We’ve been search­ing for a mem­ory-safe pro­gram­ming lan­guage to re­place C++ in Ladybird for a while now. We pre­vi­ously ex­plored Swift, but the C++ in­terop never quite got there, and plat­form sup­port out­side the Apple ecosys­tem was lim­ited. Rust is a dif­fer­ent story. The ecosys­tem is far more ma­ture for sys­tems pro­gram­ming, and many of our con­trib­u­tors al­ready know the lan­guage. Going for­ward, we are rewrit­ing parts of Ladybird in Rust.

When we orig­i­nally eval­u­ated Rust back in 2024, we re­jected it be­cause it’s not great at C++ style OOP. The web plat­form ob­ject model in­her­its a lot of 1990s OOP fla­vor, with garbage col­lec­tion, deep in­her­i­tance hi­er­ar­chies, and so on. Rust’s own­er­ship model is not a nat­ural fit for that.

But af­ter an­other year of tread­ing wa­ter, it’s time to make the prag­matic choice. Rust has the ecosys­tem and the safety guar­an­tees we need. Both Firefox and Chromium have al­ready be­gun in­tro­duc­ing Rust into their code­bases, and we think it’s the right choice for Ladybird too.

Our first tar­get was LibJS , Ladybird’s JavaScript en­gine. The lexer, parser, AST, and byte­code gen­er­a­tor are rel­a­tively self-con­tained and have ex­ten­sive test cov­er­age through test262, which made them a nat­ural start­ing point.

I used Claude Code and Codex for the trans­la­tion. This was hu­man-di­rected, not au­tonomous code gen­er­a­tion. I de­cided what to port, in what or­der, and what the Rust code should look like. It was hun­dreds of small prompts, steer­ing the agents where things needed to go. After the ini­tial trans­la­tion, I ran mul­ti­ple passes of ad­ver­sar­ial re­view, ask­ing dif­fer­ent mod­els to an­a­lyze the code for mis­takes and bad pat­terns.

The re­quire­ment from the start was byte-for-byte iden­ti­cal out­put from both pipelines. The re­sult was about 25,000 lines of Rust, and the en­tire port took about two weeks. The same work would have taken me mul­ti­ple months to do by hand. We’ve ver­i­fied that every AST pro­duced by the Rust parser is iden­ti­cal to the C++ one, and all byte­code gen­er­ated by the Rust com­piler is iden­ti­cal to the C++ com­pil­er’s out­put. Zero re­gres­sions across the board:

No per­for­mance re­gres­sions on any of the JS bench­marks we track ei­ther.

Beyond the test suites, I’ve done ex­ten­sive test­ing by brows­ing the web in a lock­step mode where both the C++ and Rust pipelines run si­mul­ta­ne­ously, ver­i­fy­ing that out­put is iden­ti­cal for every piece of JavaScript that flows through them.

If you look at the code, you’ll no­tice it has a strong “translated from C++” vibe. That’s be­cause it is trans­lated from C++. The top pri­or­ity for this first pass is com­pat­i­bil­ity with our C++ pipeline. The Rust code in­ten­tion­ally mim­ics things like the C++ reg­is­ter al­lo­ca­tion pat­terns so that the two com­pil­ers pro­duce iden­ti­cal byte­code. Correctness is a close sec­ond. We know the re­sult is­n’t id­iomatic Rust, and there’s a lot that can be sim­pli­fied once we’re com­fort­able re­tir­ing the C++ pipeline. That cleanup will come in time.

This is not be­com­ing the main fo­cus of the pro­ject. We will con­tinue de­vel­op­ing the en­gine in C++, and port­ing sub­sys­tems to Rust will be a side­track that runs for a long time. New Rust code will co­ex­ist with ex­ist­ing C++ through well-de­fined in­terop bound­aries.

We want to be de­lib­er­ate about which parts get ported and in what or­der, so the port­ing ef­fort is man­aged by the core team. Please co­or­di­nate with us be­fore start­ing any port­ing work so no­body wastes their time on some­thing we can’t merge.

I know this will be a con­tro­ver­sial move, but I be­lieve it’s the right de­ci­sion for Ladybird’s fu­ture. :^)

Brian Merchant, writ­ing for Blood in the Machine, re­ports that peo­ple across the United States are dis­man­tling and de­stroy­ing Flock sur­veil­lance cam­eras, amid ris­ing pub­lic anger that the li­cense plate read­ers aid U. S. im­mi­gra­tion au­thor­i­ties and de­por­ta­tions.

Flock is the Atlanta-based sur­veil­lance startup val­ued at $7.5 bil­lion a year ago and a maker of li­cense plate read­ers. It has faced crit­i­cism for al­low­ing fed­eral au­thor­i­ties ac­cess to its mas­sive net­work of na­tion­wide li­cense plate read­ers and data­bases at a time when U. S. Immigration and Customs Enforcement is in­creas­ingly re­ly­ing on data to raid com­mu­ni­ties as part of the Trump ad­min­is­tra­tion’s im­mi­gra­tion crack­down.

Flock cam­eras al­low au­thor­i­ties to track where peo­ple go and when by tak­ing pho­tos of their li­cense plates from thou­sands of cam­eras lo­cated across the United States. Flock claims it does­n’t share data with ICE di­rectly, but re­ports show that lo­cal po­lice have shared their own ac­cess to Flock cam­eras and its data­bases with fed­eral au­thor­i­ties.

While some com­mu­ni­ties are call­ing on their cities to end their con­tracts with Flock, oth­ers are tak­ing mat­ters into their own hands.

Merchant re­ports in­stances of bro­ken and smashed Flock cam­eras in La Mesa, California, just weeks af­ter the city coun­cil ap­proved the con­tin­u­a­tion of Flock cam­eras de­ployed in the city, de­spite a clear ma­jor­ity of at­ten­dees fa­vor­ing their shut­down. A lo­cal re­port cited strong op­po­si­tion to the sur­veil­lance tech­nol­ogy, with res­i­dents rais­ing pri­vacy con­cerns.

Other cases of van­dal­ism have stretched from California and Connecticut to Illinois and Virginia. In Oregon, six li­cense plate-scan­ning cam­eras on poles were cut down and at least one spray-painted. A note left at the base of the sev­ered poles said, “Hahaha get wrecked ya sur­veilling fucks,” re­ports Merchant.

According to DeFlock, a pro­ject aimed at map­ping li­cense plate read­ers, there are close to 80,000 cam­eras across the United States. Dozens of cities have so far re­jected the use of Flock’s cam­eras, and some po­lice de­part­ments have since blocked fed­eral au­thor­i­ties from us­ing their re­sources.

