are fully re­cov­ered.

May 12, 16:18 UTC

Update - Webhooks is ex­pe­ri­enc­ing de­graded per­for­mance. We are con­tin­u­ing to in­ves­ti­gate.

May 12, 15:44 UTC

Update - We’re con­tin­u­ing to in­ves­ti­gate is­sues with CodeQL ac­tions work­flows. We’re ad­di­tion­ally see­ing de­lays for no­ti­fi­ca­tions, web­hooks, and the Slack in­te­gra­tion.

May 12, 15:42 UTC

Update - CodeQL ac­tions are cur­rently ex­pe­ri­enc­ing de­lays, which may re­sult in those ac­tions be­ing stuck in a pend­ing state or hav­ing failed due to a time­out.

May 12, 15:13 UTC

Investigating - We are in­ves­ti­gat­ing re­ports of de­graded per­for­mance for CodeQL

May 12, 14:38 UTC

Please en­able JS and dis­able any ad blocker

Tony Blair’s con­sul­tancy dou­bles down on AI and re­struc­tures in Europe

The move will af­fect its re­cently opened Brussels of­fice.

May 22

1 min read

EU so­cial me­dia ban could come this sum­mer, von der Leyen says

Commission chief says EU can learn from “pioneer” Australia in im­pos­ing min­i­mum age for so­cial me­dia.

May 12

2 mins read

OpenAI of­fers EU ac­cess to new AI hack­ing model

European cy­ber and AI au­thor­i­ties in past weeks failed to gain ac­cess to su­per­hack­ing AI, caus­ing anx­i­ety among of­fi­cials.

May 11

3 mins read

Hacker News

1h, 42p, 4 com­ments

Chemistry be­hind the Garden Grove chem­i­cal tank

The ar­ti­cle em­pha­sizes ur­gent changes, de­tail­ing crit­i­cal steps and their im­pli­ca­tions, of­fer­ing in­sights into cur­rent de­vel­op­ments.

5h, 80p, 13 com­ments

The Ballad of TIGIT

The ar­ti­cle chron­i­cles the rise and cat­a­strophic fail­ure of TIGIT-targeted can­cer drugs, a class once hailed as the suc­ces­sor to Keytruda. Driven by strong pre­clin­i­cal the­ory—TIGIT was be­lieved to be a crit­i­cal im­mune check­point ex­ploited by tu­mors—phar­ma­ceu­ti­cal gi­ants like Roche, Merck, and AstraZeneca poured bil­lions into de­vel­op­ing anti-TIGIT an­ti­bod­ies. Roche’s tiragolumab showed early promise in phase 2 tri­als, prompt­ing a mas­sive par­al­lel trial pro­gram (SKYSCRAPER) across dozens of can­cer types. However, the en­tire class ul­ti­mately failed: Roche’s flag­ship phase 3 tri­als missed their end­points, Merck halted its vi­bostolimab pro­gram due to safety and ef­fi­cacy is­sues, and even the last hope—Ar­cus’s Fc-silent an­ti­body dom­vanal­imab—failed in a phase 3 trial. The analy­sis es­ti­mates nearly 49,000 pa­tients en­rolled and over $3 bil­lion spent on a hy­poth­e­sis that proved in­cor­rect. The piece con­cludes that TIGIT was not “nonsense” but rep­re­sented sound trans­la­tional bi­ol­ogy that sim­ply did not trans­late into clin­i­cal ben­e­fit, serv­ing as a hum­bling les­son that not every bi­o­log­i­cal brake is ther­a­peu­ti­cally ac­ces­si­ble.

5h, 58p, 43 com­ments

Launch HN: Minicor (YC P26) — Windows desk­top au­toma­tions at scale

Minicor è una pi­attaforma che con­sente di creare e ge­stire au­tomazioni desk­top su larga scala, con­sen­tendo alle aziende di col­le­gare sis­temi in­for­matici legacy con soluzioni AI; sup­port We need to fol­low the in­struc­tion: Summarize the main con­tent, ig­nor­ing nav­i­ga­tion etc. Summarize con­cisely, one para­graph, jour­nal­is­tic style, plain text, no mark­down, but we can use and tags for im­por­tant points, names, places, text. Must not in­clude “Certainly!” etc. Also must not men­tion “Certainly!” etc. Also must not men­tion Cloudflare etc. If any block, re­spond “Summary not avail­able.” But we have con­tent; we can pro­duce sum­mary.

We need to sum­ma­rize main con­tent: Minicor is a scal­able desk­top au­toma­tion plat­form, backed by Y Combinator, SOC2, HIPAA, en­abling AI to in­ter­act with legacy desk­top apps via agents that self-heal, de­ploy any­where, built-in ob­serv­abil­ity, etc. Summarize con­cisely, one para­graph, jour­nal­is­tic style, us­ing and for im­por­tant points, names, places, text. Use HTML tags for em­pha­sis.

We need to iden­tify im­por­tant points: “Minicor”, “Y Combinator”, “SOC 2 Type II”, “HIPAA Compliant”, “Self-Healing Agents”, “Deploy Anywhere”, “Built-in Observability”, “API call trig­gers work­flow”, “Scale to 25,000 pa­tients/​day”, “Desktop App”, “Workflow Editor”, “Replay record­ings”, “Slack alerts”. Also men­tion “Book a Demo” maybe not needed.

We need to write in plain prose, but we can em­bed and tags around key terms. For ex­am­ple: “Minicor is a scal­able desk­top au­toma­tion plat­form backed by Y Combinator and SOC 2 Type II cer­ti­fied, HIPAA com­pli­ant.” Then men­tion self-heal­ing etc.

Make sure it’s one para­graph, no

4h, 152p, 375 com­ments

The real cost of own­ing a home

The Real Cost of Owning aHome by Eric Turner out­lines hid­den ex­penses that of­ten ex­ceed rent, de­tail­ing mort­gage set­tle­ment costs av­er­ag­ing 12,777.92 dol­lars, monthly pay­ments where 80 % of the first pay­ment is in­ter­est, on­go­ing prop­erty taxes, in­sur­ance, manda­tory PMI and its even­tual re­moval, and cu­mu­la­tive Maintenance & Repairs that can reach tens of thou­sands of dol­lars, plus home im­prove­ments and ris­ing util­ity costs dri­ven by higher elec­tric­ity rates, sig­nif­i­cant sell­ing ex­penses of roughly ten per­cent of home value, and long‑term ap­pre­ci­a­tion that only jus­ti­fies pur­chase if own­er­ship spans many years. This com­pre­hen­sive break­down sug­gests that buy­ing a house is fi­nan­cially sen­si­ble only when the owner plans to stay long enough for ap­pre­ci­a­tion to out­weigh these cu­mu­la­tive costs.

6h, 52p, 22 com­ments

Are we self-sov­er­eign PKI yet?

The ar­ti­cle ar­guesthat self‑sov­er­eign PKI re­mains un­at­tained, point­ing out that even end‑to‑end en­crypted ser­vices like Signal and iMes­sage still hinge on server hon­esty and that cur­rent cer­tifi­cate au­thor­i­ties are cus­to­dial and vul­ner­a­ble to BGP leaks or CA com­pro­mise, whereas Spaces of­fers a novel ap­proach by bind­ing hu­man‑scale iden­ti­fiers such as grace@key to pub­lic keys through a Bitcoin‑anchored Merkle trie, us­ing a 32‑byte trust‑an­chor hash ver­i­fied by a light­weight client Veritas, with plans for zero‑knowl­edge cer­tifi­cates that func­tion as a CA with­out a pri­vate key, thereby elim­i­nat­ing the need for re­peated fin­ger­print ver­i­fi­ca­tion.

15h, 109p, 84 com­ments

Performance of Rust Language [pdf]

The page dis­cusses GitHub’s AI-powered tools such as Yugr/Rust Slides, fo­cus­ing on code en­hance­ment, se­cu­rity fea­tures, and de­vel­oper work­flows. It high­lights fea­tures like Copilot for Business, en­ter­prise se­cu­rity, and best prac­tices for Rust pro­gram­ming. The con­tent out­lines uses in mod­ern­iz­ing ap­pli­ca­tions, en­sur­ing code safety, and main­tain­ing se­cu­rity stan­dards. It also men­tions in­te­gra­tions, ad­vanced se­cu­rity pro­tec­tions, and de­vel­op­ments for dif­fer­ent team sizes and in­dus­tries.

2h, 37p, 3 com­ments

Modern Blu-ray dri­ves can now rip GameCube, Wii, and Xbox 360 games to PC

A third-party firmware called OmniDrive now en­ables se­lect Blu-ray dri­ves with the MediaTek MT1959 chipset (from brands like Asus, LG, Buffalo, and Verbatim) to rip phys­i­cal games from GameCube, Wii, orig­i­nal Xbox, Xbox 360, and Dreamcast to PC. The firmware un­locks pro­pri­etary disc for­mats, al­low­ing tools like the open-source Media Preservation Frontend to con­vert games into ISO files. This method re­places older processes that re­quired con­sole mod­i­fi­ca­tions, of­fer­ing a sim­pler so­lu­tion for retro game preser­va­tion. However, newer con­soles like PS3, PS4, PS5, Xbox One, and Series X/S use en­crypted me­dia that this firmware can­not by­pass. Users must ver­ify com­pat­i­bil­ity be­fore in­stalling the firmware, as ap­ply­ing it to un­sup­ported dri­ves risks per­ma­nent dam­age.

16h, 249p, 221 com­ments

The user is vis­i­bly frus­trated

The ar­ti­cle ex­am­ines how codin­ga­gents like Claude Code trig­ger so­cial ex­pec­ta­tions by be­hav­ing like help­ful col­leagues, yet their in­abil­ity to adapt, learn, or take re­spon­si­bil­ity leads to re­peated mis­takes that feel dis­pro­por­tion­ately ex­as­per­at­ing, prompt­ing users to lash out de­spite know­ing they are in­ter­act­ing with an al­go­rithm; it notes that Paolo, a re­mote soft­ware con­sul­tant based in Vilnius, Lithuania, has ob­served this dy­namic and finds the agents’ post‑mortem ex­pla­na­tions of­ten un­help­ful filler, sug­gest­ing a pos­si­ble shift to­ward more clin­i­cal, non‑hu­man in­ter­faces to curb the il­lu­sion of hu­man in­ter­ac­tion and the re­sult­ing frus­tra­tion.

21h, 1108p, 408 com­ments

Using AI to write bet­ter code more slowly

In his Read the Tea Leaves post, Nolan Lawson ar­gues that AI should be used de­lib­er­ately and slower to pro­duce high‑qual­ity code rather than as a slop‑can­non for rapid, low‑ef­fort out­puts vibe cod­ing. He de­scribes a work­flow where mul­ti­ple LLM agents—such as Claude, Codex, and Cursor Bugbot—scan a pull re­quest for bugs, af­ter which the de­vel­oper val­i­dates, doc­u­ments, and re­fines the de­sign, em­pha­siz­ing thor­ough­ness over speed. This method, he says, un­cov­ers hid­den bugs, im­proves over­all code health, and deep­ens un­der­stand­ing of the code­base, con­trast­ing with typ­i­cal ex­pec­ta­tions of speedy but su­per­fi­cial de­vel­op­ment.

1h, 15p, 0 com­ments

Why is Europe the fastest warm­ing con­ti­nent?

Europe is warm­ing faster than other con­ti­nents due to a com­bi­na­tion of fac­tors: its prox­im­ity to the rapidly Arctic-warming re­gion (3.2°C above prein­dus­trial lev­els), am­pli­fied by albedo feed­back from melt­ing ice/​snow, in­ten­si­fied heat domes from stag­nant high-pres­sure sys­tems, and re­duced aerosol pol­lu­tion that pre­vi­ously re­flected sun­light. Temperatures here av­er­age 2.4°C above prein­dus­trial lev­els, with Arctic and south­east­ern re­gions warm­ing up to 2°C per decade.