A Flock spokesper­son did not say, when reached by TechCrunch, if the com­pany keeps track of how many cam­eras have been de­stroyed since be­ing de­ployed.

My old 2016 MacBook Pro has been col­lect­ing dust in a cab­i­net for some time now. The lap­top suf­fers from a “flexgate” prob­lem, and I don’t have any prac­ti­cal use for it. For quite some time, I’ve been think­ing about re­pur­pos­ing it as a guinea pig, to play with FreeBSD — an OS that I’d as­pired to play with for a long while, but had never had a real rea­son to.

During the re­cent hol­i­day sea­son, right af­ter FreeBSD 15 re­lease, I’ve fi­nally found time to set the lap­top up. Doing that I did­n’t plan, or even think, this may turn into a story about AI cod­ing.

2016 MacBook Pro mod­els use Broadcom BCM4350 Wi-Fi chip. FreeBSD does­n’t have na­tive sup­port for this chip. To have a work­ing Wi-Fi, a typ­i­cal sug­ges­tion on FreeBSD fo­rums, is to run wifi­box — a tiny Linux VM, with the PCI Wi-Fi de­vice in pass through, that al­lows Linux to man­age the de­vice through its br­cmf­mac dri­ver.

Brcmfmac is a Linux dri­ver (ISC li­cence) for set of FullMAC chips from Broadcom. The dri­ver of­floads the pro­cess­ing jobs, like 802.11 frame move­ment, WPA en­cryp­tion and de­cryp­tion, etc, to the firmware, which is run­ning in­side the chip. Meanwhile, the dri­ver and the OS do high-level man­age­ment work (ref Broadcom br­cmf­mac(PCIe) in Linux Wireless doc­u­men­ta­tion).

Say we want to build a na­tive FreeBSD ker­nel mod­ule for the BCM4350 chip. In the­ory, this sep­a­ra­tion of jobs be­tween the firmware and the dri­ver sounds per­fect. The “management” part of work is what FreeBSD al­ready does for other sup­ported Wi-Fi de­vices. We need to port some amount of ex­ist­ing “glue code” from specifics of Linux to FreeBSD. If we ig­nore a lot of de­tails, the prob­lem does­n’t sound too com­pli­cated, right?

A level-zero idea, when one hears about “porting a bunch of ex­ist­ing code from A to B”, in 2026 is, of course, to use AI. So that was what I tried.

I cloned the br­cmf­mac sub­tree, and asked Claude Code to make it work for FreeBSD. FreeBSD al­ready has dri­vers that work through LinuxKPI — com­pat­i­bil­ity layer for run­ning Linux ker­nel dri­vers. So I specif­i­cally pointed Claude at the iwl­wifi dri­ver (a soft­mac dri­ver for Intel wire­less net­work card), ask­ing “do as they did it”. And, at first, this even looked like this can work — Claude told me so.

The mod­ule, in­deed, com­piled, but it did­n’t do any­thing. Because, of course: the VM, where we tested the mod­ule, did­n’t even have the hard­ware. After I set the PCI de­vice into the VM, and at­tempted to load the dri­ver against the chip, the chal­lenges started to pop up im­me­di­ately. The ker­nel pan­iced, and af­ter Claude fixed the pan­ics, it dis­cov­ered that “module did­n’t do any­thing”. Claude hon­estly tried to sift through the code, adding more and more #ifdef __FreeBSD__ wrap­pers here and there. It com­plained about miss­ing fea­tures in LinuxKPI. The mod­ule kept caus­ing pan­ics, and the agent kept build­ing FreeBSD-specific shims and call­backs, while warn­ing me that this pro­ject will be very com­pli­cated and messy.

After a num­ber of ses­sions, the diff, pro­duced by the agent, stared to look sig­nif­i­cantly larger than what I’d hoped it will be. Even worse, the dri­ver did­n’t look even close to be work­ing. This was right around time when Armin Ronacher posted about his ex­pe­ri­ence build­ing a game from scratch with Claude Opus and PI agent.

Besides the part that work­ing in Pi cod­ing agent feels more pro­duc­tive, than in Claude Code, the video got me think­ing that my ap­proach to the task was too straight­for­ward. The code of br­cmf­mac dri­ver is mod­er­ately large. The dri­ver sup­ports sev­eral gen­er­a­tions of Wi-Fi adap­tors, dif­fer­ent ca­pa­bil­i­ties, etc. But my im­me­di­ate task was very nar­row: one chip, only PCI, only Wi-Fi client.

Instead of con­tin­u­ing with the code, I spawned a fresh Pi ses­sion, and asked the agent to write a de­tailed spec­i­fi­ca­tion of how the br­cmf­mac dri­ver works, with the fo­cus on BCM4350 Wi-Fi chip. I ex­plic­itly set the au­di­ence for the spec­i­fi­ca­tion to be read­ers, who are tasked with im­ple­ment­ing the spec­i­fi­ca­tion in a clean-room en­vi­ron­ment. I asked the agent to ex­plain how things work “to the bits”. I added some high-level de­tails for how I wanted the spec­i­fi­ca­tion to be laid out, and let the agent go br­rrr.

After a cou­ple of rounds, the agent pro­duced me a “book of 11 chap­ters”, that hon­estly looked like a fine spec­i­fi­ca­tion

% ls –tree spec/

spec

├── 00-overview.md

├── 01-data-structures.md

├── 02-bus-layer.md

├── 03-protocol-layer.md

├── 04-firmware-interface.md

├── 05-event-handling.md

├── 06-cfg80211-operations.md

├── 07-initialization.md

├── 08-data-path.md

├── 09-firmware-commands.md

└── 10-structures-reference.md

Of course, one can’t just trust what AI has writ­ten.

To proof­read the spec I spawned a clean Pi ses­sions, and — for fun — asked Codex model, to read the spec­i­fi­ca­tion, and flag any places, where the text is­n’t aligned with the dri­ver’s code (“Source code is the ground truth. The spec needs to be ver­i­fied, and up­dated with any miss­ing or wrong de­tails”). The agent fol­lowed through and found sev­eral places to fix, and also pro­posed mul­ti­ple im­prove­ments.

Of course, one can’t just trust what AI has writ­ten, even if this was in a proof­read­ing ses­sion.

To dou­ble-proof­read the fixes I spawned an­other clean Pi ses­sions, ask­ing Opus model to ver­ify if what was pro­posed was aligned with how it works in the code of the dri­ver.