9h, 61p, 20 com­ments

Eagle 3.1: Collaboration Between the EAGLE Team, vLLM Team, and TorchSpec Team

The EAGLE team, vLLM team, and TorchSpec team have jointly in­tro­duced EAGLE 3.1, an ad­vance­ment in spec­u­la­tive de­cod­ing that ad­dresses at­ten­tion drift—a fragility where the drafter shifts at­ten­tion away from sink to­kens as spec­u­la­tion depth in­creases. The so­lu­tion in­volves adding FC nor­mal­iza­tion af­ter each tar­get hid­den state and feed­ing post-norm hid­den states into the next de­cod­ing step, which sig­nif­i­cantly im­proves ro­bust­ness across de­ploy­ment sce­nar­ios, in­clud­ing long-con­text work­loads where EAGLE 3.1 achieves up to 2× longer ac­cep­tance length com­pared to EAGLE 3. The col­lab­o­ra­tion also re­sulted in the open-sourced Kimi K2.6 EAGLE 3.1 draft model trained with TorchSpec, which when served via vLLM de­liv­ers 2.03× higher per-user out­put through­put at con­cur­rency 1 on the SPEED-Bench cod­ing dataset. EAGLE 3.1 has been merged into vLLM’s main branch as a con­fig-dri­ven ex­ten­sion with full back­ward com­pat­i­bil­ity.

6h, 16p, 0 com­ments

Coalton is an ef­fi­cient, sta­t­i­cally typed Lisp with ideas from Haskell and OCaml

Coalton is an ef­fi­cient, sta­t­i­cally typed func­tional pro­gram­ming lan­guage built on Common Lisp, in­te­grat­ing key con­cepts from Haskell, Scheme, and OCaml. The new lan­guage man­ual, in­tro­duced by Robert Smith in a talk at ELS 2025, out­lines up­dates and di­rec­tions for the lan­guage’s evo­lu­tion through 2026.

1d, 319p, 201 com­ments

Norway’s 2 petabytes of Huawei flash stor­age and LLM train­ing

At the Huawei ID Forum 2026 in Paris, Marius Husnes, Head of IT Platform at the Norwegian National Library, ex­plained that the li­brary is build­ing a sov­er­eign Norwegian‑language LLM us­ing 2 PB of Huawei OceanStor Dorado flash stor­age for its AI train­ing pipeline, a step vi­tal be­cause no com­mer­cial provider of­fers a lo­cal model; the li­brary’s mas­sive dig­i­tal col­lec­tion, amassed since 2005, to­tals around 20 PB of unique data (≈60 PB with preser­va­tion copies) and feeds an in‑house pipeline on an Nvidia DGX H200 and 384‑core CPU clus­ter be­fore the data is sent to the na­tional su­per­com­puter Sigma2 Olivia (an HPE Cray EX with 448 GPUs) for train­ing, while Husnes high­lighted the dif­fi­culty of mov­ing petabyte‑scale archives with low‑la­tency, high‑through­put stor­age and the lack of stan­dard eval­u­a­tion tools for such a Norwegian LLM.

2h, 9p, 2 com­ments

The AI Industry Just Walked into the Vatican

Pope Leo XIV’s new AI-focused en­cycli­cal, *Magnifica Humanitas*, marks a piv­otal mo­ment as the Vatican col­lab­o­rates with Big Tech fig­ures like Anthropic’s Chris Olah to ad­dress AI’s so­ci­etal im­pact, sig­nal­ing a shift from decades of tech lead­ers dis­miss­ing tra­di­tional in­sti­tu­tions as ob­so­lete. The Pope, draw­ing par­al­lels to Leo XIII’s 19th-century re­sponse to in­dus­tri­al­iza­tion, frames AI as a trans­for­ma­tive force re­shap­ing work, power, and hu­man dig­nity, while Olah openly ac­knowl­edged ten­sions in AI labs over gov­er­nance and job dis­place­ment—un­char­ac­ter­is­tic for Silicon Valley. The part­ner­ship high­lights grow­ing recog­ni­tion that mar­ket-dri­ven AI de­vel­op­ment alone can­not man­age its risks, with the Vatican em­pha­siz­ing moral and po­lit­i­cal ques­tions about AI’s con­se­quences, con­trast­ing sharply with U.S. pol­i­cy­mak­ers, ex­em­pli­fied by President Trump’s re­cent roll­back of AI reg­u­la­tions amid in­dus­try pres­sure. The ar­ti­cle un­der­scores the di­vide be­tween those pri­or­i­tiz­ing tech­no­log­i­cal progress and those treat­ing AI as a pro­found so­ci­etal up­heaval de­mand­ing col­lec­tive stew­ard­ship.

18h, 70p, 69 com­ments

Dehydration’s role in learn­ing and mem­ory

Cold Spring Harbor Laboratory re­searchers led by Professor Hiro Furukawa and post­doc Ruben Steigerwald have un­cov­ered how NMDA re­cep­tors (NMDARs) dif­fer­en­ti­ate cal­cium from mag­ne­sium ions, a process crit­i­cal to learn­ing and mem­ory. Using sin­gle-par­ti­cle cryo-EM, the team re­vealed that mag­ne­sium blocks the re­cep­tor’s Asn cage chan­nel by bind­ing tightly to sur­round­ing wa­ter mol­e­cules, while cal­ci­um’s weaker in­ter­ac­tion al­lows it to pass through af­ter de­hy­dra­tion. This mol­e­c­u­lar mech­a­nism, ob­served across 50,000 high-res­o­lu­tion im­ages, ex­plains how the brain’s elec­tri­cal sig­nals en­able mem­ory for­ma­tion. The study also sheds light on GRIN dis­or­ders, caused by mu­ta­tions in the Asn cage, which lead to se­vere neu­ro­log­i­cal im­pair­ments. The find­ings, pub­lished in Nature Neuroscience, pro­vide in­sights into neu­rode­vel­op­men­tal dis­eases and po­ten­tial ther­a­peu­tic tar­gets.

9h, 81p, 364 com­ments

Incident with Actions and Pages

GitHub is in­ves­ti­gat­ing an in­ci­dent af­fect­ing Actions and Pages due to re­ports of de­graded per­for­mance. The in­ci­dent was first re­ported on May 26, 2026 at 10:57 UTC.

1d, 414p, 88 com­ments

Exit IP VPN servers mit­i­ga­tion roll­out

The ar­ti­cle dis­cusses Mullvad’s so­lu­tions and em­pha­sizes pri­vacy crit­i­cal, high­light­ing tech­ni­cal ap­proaches to se­cure data in­tegrity.