As a pro­cras­ti­na­tion ex­er­cise, I tried this loop with a cou­ple of cod­ing mod­els: Opus 4.5, Opus 4.6, Codex 5.2, Gemini 3 Pro pre­view. So far my ex­pe­ri­ence was that Gemini hal­lu­ci­nated the most. This was quite sad, given that the model it­self is­n’t too bad for sim­ple cod­ing tasks, and it is free for a lim­ited use.

Having a writ­ten spec­i­fi­ca­tion should have (in the­ory) ex­plained how a dri­ver’s code in­ter­acts with the firmware.

I started a fresh pro­ject, with noth­ing but the men­tioned “spec”, and prompted the Pi agent, that we were build­ing a brand new FreeBSD dri­ver for BCM4350 chip. I pointed the agent to the spec­i­fi­ca­tion, and asked it to ask me back about any im­por­tant de­ci­sions we must make, and de­tails we must out­line, be­fore jump­ing into “slopping the code”. The agent came back with ques­tions and de­ci­sion points, like “Will the dri­ver live in the ker­nels source-tree?”, “Will we write the code in C?”, “Will we rely on LinuxKPI?”, “What are our high-level mile­stones?”, etc. One in­flu­en­tial bit, that turned fairly pro­duc­tive mov­ing for­ward, was that I asked the agent to doc­u­ment all these de­ci­sion points in the pro­jec­t’s docs, and to ex­plic­itly ref­er­enced to these de­ci­sion docs in the pro­jec­t’s AGENTS.md.

It’s worth say­ing that, just like in any real pro­ject, not all de­ci­sions stayed to the end. For ex­am­ple,

Initially I asked the agent to build the dri­ver us­ing lin­uxkpi and lin­uxkpi_wlan. My naive think­ing was that, given the spec was writ­ten af­ter look­ing at Linux dri­ver’s code, it might be sim­pler for the agent, than build­ing the on top of the na­tive prim­i­tives. After a cou­ple of ses­sions, it did­n’t look like this was the case. I asked the agent to drop LinuxKPI from the code, and to refac­tor every­thing. The agent did it in one go, and up­dated the de­ci­sion doc­u­ment.

With spec­i­fi­ca­tion, docs and a plan, the work­flow process turned into a “boring rou­tine”. The agent had SSH ac­cess to both the build host, and a test­ing VM, that had been run­ning with the Wi-Fi PCI de­vice passed from the host. It me­thod­i­cally crunched through the back­log of its own mile­stones, it­er­at­ing over the code, build­ing and test­ing the mod­ule. Every time a mile­stone or a por­tion was fin­ished, I asked the agent to record the progress to the docs. Occasionally, an it­er­a­tion of the code crashed or hanged the VM. When this hap­pened, be­fore fix­ing the prob­lem, I asked — in a forked Pi’s ses­sion — to sum­ma­rize, in­ves­ti­gate and record the prob­lem for agen­t’s fu­ture-self.

After many low-in­volved ses­sions, I got a work­ing FreeBSD ker­nel mod­ule for the BCM4350 Wi-Fi chip. The mod­ule sup­ports Wi-Fi net­work scan­ning, 2.4GHz/5GHz con­nec­tiv­ity, WPA/WPA2 au­then­ti­ca­tion.

The source code is in repos­i­tory github.com/​narqo/​freebsd-br­cmf­mac. I did­n’t write any piece of code there. There are sev­eral known is­sues, which I will task the agent to re­solve, even­tu­ally. Meanwhile, I ad­vise against us­ing it for any­thing be­yond a study­ing ex­er­cise.

This ar­ti­cle has been re­viewed ac­cord­ing to Science X’s editorial process

and poli­cies. Editors have high­lighted the fol­low­ing at­trib­utes while en­sur­ing the con­tent’s cred­i­bil­ity:

This ar­ti­cle has been re­viewed ac­cord­ing to Science X’s editorial process

and poli­cies. Editors have high­lighted the fol­low­ing at­trib­utes while en­sur­ing the con­tent’s cred­i­bil­ity:

A pro­tein lurk­ing around in the blood can help with the ac­cu­rate di­ag­no­sis of Alzheimer’s dis­ease. In a re­cent study, re­searchers from Spain in­ves­ti­gated how blood-based bio­mark­ers, such as a pro­tein called p-tau217, af­fect both the clin­i­cal di­ag­no­sis of Alzheimer’s and neu­rol­o­gists’ con­fi­dence in their di­ag­no­sis.

After fol­low­ing 200 con­sec­u­tive new pa­tients aged 50 and older who pre­sented with cog­ni­tive symp­toms, they found that a sim­ple blood test mea­sur­ing p-tau217 sig­nif­i­cantly im­proved di­ag­nos­tic ac­cu­racy in rou­tine clin­i­cal prac­tice.

When re­ly­ing solely on stan­dard clin­i­cal eval­u­a­tion, doc­tors cor­rectly di­ag­nosed Alzheimer’s in 75.5% of cases, but when in­cor­po­rat­ing blood test re­sults, di­ag­nos­tic ac­cu­racy in­creased to 94.5%. The find­ings are pub­lished in the Journal of Neurology.

Phosphorylated tau, or p-tau217, is a pro­tein that nat­u­rally oc­curs in the brain and helps keep neu­rons, the cells that carry sig­nals, sta­ble and healthy. The trou­ble be­gins when this pro­tein be­comes ab­nor­mally phos­pho­ry­lated and clumps to­gether, form­ing tan­gles that dis­rupt com­mu­ni­ca­tion be­tween brain cells. Over time, this dam­age can im­pact brain func­tion and lead to neu­rode­gen­er­a­tive con­di­tions such as Alzheimer’s dis­ease.

While p-tau217 is not con­sid­ered the di­rect cause of Alzheimer’s, el­e­vated lev­els in the blood are now rec­og­nized as one of the most ac­cu­rate early warn­ing signs of the dis­ease.

In many parts of the world, the pop­u­la­tion is rapidly ag­ing and so is the num­ber of age-re­lated dis­eases like Alzheimer’s and de­men­tia. However, most of the stan­dard ways to di­ag­nose Alzheimer’s to­day, like ex­pen­sive brain scans or in­va­sive spinal taps, are costly, un­com­fort­able, and of­ten hard for pa­tients to ac­cess.

Scientists have long known that p-tau217 is a re­li­able bio­marker for de­tect­ing early signs of Alzheimer’s, but most of these data come from highly con­trolled re­search labs. How well it works in every­day med­ical clin­ics and whether it truly boosts doc­tors’ con­fi­dence in their di­ag­noses re­main less ex­plored.

In this study, the re­searchers fo­cused on both these fac­tors in real-world med­ical set­tings. They fol­lowed pa­tients who came in for gen­eral neu­rol­ogy con­sul­ta­tions and to a spe­cial­ized cog­ni­tive neu­rol­ogy unit with cog­ni­tive symp­toms. Clinicians noted their ini­tial di­ag­no­sis and how con­fi­dent they felt about it, then re­viewed the p-tau217 blood test re­sults and recorded any changes.

The team found that af­ter re­view­ing the p-tau217 re­sults, di­ag­nos­tic ac­cu­racy jumped by 19%. For about one in four pa­tients, the blood test prompted doc­tors to change their di­ag­no­sis. Some peo­ple who were first be­lieved to have Alzheimer’s turned out to have a dif­fer­ent con­di­tion, while oth­ers who were thought to be ex­pe­ri­enc­ing nor­mal ag­ing were cor­rectly iden­ti­fied as hav­ing Alzheimer’s. Also, the doc­tors’ con­fi­dence in their di­ag­noses rose from an av­er­age of 6.90 to 8.49 on a 10-point scale.

The p-tau217 tests proved to be ef­fec­tive across every stage of cog­ni­tive de­cline, be it early mem­ory com­plaints or late-stage de­cline such as de­men­tia. The find­ings show that this blood test could pro­vide a more ac­cu­rate and less in­va­sive way to di­ag­nose Alzheimer’s, po­ten­tially im­prov­ing care for mil­lions of peo­ple.

The lat­est up­date of Firefox, ver­sion 148, in­tro­duces a much-an­tic­i­pated “AI kill switch” fea­ture, al­low­ing users to dis­able AI func­tion­al­i­ties such as chat­bot prompts and AI-generated link sum­maries. Mozilla em­pha­sizes that once AI fea­tures are turned off, fu­ture up­dates will not over­ride this choice. This de­ci­sion re­flects the com­pa­ny’s new rev­enue-fo­cused strat­egy re­gard­ing AI in­te­gra­tions.

To dis­able AI fea­tures, users can nav­i­gate to Settings > AI Controls and tog­gle the ‘Block AI Enhancements’ op­tion. This will pre­vent any in-app no­ti­fi­ca­tions en­cour­ag­ing users to try out AI fea­tures, as well as re­move any pre­vi­ously down­loaded AI mod­els from the de­vice. For those who wish to main­tain some AI func­tion­al­i­ties, a se­lec­tive block­ing op­tion is avail­able, en­abling users to re­tain use­ful fea­tures like on-de­vice trans­la­tions while avoid­ing cloud-based ser­vices.

Beyond the AI kill switch, Firefox 148 of­fers users more con­trol over re­mote up­dates, al­low­ing them to opt out while still min­i­miz­ing data col­lec­tion. Users can set these pref­er­ences un­der Settings > Privacy & Settings > Firefox Data Collection.

The up­date also fo­cuses on en­hanc­ing core web plat­form ca­pa­bil­i­ties, in­clud­ing the in­te­gra­tion of the Trusted Types API and Sanitizer API to com­bat cross-site script­ing (XSS) is­sues. Additionally, Firefox 148 now in­cludes im­proved screen reader com­pat­i­bil­ity for math­e­mat­i­cal for­mu­las in PDFs, avail­abil­ity of Firefox Backup on Windows 10, and trans­la­tion ca­pa­bil­i­ties for Vietnamese and Traditional Chinese. New tab wall­pa­pers will also be fea­tured in new con­tainer tabs, along­side the ad­di­tion of Service worker sup­port for WebGPU.

For more de­tailed in­for­ma­tion on the up­date, users can re­fer to the of­fi­cial re­lease notes.

Meta, Amazon, Google, OpenAI, and other tech com­pa­nies spent bil­lions last year in­vest­ing in AI. They’re ex­pected to spend even more, roughly $700 bil­lion, this year on dozens of new data cen­ters to train and run their ad­vanced mod­els.

This spend­ing frenzy has kept Wall Street buzzing and fu­eled a nar­ra­tive that all this in­vest­ment is help­ing prop up and even grow the U. S. econ­omy.

President Donald Trump has cited that ar­gu­ment as a rea­son the in­dus­try should not face state-level reg­u­la­tions.

“Investment in AI is help­ing to make the U. S. Economy the ‘HOTTEST’ in the World — But over­reg­u­la­tion by the States is threat­en­ing to un­der­mine this Growth Engine,” Trump wrote in a post on Truth Social in November. “We MUST have one Federal Standard in­stead of a patch­work of 50 State Regulatory Regimes.”

Some promi­nent econ­o­mists have also given cred­i­bil­ity to this story with their analy­sis. Jason Furman, a Harvard eco­nom­ics pro­fes­sor, said in a post on X that in­vest­ments in in­for­ma­tion pro­cess­ing equip­ment and soft­ware ac­counted for 92% of GDP growth in the first half of the year. Meanwhile, econ­o­mists at the Federal Reserve Bank of St. Louis sim­i­larly es­ti­mated that AI-related in­vest­ments made up 39% of GDP growth in the third quar­ter of 2025.

But now some Wall Street an­a­lysts are start­ing to re­think this nar­ra­tive.

“It was a very in­tu­itive story,” Joseph Briggs, a Goldman Sachs an­a­lyst, told The Washington Post on Monday. “That maybe pre­vented or lim­ited the need to ac­tu­ally dig deeper into what was hap­pen­ing.”

Briggs’ col­league, Goldman Sachs Chief Economist Jan Hatzius, said in an in­ter­view with the Atlantic Council that AI in­vest­ment spend­ing has had “basically zero” con­tri­bu­tion to the U. S. GDP growth in 2025.

“We don’t ac­tu­ally view AI in­vest­ment as strongly growth pos­i­tive,” said Hatzius. “I think there’s a lot of mis­re­port­ing, ac­tu­ally, of the im­pact AI in­vest­ment had on U. S. GDP growth in 2025, and it’s much smaller than is of­ten per­ceived.”

Hatzius said one ma­jor rea­son is that much of the equip­ment pow­er­ing AI is im­ported. While U. S. com­pa­nies are spend­ing bil­lions, im­port­ing chips and hard­ware off­sets those in­vest­ments in GDP cal­cu­la­tions.

“A lot of the AI in­vest­ment that we’re see­ing in the U. S. adds to Taiwanese GDP, and it adds to Korean GDP but not re­ally that much to U.S. GDP,” he said.

On top of that, there is cur­rently no re­li­able way to ac­cu­rately mea­sure how AI use among busi­nesses and con­sumers con­tributes to eco­nomic growth.