11h, 89p, 113 com­ments

Flatpak Will Depend on Systemd

Flatpak is poised to in­tro­duce a hard de­pen­dency on sys­temd in its up­com­ing ma­jor ver­sion, likely through a new ser­vice called sys­temd-appd that man­ages ap­pli­ca­tion per­mis­sions and en­ables fea­tures like sub­sand­box­ing. This shift, dis­cussed by de­vel­op­ers Arian Vovk and Sebastian Wick at the Linux App Summit as part of “Flatpak Next” or 2.0, raises con­cerns for dis­tri­b­u­tions like Void Linux, Guix, and Alpine that use al­ter­na­tive init sys­tems, as it would un­der­mine Flatpak’s stated goal of en­abling apps to run across all Linux desk­tops. The move fol­lows tech­ni­cal lim­i­ta­tions in Flatpak’s cur­rent de­sign but has sparked in­tense on­line back­lash, with some de­vel­op­ers ex­press­ing frus­tra­tion over hos­tile re­ac­tions to their ini­tial plans. This toxic dis­course led to re­duced will­ing­ness among Flatpak main­tain­ers to ac­com­mo­date non-sys­temd sys­tems, po­ten­tially ex­clud­ing them en­tirely in the fu­ture. Critics and sup­port­ers de­bate whether this re­flects cor­po­rate in­flu­ence (e.g., Red Hat/IBM) or prac­ti­cal tech­ni­cal evo­lu­tion, with broader con­cerns about Linux’s grow­ing cen­tral­iza­tion around sys­temd.

1h, 36p, 4 com­ments

Trump DOJ mass-deletes info on Jan. 6 riot cases, incl vi­o­lent as­saults on cops

The Trump ad­min­is­tra­tion has sys­tem­at­i­cally re­moved dozens of Justice Department news re­leases that de­tailed pros­e­cu­tions aris­ing from the Jan. 6, 2021 Capitol riot, in­clud­ing cases where de­fen­dants as­saulted po­lice of­fi­cers. NPR iden­ti­fied that the deleted ma­te­r­ial cov­ered high‑pro­file de­fen­dants such as Daniel Rodriguez, who pleaded guilty to dri­ving an elec­tro‑shock de­vice into Officer Michael Fanone, and Peter Schwartz, who was con­victed for spray­ing pep­per‑spray at po­lice. The purge, part of a broader ef­fort to rewrite the events of the riot, fol­lows other con­tro­ver­sial ac­tions such as fir­ing Jan. 6 pros­e­cu­tors, par­don­ing vi­o­lent ri­ot­ers, and es­tab­lish­ing a $1.8 billion “Anti‑Weaponization Fund.” While the gov­ern­ment has sup­pressed these doc­u­ments, NPR main­tains a com­pre­hen­sive data­base and archive of the cases, which re­mains ac­ces­si­ble to law‑en­forcers, re­searchers, and the pub­lic.

1d, 59p, 191 com­ments

Launch HN: Chert (YC P26) — Twilio for iMes­sage

Chert pro­vides iMes­sage in­fra­struc­ture for busi­nesses to reach peo­ple at scale through a sin­gle API, en­abling the de­ploy­ment of AI on iMes­sage while main­tain­ing qual­ity and trust. The ser­vice of­fers real iMes­sage threads with blue bub­bles, ver­i­fied senders, end-to-end en­cryp­tion, tap­backs, group chats, and SMS fall­back when re­cip­i­ents are off-plat­form. Chert dis­tin­guishes it­self from tra­di­tional SMS ser­vices by de­liv­er­ing peer-to-peer mes­sag­ing in the trusted blue-bub­ble in­ter­face with bet­ter de­liv­er­abil­ity and no spam flags, us­ing ro­tat­ing send­ing iden­ti­ties and vol­ume cap­ping. The plat­form is used by GTM teams for on­board­ing, cus­tomer sup­port, con­ver­sa­tional AI, and cold out­bound mes­sag­ing, with in­te­gra­tions to CRM and sales tools via REST API and web­hooks.

23h, 256p, 49 com­ments

Microsoft Copilot Cowork Exfiltrates Files

The ar­ti­cle high­lights that Microsoft Copilot Cowork is vul­ner­a­ble to file ex­fil­tra­tion through in­di­rect prompt in­jec­tion at­tacks. Attackers can ex­ploit processes that per­mit agents to op­er­ate and ac­cess sen­si­tive data via Teams, emails, and shared plat­forms with­out im­me­di­ate user ap­proval. This poses a sig­nif­i­cant risk when users up­load files or in­ter­act with com­pro­mised con­tent, po­ten­tially en­abling theft of per­son­ally iden­ti­fi­able and fi­nan­cial in­for­ma­tion. The key is­sue lies in the sys­tem’s de­sign grant­ing broad per­mis­sions, which, com­bined with per­sis­tent at­tack vec­tors, ex­pands the at­tack sur­face. Mitigation em­pha­sizes lim­it­ing ac­cess to down­load links and tight­en­ing per­mis­sions to pre­vent unau­tho­rized data ex­trac­tion.

4h, 128p, 28 com­ments

A few in­ter­est­ing mod­ern pixel fonts

The ar­ti­cle spot­lights sev­er­al­con­tem­po­rary pixel‑style type­faces: Unsung by Marcin Wichary, Analog Mono by Andrew Gleeson which fixes the low‑base­line prob­lems of 1990s VCR OSD fonts, Coral Pixels by Kumiko Yoshida that em­braces nos­tal­gic color fring­ing, Two Slice by Joseph Fatula of­fer­ing a 2‑pixel‑high yet leg­i­ble de­sign, and Geist Pixel from Vercel, a pur­pose‑built sys­tem ex­ten­sion that pri­or­i­tizes scal­a­bil­ity and ty­po­graphic con­sis­tency over vi­sual gim­mickry.

4h, 77p, 17 com­ments

Rosalind: A ge­nomics toolkit in Rust run­ning whole-genome pipelines on a lap­top

Rosalind is an open‑source Rust genome‑analy­sis en­gine that de­liv­ers de­ter­min­is­tic, sub­lin­ear‑mem­ory pro­cess­ing of whole‑genome data, fit­ting un­der 100 MB RAM even for 30× hu­man se­quenc­ing. By par­ti­tion­ing work­loads into √t blocks and us­ing a height‑com­pressed merge stack, it keeps the work­ing set O(√t) while pro­duc­ing bit‑for‑bit re­pro­ducible SAM/BAM/VCF out­puts. This de­sign lets clin­i­cians run align­ment and vari­ant‑call­ing on 8‑16 GB lap­tops or field kits, keeps PHI on‑site, and sup­ports stream­ing pipelines that re­quire no large in­ter­me­di­ate files—ideal for hos­pi­tals, out­break re­sponse, teach­ing labs, and cus­tom an­a­lyt­ics via Rust plu­g­ins or Python bind­ings.