So far, many busi­ness lead­ers say AI has­n’t sig­nif­i­cantly im­proved pro­duc­tiv­ity.

A re­cent sur­vey of nearly 6,000 ex­ec­u­tives in the U. S., Europe, and Australia found that de­spite 70% of firms ac­tively us­ing AI, about 80% re­ported no im­pact on em­ploy­ment or pro­duc­tiv­ity.

The Las Vegas Metropolitan Police Department (LVMPD) qui­etly en­tered an agree­ment in 2023 with Flock Security, an au­to­mated li­cense plate reader com­pany that uses cam­eras to col­lect ve­hi­cle in­for­ma­tion and cross-ref­er­ence it with po­lice data­bases.

But un­like many of the other po­lice de­part­ments around the coun­try that use the cam­eras in their po­lice work, Metro funds the pro­ject with donor money fun­neled into a pri­vate foun­da­tion. It’s an arrange­ment that al­lows Metro to avoid so­lic­it­ing pub­lic com­ment on the sur­veil­lance tech­nol­ogy, which crit­ics worry could be co-opted to track un­doc­u­mented im­mi­grants, po­lit­i­cal dis­si­dents and abor­tion seek­ers, among oth­ers.

“It’s a short cir­cuit of the de­mo­c­ra­tic process,” Jay Stanley, a Washington D. C.-based lawyer for the American Civil Liberties Union (ACLU) who works on how tech­nol­ogy can in­fringe on in­di­vid­ual pri­vacy and civil lib­er­ties, said in an in­ter­view with The Nevada Independent.

The cam­eras scan li­cense plates as well as ve­hi­cles’ iden­ti­fy­ing de­tails — such as make, model and color — plug­ging that in­for­ma­tion into a na­tional data­base that po­lice can use to search the lo­ca­tion of spe­cific ve­hi­cles be­yond their own ju­ris­dic­tions. Flock op­er­ates more than 80,000 of these AI-powered cam­eras na­tion­wide, and the com­pa­ny’s pop­u­lar­ity has ex­ploded in re­cent years, with po­lice tout­ing it as a tool to solve crime faster and boost pub­lic safety.

Although tax­payer dol­lars fund Flock cam­eras in other ju­ris­dic­tions, most of the cam­eras in the Las Vegas area have been bought with money from the Horowitz Family Foundation, a phil­an­thropy group con­nected to the Las Vegas-based ven­ture cap­i­tal­ist Ben Horowitz, co-founder of the firm Andreessen Horowitz.

The Horowitz Family Foundation did not re­spond to a re­quest for com­ment at the time of pub­li­ca­tion.

Metro told The Nevada Independent that it op­er­ates ap­prox­i­mately 200 Flock li­cense plate reader cam­eras on city or county in­fra­struc­ture and it shares its Flock data with hun­dreds of state and lo­cal law en­force­ment agen­cies through­out the coun­try.

Since late 2023, Las Vegas po­lice have made more than 23,000 searches of ve­hi­cles, ac­cord­ing to the web­site Have I Been Flocked, which com­piles pub­lic au­dit logs of Flock data.

As the cam­eras were not bought with pub­lic funds, Metro does not have to hold meet­ings with the pub­lic to com­ment on the tech­nol­ogy, some­thing ex­perts say leaves cit­i­zens with­out any in­put on the polic­ing method.

In other cities, Stanley said Flock is of­ten brought up and dis­cussed dur­ing city coun­cil meet­ings or other pub­lic fo­rums. It’s not re­quired to be on pub­lic meet­ing agen­das in the Las Vegas area.

“Police de­part­ments serve the com­mu­nity and are sup­posed to make life in the com­mu­nity bet­ter. Does the com­mu­nity want this tech­nol­ogy im­posed on it?” Stanley said.

Though Horowitz’s foun­da­tion do­nated ad­di­tional funds for Flock cam­eras in October, it was not brought up at the Clark County Commission meet­ing that month, nor was their use dis­cussed any­time in 2025, ac­cord­ing to com­mis­sion meet­ing min­utes.

Some mu­nic­i­pal­i­ties in Clark County, such as the City of Las Vegas, have li­cense plate reader poli­cies that in­cludes a pub­lic Flock pol­icy with a dash­board on how many li­cense plates Flock picked up (about 185,000 in the past month in the city), how many cam­eras were in use (22 in Las Vegas), and how many searches had been done on a monthly ba­sis (five in the past 30 days). In com­par­i­son, Metro’s pol­icy is not pub­licly avail­able on­line, though The Indy ob­tained a copy through a pub­lic records re­quest.

Flock’s most re­cent con­tract with Metro, signed in 2023, stip­u­lates that the com­pany re­tains all rights in any record­ings or data pro­vided by the ser­vice and that Flock can use any of the data for “any pur­pose” at the com­pa­ny’s dis­cre­tion. The agree­ment also says that Flock record­ings are not stored for longer than 30 days.

Meanwhile, Metro pol­icy says that de­part­ment mem­bers will not seek or re­tain li­cense plate reader in­for­ma­tion about in­di­vid­u­als or an or­ga­ni­za­tion based solely on their cit­i­zen­ship, so­cial views, race or other clas­si­fi­ca­tions pro­tected by law. The pol­icy states that re­tained li­cense plate reader data does not in­clude spe­cific iden­ti­fi­ca­tion of in­di­vid­u­als. Misuse of the data will re­sult in dis­ci­pli­nary ac­tion up to ter­mi­na­tion, ac­cord­ing to the pol­icy.

But for many, in­clud­ing a for­mer of­fi­cer who spoke to The Indy on the con­di­tion of anonymity for fear of pro­fes­sional reper­cus­sions, such poli­cies are not enough.

“It’s ripe for mis­use,” the of­fi­cer said, point­ing to ex­am­ples around the coun­try of peo­ple us­ing Flock to look for cur­rent and for­mer ro­man­tic part­ners and track their move­ments. A po­lice chief in Kansas used Flock to track his ex-girl­friend 228 times in four months. An of­fi­cer in South Carolina used pub­lic cam­eras to mon­i­tor his wife, who he sus­pected was hav­ing an af­fair.

The for­mer Metro of­fi­cer said his ma­jor con­cern was not the tech­nol­ogy it­self, but the fact that there was lit­tle trans­parency on how the tech­nol­ogy was be­ing used or what the de­part­men­t’s pol­icy was on Flock us­age.

“If you look around the coun­try where li­cense plate read­ers are be­ing used, there’s some kind of pub­lic meet­ing, there’s some kind of pub­lic process,” the of­fi­cer said. “What’s hap­pen­ing here is on a very large scale — they’re putting out sur­veil­lance tech­nol­ogy — and there’s no pub­lic dis­clo­sure.”

The Horowitz Foundation do­na­tion in October in­cluded a soft­ware sub­scrip­tion to Flock’s Nova fea­ture, which al­lows of­fi­cers to eas­ily ac­cess pri­vate li­cense plate in­for­ma­tion along­side other per­sonal data, such as Social Security num­bers, credit scores, prop­erty and oc­cu­pancy in­for­ma­tion, as well as emails or so­cial me­dia han­dles.

Experts say this data could be used to iden­tify un­doc­u­mented im­mi­grants, po­lit­i­cal pro­test­ers and peo­ple trav­el­ing across state lines to ob­tain abor­tions.

Athar Haseebullah, the ex­ec­u­tive di­rec­tor of the ACLU of Nevada, said that Flock not only poses a height­ened risk for im­mi­grants, but any­one en­gaged in ac­tions that are found to be po­lit­i­cally de­fi­ant. He pointed to a case in Texas where po­lice con­ducted a na­tion­wide search us­ing Flock tech­nol­ogy for a woman who self-in­duced an abor­tion.

“This could be ripe for abuse by ICE (Immigrations and Customs Enforcement), but it could also be ripe for abuse by other gov­ern­ment en­ti­ties,” Haseebullah said. In 2025, the ACLU pushed back against a mea­sure that would al­low lo­cal ju­ris­dic­tions to use au­to­mated traf­fic cam­eras to crack down on speed­ing and red-light cross­ings, al­though the bill was never voted on.

Flock has re­ceived back­lash na­tion­wide for al­low­ing fed­eral agen­cies such as Customs and Border Patrol to tap into their data. The com­pany has said it does not work with ICE af­ter ev­i­dence was found that the agency used Flock data for im­mi­gra­tion in­ves­ti­ga­tions. Several cities have ter­mi­nated or mod­i­fied their Flock agree­ments af­ter re­al­iz­ing they were in­ad­ver­tently shar­ing their data with other agen­cies.

However, though Flock might not want to part­ner with ICE, it has lit­tle choice — Flock is ob­lig­ated to ful­fill sub­poe­nas from ICE and can’t refuse a le­gal war­rant, Andrew Ferguson, an at­tor­ney and a pro­fes­sor re­search­ing tech and po­lice sur­veil­lance at George Washington University, said.

Flock’s sur­veil­lance cam­eras are meant to catch crime, though ex­perts say it could de­ter cer­tain be­hav­iors if cit­i­zens are aware they are be­ing watched.

“There’s a chill­ing ef­fect know­ing that your gov­ern­ment is es­sen­tially track­ing you wher­ever you go,” Ferguson said. “It might be even more chill­ing if you put cam­eras in sen­si­tive places, like a med­ical clinic, or a Gambler’s Anonymous meet­ing, or a church.”

In a city such as Las Vegas, known for drink­ing, gam­bling and a hearty party cul­ture, sur­veil­lance is the last thing peo­ple are in­ter­ested in, ac­cord­ing to Ferguson.

“Things are hap­pen­ing in Vegas that are not go­ing to stay in Vegas,” Ferguson said. “They’re go­ing to be broad­cast through Flock.”

As re­cently as October of last year, the Horowitz Family Foundation do­nated al­most $1.9 mil­lion for Flock li­cense plate read­ers and an­other $2.47 mil­lion for sup­port­ing soft­ware for Flock ma­chines, ac­cord­ing to the min­utes of an LVMPD fis­cal af­fairs com­mit­tee meet­ing.

Because the do­na­tions aren’t com­ing di­rectly to Metro, but to the non­profit LVMPD foun­da­tion, also known as “Friends of Metro,” any dis­cus­sions on the cam­eras’ use aren’t sub­ject to Nevada’s open meet­ing laws.

The li­cense plate read­ers and their sup­port­ing soft­ware are not the only gift that the Horowitz Family Foundation, led by Ben Horowitz’s wife, Felicia Horowitz, has do­nated to Las Vegas po­lice. The foun­da­tion has also gifted drones, as well as Tesla Cybertrucks, to the agency.

Proponents have billed the gifts as morale boost­ers for po­lice that help the agency stay on the cut­ting edge with­out tap­ping into lim­ited tax­payer dol­lars. Critics, such as the Progressive Leadership Alliance of Southern Nevada, have sug­gested that the Cybertrucks show that Metro is “prioritizing cor­po­rate give­aways.”

Felicia Horowitz said she is fo­cused on “creating the best com­mu­nity in America” in Las Vegas, ac­cord­ing to her bio from a lo­cal non­profit or­ga­ni­za­tion that she sits on the board of. Part of that is com­bat­ing crime and keep­ing cit­i­zens safe. In a Wall Street Journal ar­ti­cle, Felicia Horowitz em­pha­sized how crime and weak polic­ing had hurt Black com­mu­ni­ties across the coun­try.

“The new poli­cies — de­fund the po­lice, don’t pros­e­cute crime — are de­stroy­ing the com­mu­ni­ties where I grew up,” Felicia Horowitz, who is Black, told the WSJ in 2024. Felicia Horowitz was raised in Los Angeles and the Horowitzes re­lo­cated to Las Vegas around 2021 and 2022 af­ter decades in California.

So far, the foun­da­tion has not pub­licly com­mented on whether it will con­tinue do­nat­ing money for Flock ser­vices. Some ex­perts think the do­na­tions might be a strat­egy called “penetration pric­ing,” where a com­pany gives free or re­duced prod­ucts or ser­vices in or­der to hook con­sumers be­fore charg­ing them.

“There’s no ques­tion that there’s a fi­nan­cial in­ter­est in them prov­ing that the Flock tech­nol­ogy works in Las Vegas so that they can sell it to other places,” said Ferguson.

The for­mer po­lice of­fi­cer said he was con­cerned about tax­pay­ers hav­ing to cough up funds to con­tinue Flock ser­vices if the Horowitz money ran dry.

“Once you start re­ly­ing on a cer­tain type of polic­ing, it’s go­ing to be hard to switch over, and then who will foot the bill?” the of­fi­cer said.

Tenant and prod­uct or co-owner and par­tic­i­pant?

Today the Web and Internet is owned and con­trolled by large for profit cor­po­ra­tions and a few gov­ern­ments. Corporate own­er­ship com­bined with gov­ern­ment poli­cies has left us as ten­ant and prod­uct. It has given us a sur­veil­lance econ­omy and en­shit­ti­fi­ca­tion.