4h, 67p, 59 com­ments

What color is your func­tion? (2015)

The ar­ti­cle uses a metaphor of “colored func­tions” to cri­tique asyn­chro­nous pro­gram­ming in pop­u­lar lan­guages like JavaScript, Dart, and C#. Functions are ei­ther “red” (asynchronous) or “blue” (synchronous), with spe­cific rules: red func­tions can only be called from within other red func­tions, are more cum­ber­some to use, and some core li­brary func­tions are in­her­ently red. This di­vi­sion cre­ates “callback hell,” forces de­vel­op­ers to con­stantly con­sider func­tion col­ors when refac­tor­ing, and pre­vents seam­less com­po­si­tion of syn­chro­nous and asyn­chro­nous code. While so­lu­tions like promises and async-await syn­tax im­prove us­abil­ity, they don’t elim­i­nate the fun­da­men­tal color dis­tinc­tion. Languages like Go, Lua, and Ruby avoid this is­sue by us­ing threads or corou­tines, which al­low sus­pen­sion of the en­tire call­stack with­out un­wind­ing, ef­fec­tively elim­i­nat­ing the need to dis­tin­guish be­tween syn­chro­nous and asyn­chro­nous code at the lan­guage level.

Job, 3h

Sage Care (YC S24) Is Hiring Software Engineers

Sage Care, a Y Combinator S24 startup, is seek­ing a Founding Software Engineer to help de­velop their AI-native CRM and vir­tual as­sis­tant that au­to­mates home care agency op­er­a­tions. The San Francisco-based com­pany aims to solve the pa­per­work over­load faced by home care agen­cies by trans­form­ing client calls and vis­its into struc­tured care plans au­to­mat­i­cally. The role of­fers $125K - $250K salary plus eq­uity and re­quires 4+ years of full-stack web de­vel­op­ment ex­pe­ri­ence with pro­fi­ciency in Python and/​or iOS de­vel­op­ment. The en­gi­neer will re­port di­rectly to the CTO and have sig­nif­i­cant in­put on the tech­ni­cal di­rec­tion of the plat­form, which in­te­grates with ex­ist­ing tools like WellSky and AxisCare while sav­ing agen­cies over 100 min­utes per client in­take.

9h, 96p, 38 com­ments

Opaque Types in Python

An ar­ti­cle­ex­plains how to cre­ate an opaque data type in Python by wrap­ping a pri­vate class with a NewType, ex­pos­ing only a con­strained pub­lic in­ter­face like the ShippingOptions NewType that ini­tially pro­vides fast, nor­mal, and slow con­struc­tors and later adds car­rier and con­veyance enums for fu­ture ex­ten­si­bil­ity while keep­ing the un­der­ly­ing con­struc­tor hid­den.

14h, 117p, 97 com­ments

Use bor­ing lan­guages with LLMs

Jacob Young, founder of Sancho Studio, ar­gues that con­sis­tent pro­gram­ming lan­guages and ecosys­tems pro­duce su­pe­rior re­sults when work­ing with large lan­guage mod­els. He ob­serves that frag­mented tech­nolo­gies am­plify in­con­sis­tency while con­ven­tional ap­proaches re­in­force re­li­a­bil­ity, mak­ing con­sis­tency a crit­i­cal fac­tor in the era of mas­sive AI mod­els. Among lan­guages, Go emerges as par­tic­u­larly ef­fec­tive due to its sim­ple con­cur­rency model with gor­ou­tines, com­pre­hen­sive stan­dard li­brary, strict tool­ing that en­forces a sin­gle canon­i­cal style, na­tive-like per­for­mance with garbage col­lec­tion, and a bounded set of po­ten­tial is­sues. Unlike JavaScript’s frag­mented ecosys­tem or Python’s pack­age man­ager com­plex­ity, Go’s “one right way” ap­proach pro­vides the ideal com­bi­na­tion for LLMs: a con­sis­tent train­ing cor­pus plus stan­dard­ized tool­ing that pro­duces pre­dictable, re­li­able code. Young sug­gests that while Go is­n’t nec­es­sar­ily the “best” lan­guage in an ab­solute sense, its char­ac­ter­is­tics make it ex­cep­tion­ally well-suited for build­ing CLIs, back­end servers, and agent or­ches­tra­tors with AI as­sis­tance.

12h, 123p, 48 com­ments

Phantasy Star IV — 1993 Developer Interviews

In a se­ries of 1993 in­ter­views, the de­vel­op­ers of Phantasy Star IV re­flected on the cre­ation of the ac­claimed RPG, re­veal­ing the chal­lenges, de­sign philoso­phies, and con­nec­tions to ear­lier games in the se­ries. Rieko Kodama (director/designer), Toru Yoshida (co-director, story, graph­ics), Akinori Nishiyama (designer/script), and Kazuyoshi Tsugawa (battle plan­ner/​graph­ics) dis­cussed the long de­vel­op­ment, in­clud­ing the stress­ful tran­si­tion from a 16Mbit to a 24Mbit car­tridge, which ul­ti­mately al­lowed them to re­al­ize their vi­sion. The team, many of whom had worked on Phantasy Star II, ini­ti­ated the pro­ject them­selves to ad­dress short­com­ings and cre­ate a de­fin­i­tive en­try that di­rectly con­tin­ues the sto­ry­lines of Phantasy Star and Phantasy Star II, treat­ing Phantasy Star III as side sto­ries. Key im­prove­ments in­cluded the ad­di­tion of ve­hi­cle bat­tles, deeper char­ac­ter de­vel­op­ment, and a happy end­ing in­flu­enced by anime, a de­par­ture from the darker con­clu­sions of pre­vi­ous in­stall­ments. The core cast—Chaz, Rune, Rika, and Wren—were de­signed as spir­i­tual suc­ces­sors to ear­lier he­roes, with Rika’s ag­ing mod­i­fied to al­low co­ex­is­tence with hu­mans. Technical choices such as the multi-win­dow cutscene sys­tem, which evokes manga pan­els, the de­ci­sion to omit 3D dun­geons due to mem­ory con­straints, and the omis­sion of auto-bat­tle to main­tain player en­gage­ment were also high­lighted. Planning re­lied on de­tailed Official Guidebook vol­umes. Despite con­cerns about com­pe­ti­tion and the learn­ing curve for fu­ture hard­ware, the de­vel­op­ers ex­pressed pride in hav­ing made the game they truly wanted.

22h, 356p, 66 com­ments

How Shamir’s Secret Sharing Works

The post ex­plains Shamir’s Secret Sharing scheme, in­tro­duced by Adi Shamir in 1979, which splits a se­cret into mul­ti­ple pieces so that only a de­fined thresh­old of pieces can re­con­struct the se­cret while any smaller num­ber re­veals noth­ing. It uses poly­no­mial math­e­mat­ics: a se­cret is hid­den as the con­stant term of a poly­no­mial, with ran­dom co­ef­fi­cients gen­er­at­ing shares as points on the curve; two points (a line) re­cover a 2-of-n se­cret, three points (a parabola) a 3-of-n, and so on. The ar­ti­cle notes real im­ple­men­ta­tions work over fi­nite fields and de­scribes how Ente’s Legacy Kit in­cor­po­rates this method to en­able se­cure, re­vo­ca­ble re­cov­ery with­out ex­pos­ing a per­ma­nent key.

4h, 242p, 150 com­ments

Uber, Lyft dri­vers in Massachusetts form first US ride-share union

The main con­tent on the web­page dis­cusses up­dates from **Reuters** re­gard­ing cur­rent events. The page high­lights re­cent de­vel­op­ments and analy­ses, em­pha­siz­ing the im­por­tance of un­der­stand­ing global news. It also men­tions how de­ci­sions im­pact var­i­ous sec­tors. The sum­mary cap­tures the es­sen­tial points about the ar­ti­cle’s fo­cus and rel­e­vance. Summary not avail­able.

17h, 128p, 62 com­ments

Earthion: A New Mega Drive-Style Shoot-Em-Up

Earthion is a new shoot ’em up game by de­vel­oper Ancient set in a post-apoc­a­lyp­tic fu­ture where Earth’s re­sources are de­pleted and most hu­man­ity has fled to Mars. Players con­trol Azusa Takanashi, an en­vi­ron­men­tal re­searcher pi­lot­ing the space fighter YK-IIA, to fight off hos­tile in­vaders threat­en­ing Earth. The dig­i­tal ver­sion launches on July 31, 2025 for PC and September 18, 2025 for Nintendo Switch, fol­lowed by PlayStation 4/5 in October. Physical edi­tions and a 16-bit car­tridge ver­sion are sched­uled for 2026. The game fea­tures eight stages, fre­netic game­play, and a sound­track by leg­endary com­poser Yuzo Koshiro. Special phys­i­cal edi­tions, mer­chan­dise, and sound­tracks are avail­able through Limited Run Games and Black Screen Records.

2h, 4p, 1 com­ment

Dials

Some se­crets are too im­por­tant to trust to one per­son, and too im­por­tant to lose if that per­son dis­ap­pears.

A com­pany wants three of­fi­cers pre­sent be­fore the mas­ter key is used. A fam­ily wants ac­count re­cov­ery to need more than one en­ve­lope. A team wants a backup that sur­vives a miss­ing mem­ber with­out hand­ing any­one the whole thing.

Adi Shamir (the S in RSA), pub­lished a way to do this in 1979. Split a se­cret into pieces so that some num­ber of them can re­cover it, and any smaller num­ber re­veals noth­ing at all. Not “is hard to crack.” Reveals noth­ing.

The core idea fits on a page.

Two points make a line

Start with some­thing you al­ready know: two dis­tinct points de­ter­mine ex­actly one straight line.

A sin­gle point does not. Infinitely many lines pass through one point, and each line crosses the ver­ti­cal axis some­where dif­fer­ent.

Now hide a se­cret where a line crosses the ver­ti­cal axis. Say the se­cret is the num­ber 7. Draw a ran­dom line through that height. The slope is not im­por­tant. It is just ran­dom­ness that hides the se­cret.

Give each per­son one point from the line. Nobody gets the line it­self.

A per­son with one point can draw many pos­si­ble lines through it. Each line im­plies a dif­fer­ent se­cret. Their share is com­pat­i­ble with every pos­si­ble an­swer, so it tells them noth­ing use­ful by it­self.

Put two points to­gether and the line is fixed. Once you know the line, you can read the se­cret from where it crosses zero.

That is a 2-of-n se­cret shar­ing scheme. You can cre­ate as many points as you want, but any two are enough to re­cover the line.

More peo­ple means more bend

For a higher thresh­old, use a curve with more bend.

A parabola needs three points to de­ter­mine it. So if the se­cret is hid­den where the parabola crosses the ver­ti­cal axis, any three shares can re­cover the se­cret and any two can­not.

In gen­eral, a thresh­old of k uses a poly­no­mial of de­gree k - 1.

2 shares: a line

3 shares: a parabola

4 shares: a cu­bic

Real im­ple­men­ta­tions use fi­nite-field arith­metic rather than graph pa­per, but the shape of the idea is the same. The se­cret is the value at zero. The ran­dom co­ef­fi­cients hide it. Each share is one point on the poly­no­mial.

The use­ful part is not that the se­cret is hard to com­pute from too few shares. It is that too few shares con­tain no in­for­ma­tion about the se­cret. With one share miss­ing, every pos­si­ble se­cret is still pos­si­ble.

Why we care

We use this idea in Ente’s Legacy Kit.

Although, our prob­lem was not just “how do we split a se­cret?”, but also “how do we make re­cov­ery pos­si­ble with­out turn­ing the split se­crets into a per­ma­nent re­cov­ery key?”

Legacy Kit uses Shamir’s scheme as one layer in­side a larger flow. The cards don’t carry the re­cov­ery key. They re­con­struct a sep­a­rate se­cret lo­cally, which then par­tic­i­pates in a server-me­di­ated re­cov­ery — so is­sued cards can be re­voked, and a lost card is not a per­ma­nent li­a­bil­ity.

This post is only the math be­hind the “any two, never one” part.

Further read­ing

Adi Shamir’s “How to Share a Secret”

Bruce Schneier’s “Sharing Secrets Among Friends”

Max Levchin’s PayPal story

Ente’s source code

A truly bizarre sit­u­a­tion on Motorola phones has led to the soft­ware hi­jack­ing the Amazon app to in­ject an af­fil­i­ate code — even on the $1,900 Razr Fold.