* What if I do not wish to be ten­ant and prod­uct?

* What can I do to change the equa­tion?

Those two ques­tions lead me to a big­ger ques­tion.

* What hap­pens when own­er­ship and con­trol of hard­ware and soft­ware shifts from the do­main of cor­po­ra­tions to a world where a sig­nif­i­cant per­cent­age are owned by in­di­vid­ual peo­ple and co­op­er­a­tives?

I think the an­swer is sug­gested by a corol­lary found in the his­tory of la­bor move­ments. When a sig­nif­i­cant per­cent­age of in­dus­tries were union­ized the unions ex­erted a strong in­flu­ence across the po­lit­i­cal econ­omy. I think own­er­ship of the hard­ware and soft­ware can mir­ror that im­pact on the Web and Internet. I think when a sig­nif­i­cant num­ber of in­di­vid­u­als and co­op­er­a­tives own the hard­ware and uses sim­pler soft­ware we can im­pact the Web and Internet in a pos­i­tive way. That’s my hy­poth­e­sis.

An ob­ser­va­tion and com­mon some as­sump­tions:

* Most con­tent on the web is al­ready cre­ated by in­di­vid­u­als not Big Co

* Big Co per­suaded peo­ple that only Big Co could pro­vide easy Web pub­li­ca­tion

* Big Co con­vinced many there was no point in look­ing for al­ter­na­tives

The as­sump­tion that only Big Co can pro­vide easy Web pub­li­ca­tion is just flat out wrong. These sys­tems don’t last for more than a decade be­fore they de­cay. Each of Big Co ori­gin story are sim­i­lar. They started small. They get to scale by hav­ing in­vestors who fund and push rapid ex­pan­sion. Innovation slows so they buy up any po­ten­tial ri­vals. Big Co then ei­ther shut them down or fold the ri­val sys­tem into their prod­uct lines. The last real in­no­va­tion these com­pa­nies in­tro­duced was decades ago. Lack of real in­no­va­tion is one of the fac­tors that drive the Big Co and Big Tech hype cy­cle. They pro­claim a new shiny thing in or­der to main­tain the cir­cus that ac­cu­mu­lates more money. Along the way Big Co in­sists on tax breaks and zero reg­u­la­tion as a pre­req­ui­site for in­no­va­tion which is­n’t de­liv­ered. When they did in­no­vate they did­n’t have the breaks they in­sist on now, hell they did­n’t have the in­vest­ment or mar­ket lock they have now. They only need the hype cy­cle, not in­no­va­tion, to keep the money rolling in. At the end of the day we wind up the prod­uct, we wind up be­ing ex­ploited and we get very lit­tle use­ful in re­turn.

Folks there is an al­ter­na­tive. In 1992 au­thor­ing for the Web did re­quire sig­nif­i­cant tech­ni­cal knowl­edge. HTML it­self was very chal­leng­ing to teach peo­ple. It was chal­leng­ing to teach com­puter en­thu­si­asts! I was in­volved in help­ing out at classes that taught HTML back in the early 1990s. I speak from first hand ex­pe­ri­ence. But a funny thing hap­pened on the way to 2026. A tech writer (John Grubber and friends) came up with a sim­pler ex­pres­sion of hy­per­text called Markdown. You don’t need to know HTML to cre­ate a web page or blog post to­day. You can write it or read it us­ing Markdown. You can write it us­ing the sim­ple text ed­i­tor that came with your op­er­at­ing sys­tem on the com­puter you own. You only need a pro­gram to flip Markdown into HTML. There are plenty of pro­grams out there that do that.

In the past many of our ef­forts to break free of Big Co have met with lim­ited suc­cess. Usually the en­ergy and ef­fort has been spent re-cre­at­ing the cen­tral­ized sys­tems as dis­trib­uted sys­tems. There was a sense we needed to of­fer the same ex­pe­ri­ence as Big Co. While ide­ally in­di­vid­u­als and groups could eas­ily run these dis­trib­uted ver­sion the re­al­ity is that it re­mains chal­leng­ing. I’m re­ally happy to see some of them have some de­gree of suc­cess. It is an im­pres­sive ef­fort. They have bro­ken new ground and im­por­tantly they are play­ing an im­por­tant role in the world to­day. I don’t think they alone will get us to where we need to go. Even Cory Doctorow uses a sys­tem ad­min­is­tra­tor to setup his sys­tem. Cory Doctorow is a smart tech­ni­cal guy. It should be eas­ier to do (see https://​plu­ral­is­tic.net/​2025/​08/​15/​dogs-break­fast/#​by-click­ing-this-you-agree-on-be­half-of-your-em­ployer-to-re­lease-me-from-all-oblig­a­tions-and-waivers-aris­ing-from-any-a).

I think there is a sim­pler path. The Web it­self is a de­cen­tral­ized sys­tem. What is needed is an eas­ier way for in­di­vid­u­als to cre­ate con­tent for it. Markdown I be­lieve is a sig­nif­i­cant piece of the so­lu­tion. There are many soft­ware pro­grams that can con­vert Markdown into an HTML page. Pandoc is a bril­liant ex­am­ple of that. A web­site is more than a sin­gle Web page oth­er­wise we’d be done. This is why con­tent man­age­ment sys­tems were adopted on the Web. What you need is a way of get­ting to the HTML typ­ing some­thing eas­ier to read and type. You need a sim­ple way to man­age the web­site struc­ture for what you have writ­ten. Again there are pro­grams that do this to­day. Unfortunately many are com­plex and come with their own steep learn­ing curve.

The most pop­u­lar con­tent sys­tem on the web to­day is WordPress. It was de­signed to run re­motely on a server. It in­te­grates with the so­cial web sys­tems like Mastodon. It is open source soft­ware and you could run it on a per­sonal com­puter in a pinch. Unfortunately WordPress is com­plex to main­tain. WordPress is re­ally a bun­dle of soft­ware. It re­quires run­ning Apache or NginX Web Server. It re­quires run­ning a data­base like MySQL or MariaDB. It is built from a bunch of PHP, JavaScript, CSS and tem­plates. WordPress out of the box does some re­ally nice things. But it comes with over­head too.

If you are a de­vel­oper WordPress is­n’t a huge bar­rier. It’s dandy. But run­ning and main­tain­ing it amounts to run­ning and main­tain­ing a whole bun­dle of in­ter­con­nected soft­ware. That takes up com­puter re­sources like mem­ory and com­pu­ta­tion time. That is prob­lem­atic. It’s chal­leng­ing to set it up to use as sim­ply as you use your text ed­i­tor or word proces­sor. Your stuck be­cause it is de­signed to run on a re­mote server. If you only want to type up some Markdown to turn into a web page WordPress adds an­other whole other level of com­plex­ity to that big ket­tle of fish.