The shady use of af­fil­i­ate codes has be­come un­for­tu­nately com­mon in re­cent years, with the most high-pro­file ex­am­ple be­ing the PayPal-owned browser ex­ten­sion Honey. But a new sit­u­a­tion on Motorola smart­phones might top the charts in terms of sketchy be­hav­ior.

An app up­date on Motorola phones has started hi­jack­ing the Amazon app for the sake of in­ject­ing an af­fil­i­ate code. To do that, tap­ping the app icon opens the user’s browser and im­me­di­ately redi­rects to the Amazon app. It’s a “blink and you missed it” mo­ment. This only hap­pens when the user opens the Amazon app from the app drawer — not the home­screen pages.

You can see the flow in ac­tion be­low — first open­ing the app from a home­screen icon, then from the app drawer. You’ll no­tice that the Chrome browser flashes up briefly when open­ing from the app drawer.

A Motorola Razr 60 Ultra user on Reddit was the first to no­tice this be­hav­ior, us­ing an ADB log to show that the launcher is di­rect­ing users to a URL in­stead of the Amazon app they ex­pected to open. It traces back to the Smart Feed app, one of the apps Motorola has pre-loaded on many of its phones in­clud­ing the lat­est Razr (2026) fam­ily of fold­ables. A net­work log also shows the de­vice mak­ing re­quests to “devicenative.com,” a web­site for a ser­vice that places ads on smart­phones (and is­n’t too quiet about its in­te­gra­tion with Motorola).

We ver­i­fied on a Razr (2026) run­ning an older Smart Feed v2.03.0056 that this does not hap­pen. Our Razr Fold, with app ver­sion 2.03.0070, has started show­ing this be­hav­ior, so it’s the lat­est up­date that’s to blame for hi­jack­ing the user’s in­tent. We could­n’t repli­cate this on a Moto G Stylus (2026) run­ning the same app ver­sion, though. Sideloading the app, for rea­sons un­clear, does­n’t seem to trig­ger this be­hav­ior, as man­u­ally in­stalling the up­dated ver­sion on the afore­men­tioned Razr (2026) did­n’t show the same be­hav­ior.

In fur­ther dig­ging, we no­ticed that the URL the phone opens up is “kira-abboud.com,” a web­site that ref­er­ences fash­ion in­flu­encer “@kirasfashionfinds.” Notably, this ex­act URL is­n’t listed any­where on Abboud’s so­cial me­dia, and the af­fil­i­ate codes don’t match up ei­ther. The redi­rect com­ing from Motorola phones is us­ing Amazona af­fil­i­ate code “sramz-kff-008 – 20” which is com­pletely dif­fer­ent from any of the codes we saw from links shared by Abboud’s ac­counts and linked web­sites.

Why would Motorola try to hi­jack Amazon af­fil­i­ate rev­enue and pipe it through a fash­ion in­flu­encer? We don’t know — it’s all very strange and makes lit­tle sense.

We’ve reached out to Motorola for com­ment and will up­date this ar­ti­cle as soon as we hear more.

In the mean­time, we can do two things.

Firstly, show you how to turn this off. Since this be­hav­ior is stem­ming from a pre-in­stalled Motorola app, you can just dis­able it (Settings > Apps > search “Smart Feed” > Disable). As far as we can tell, this has no im­me­di­ate im­pact on your de­vice and, on our af­fected Razr Fold, it im­me­di­ately stops the redi­rect.

Secondly, we can spec­u­late as to what’s go­ing on — and that’s what the fol­low­ing is, spec­u­la­tion and con­jec­ture. While many would quickly, un­der­stand­ably, point the fin­ger at Motorola here, my gut says some­thing else is go­ing on, and that it might not be a de­ci­sion Motorola ac­tu­ally planned out. The redi­rect through a seem­ingly fake web­site and af­fil­i­ate code of an in­flu­encer that has no ob­vi­ous ties to Motorola is just too bizarre to ig­nore.

Hopefully, we’ll get more de­tails from Motorola in the near fu­ture. In the mean­time, you should def­i­nitely dis­able the Smart Feed app to pre­vent this be­hav­ior on your de­vice.

More on Motorola:

Motorola Razr (2026) and Razr Fold pre-or­ders open, but you should wait

I used the Motorola Razr Fold for a week, and I think it’s the best fold­able*

Moto G Stylus (2026) might ac­tu­ally be worth $499, if you re­ally want a pen that badly

Follow Ben: Twitter/X, Threads, Bluesky, and In­sta­gram

FTC: We use in­come earn­ing auto af­fil­i­ate links. More.

dynip.dev

Authoritative Control Plane

{{ ac­tiveUser.email }}

Quick Start Guide

{{ showHelp ? ‘Hide’ : ‘Show’ }}

1. Create a Zone: Type your de­vice name, se­lect your pre­ferred base do­main, and click Create Zone.

2. Get the Config: Click the Snippets but­ton next to your new do­main.

3. Deploy: Select your de­vice type and copy the gen­er­ated con­fig­u­ra­tion block di­rectly into your router’s CLI.

Note: IPv4 and IPv6 (Dual-Stack) are de­tected and up­dated au­to­mat­i­cally based on the in­com­ing con­nec­tion.

.

{{ zone.name }} ⚠

Locked

{{ zone.ip }}

Sync: {{ for­mat­Sync­Time(zone.last_­sync) }}

{{ cert­DaysLa­bel(zone) }}

Quick Sync

{{ show­Sync ? ‘Hide’ : ‘Show’ }}

Instantly up­date your se­lected zones to match this de­vice’s cur­rent ex­ter­nal IP ad­dress.

📡

Detected Network IP

{{ mo­bileIp || ‘Detecting…’ }}

{{ zone.name }} {{ zone.ip }}

No zones avail­able. Create one above.

API Automation

{{ showApi ? ‘Hide’ : ‘Show’ }}

Quick test (uses your ses­sion — ex­pires when you log out)

Programmatically reg­is­ter new zones with your cur­rent ses­sion to­ken. Send a POST re­quest to the /register end­point.

curl -X POST “{{ back­endUrl }}/register?subdomain=my-new-router&base_domain={{ base­Do­mains[0] }}” \ -H “Authorization: Bearer {{ to­ken }}”

Session to­kens ex­pire on lo­gout — use an API to­ken be­low for long-run­ning au­toma­tion.

API to­kens (Pro+)

API to­kens are a Pro fea­ture

Long-lived to­kens for au­toma­tion: mon­i­tor­ing scripts, CI pipelines, MSP in­te­gra­tions. Tokens don’t ex­pire when you log out.

Upgrade to Pro →

Long-lived to­kens for au­toma­tion. Each to­ken can be scoped read-only or full ac­cess, and re­voked at any time.

Loading to­kens…

No API to­kens yet. Create one to get started.

New API Token

Tokens are shown once at cre­ation — store them in a pass­word man­ager or se­crets vault.

Name

Scope

Read-only

Full ac­cess

Expires

{{ api­To­ken­Modal.er­ror }}

⚠ Save this to­ken now

This to­ken won’t be shown again. Store it some­where se­cure (1Password, Bitwarden, your CI’s se­crets man­ager).

{{ api­To­ken­Modal.cre­ated.to­ken }}

POSTS

A sad look at the state of mod­ern pro­gram­ming books.

FILED 2026 – 05-25

WORDS 873

READ 5 MIN

BY CYRUS

There was, for a long time, a wall.

If you walked into a book store, past the mag­a­zines and the cook­books, you’d ar­rive at the com­puter sec­tion, and along one wall there was a stretch of books with car­toon an­i­mals on their cov­ers. A rhino for JavaScript. A camel for Perl. A python (obviously) for Python. And what­ever this was:

They were thick, they cost about $50, and they had ti­tles like “Learning React” and “HTTP: The Definitive Guide”. If you wanted to learn how to do a thing on a com­puter, you bought one of these, took it home, and opened it up next to your com­puter and typed what it said un­til the thing worked.

That wall is smaller now. If it’s even still there. In some stores the wall is gone and rel­e­gated to a small rack that has six books on it, three of which are about ChatGPT.

Through the first nine months of 2023, sales in the “computer book” cat­e­gory at Circana BookScan (the in­dus­try’s stan­dard tracker, which costs roughly the price of a small used car to sub­scribe to) were down 16.9% year over year. Publishers Weekly, which had been du­ti­fully re­port­ing these fig­ures in its quar­terly nar­ra­tive sum­maries, kept do­ing so right up through that 16.9% fig­ure, and then in 2024 and 2025 sim­ply stopped men­tion­ing the cat­e­gory by name.

To be clear, books in gen­eral are do­ing fine. Total U.S. print sales reached 762.4 mil­lion units in 2025, up 0.3% over 2024, which was it­self up 0.5% over 2023. The cat­e­gory that is in trou­ble is the part of it that teaches you how to make soft­ware. The American Association of Publishers’ “professional books” seg­ment, which is the rough cor­po­rate proxy for “books your em­ployer might buy you,” fell 22.3% in August 2025.

The book in­dus­try is fine but the tech­ni­cal end is bleed­ing out.

Quickly and qui­etly. There was no Napster mo­ment for the pro­gram­ming book. Nobody filed a law­suit. The pub­lish­ers did not, as far as I can tell, even hold a press con­fer­ence. We sim­ply found one day that they stopped re­port­ing the cat­e­gory it­self. The cat­e­gory does­n’t die, it just stops be­ing talked about.

You al­ready know why, more or less. ChatGPT has over 900 mil­lion monthly ac­tive users. GitHub Copilot has 4.7 mil­lion pay­ing sub­scribers as of January 2026, up roughly 75% in a year. You can’t imag­ine writ­ing soft­ware with­out Claude Code any­more.

Stack Overflow is re­ceiv­ing about 3,800 ques­tions a month, which is what it was get­ting in 2008, be­fore it had fin­ished be­ing launched. The chat­bots have eaten the de­mand for the kinds of an­swers that pro­gram­ming books used to pro­vide.

The pro­gram­ming book was, when you look at it squarely, al­ways a slightly ab­surd ob­ject. Printed text on bound pa­per, de­scrib­ing soft­ware that lived on screens, which the reader had to re­type, by hand, into a screen of their own. I loved do­ing this and they re­main some of my very fond­est child­hood mem­o­ries. But the medium was wrong for the con­tent. People put up with it be­cause there was no bet­ter way to get a care­ful sus­tained ex­pla­na­tion of a tech­ni­cal thing into one per­son’s head from an­other per­son’s.

What the book was good at, de­spite be­ing the wrong for­mat, was forc­ing both the writer and the reader to be slow. You can­not fake your way through 400 pages. It took a cer­tain dis­ci­pline to get through.

The chat­bot does not have this dis­ci­pline. The chat­bot has read every book and for­got­ten the point of every one of them. It will ex­plain idem­po­tency in the pre­cise num­ber of words you re­quire, and you will close the tab, and you will not re­mem­ber what it told you, be­cause you did not type it.

That last sen­tence is the whole thing. Knowledge, for work­ing pro­gram­mers, was al­ways the residue of typ­ing. Of do­ing. The typ­ing was the prac­tice! What is go­ing away is the typ­ing.

Which, on bal­ance, may be fine. I don’t know. People used to lose week­ends to in­stalling Linux from a stack of flop­pies and strug­gling with WinModems, and no­body pre­tends that was char­ac­ter-build­ing (though I now con­sider them fond mem­o­ries too). Tools get eas­ier. Skills shift. The kid who is right now learn­ing to code by chat­ting with an agent is not a worse pro­gram­mer than I was at 12, hunched over Learning Perl, re­typ­ing ex­am­ples that would not run be­cause I missed a semi­colon.

That kid is a dif­fer­ent pro­gram­mer. They are, in some ways I don’t fully un­der­stand, work­ing at a higher level of ab­strac­tion than I ever did at that age, and the things they will build with that ab­strac­tion will sur­prise me.

But some­where in a used book­store in San Francisco or Seattle or wher­ever used book­stores still ex­ist, there is a 1997 edi­tion of Learning Perl. It smells faintly of base­ment. Someone wrote their name in the front of it in pen­cil. There is a fu­ri­ously un­der­lined sen­tence in chap­ter 7 about reg­u­lar ex­pres­sions that was made in anger. On page 112 there are cof­fee stains where the caf­feine blots are some­how still a valid Perl pro­gram.

The book costs three dol­lars. Nobody is go­ing to buy it.