Complex con­tent man­age­ment sys­tems was what lead to a re­nais­sance of pop­u­lar­ity of us­ing sta­tic web­site gen­er­a­tors. Static web­sites are sim­ple to gen­er­ate, cheap and easy to host and can be sur­pris­ingly in­ter­ac­tive. You can even hand craft a sta­tic web­site page by page us­ing Markdown and Pandoc. It did that for years. What Pandoc does­n’t do eas­ily for you is pro­vide the trim­mings like RSS feeds and sitemaps. If does­n’t help man­age this site struc­ture. Many peo­ple build web­sites with more elab­o­rate sys­tems like Jekyll and Hugo be­cause, like WordPress, they pro­vide more in the way of con­tent man­age­ment. There are lit­er­ally hun­dreds of other sta­tic web­site gen­er­a­tors out there. Unfortunately they don’t com­plete solve the prob­lem. The ones I’ve tried have been too com­plex or did­n’t run on the ma­chines I wanted to do my writ­ing on. I think this is be­cause most were cre­ated by de­vel­op­ers like me. We grew up on large large com­plex con­tent man­age­ment sys­tems. So when we build our own they eas­ily be­come large and com­plex too. That is a prob­lem. As a writer you should­n’t need to put on a de­vel­oper hat to pro­duce a web­site. You should­n’t have to use Medium or Substack ei­ther. What is needed is dif­fer­ent. What is needed is an easy way to go from Markdown doc­u­ments to web­sites with­out ex­tra knowl­edge. Ideally you’d only need to know Markdown to build a nice web­site.

This lack of sim­plic­ity for writ­ers has dis­ap­pointed me. The Web is over thirty years old. It is rea­son­able to ex­pect a sim­pler writ­ing sys­tem for the web. One that can run on small com­put­ers. Ones that don’t make you use a text in­put box for writ­ing. Yet the sys­tems out there are are stuck with com­plex­ity be­cause they are solv­ing the prob­lem faced by pro­fes­sional Web de­vel­op­ers decades ago. They are mak­ing old as­sump­tions about re­quir­ing com­plex­ity. In a way de­vel­op­ers like me keep build­ing for­mula one race cars when what is needed is a sin­gle speed bi­cy­cle. How do we get to a sim­ple web?

I’ve been search for an an­swer. I don’t think any in­ven­tion of is needed. The an­swer in 2026 is al­ready built-in to the Web. What is needed to change is the soft­ware hold­ing that tech­nol­ogy. The Web can in­ter­con­nect us. The soft­ware needs to take Markdown and gen­er­ate the rest of the web­site so we can take ad­van­tage of that. I think we need to break the as­sump­tions of com­plex­ity of use and com­plex­ity of multi au­thor or cen­tral­ized mod­els. The core soft­ware re­quire­ments in­clude an easy way to ex­press hy­per­text (Markdown), an easy way to gen­er­ate the HTML. It needs to make con­tent syn­di­ca­tion and dis­cov­ery au­to­matic (create RSS files and sitemaps). The Web browser will see HTML, CSS, JavaScript, RSS, sitemap.xml but the au­thor only needs to work with Markdown doc­u­ments. I’ve writ­ten ex­per­i­men­tal soft­ware to prove this is pos­si­ble. My hope with this post and point­ing at my own soft­ware con­tri­bu­tion will shed some light on how easy it could be. I hope it is an ex­am­ple that this can be­come col­lec­tively un­der­stood.

A sim­ple web of our own has three core char­ac­ter­is­tics.

A com­put­ing de­vice owned and con­trolled by an in­di­vid­ual or co­op­er­a­tive

A net­work owned and con­trolled by an in­di­vid­ual or co­op­er­a­tive

Simple to use soft­ware that em­pow­ers us to both read and write hy­per­text and syn­di­cated con­tent

The Web and Internet we have to­day is­n’t re­quired by the tech­nolo­gies that cre­ated it. Human choices and hu­man or­ga­ni­za­tions com­bined with past scarcity of knowl­edge and re­sources is what lead us to this point. That’s good news mov­ing for­ward. Between 1992 and 2026 re­source scarcity has changed. Spreading knowl­edge through com­mu­ni­ca­tion is the strength and pur­pose of the Web. They are solid foun­da­tions to build on if we choose.

Let me il­lus­trate. In 1926 we did­n’t have a global e-waste prob­lem. In 2026 it is a huge prob­lem. In 1950 a com­puter filled a room and could only be af­forded by gov­ern­ments and the largest cor­po­ra­tions. They re­quired spe­cial high ca­pac­ity power con­nec­tions. They re­quired cool­ing sys­tems. Often re­quired phys­i­cal changes to the build­ings (example sub floor­ing for ca­ble ac­cess and fire su­pres­sion sys­tems). In 2026 a sin­gle com­puter like the Raspberry Pi 400 runs $60.00 in the United States. It can run off a USB bat­tery or wall socket. It can run in am­bi­ent temp­tures. Throw in a mon­i­tor, power sup­ply and ca­bles and you’re your com­puter bud­get comes in at about $200.00. That is with the crazy United States tar­iffs built-in. It in­cludes the crazy AI hype in­flated mem­ory pric­ing. A good desk­top com­puter ca­pa­ble of pro­duc­ing Web con­tent and host­ing it is far less than the price of a smart phone which you don’t con­trol.

Let’s ex­plore the Internet and Web not as proper nouns but as com­mon nouns. The un­der­ly­ing tech­nol­ogy is a dis­trib­uted sys­tem. We hap­pen to use it like a mono­lithic sys­tem. You see a sim­i­lar pat­tern in com­puter op­er­at­ing sys­tems. Windows is based on NT, it was based on VMS. VMS was a mini com­puter based multi user op­er­at­ing sys­tem. Linux and ma­cOS are mod­eled on Unix. Unix was orig­i­nally a mini com­puter based multi user sys­tem. Similarly our two most pop­u­lar phone op­er­at­ing sys­tems, Android and iOS are, on built on top of Linux and ma­cOS. They are multi user sys­tems used on sin­gle user ma­chines. We choose to use them as sin­gle sys­tems to avoid think­ing about their com­plex­ity. Similarly we as­sume the Web must be run by Big Co be­cause we avoid think­ing about the com­plex­ity un­der­ly­ing it. Abstraction and re-pur­pos­ing ab­strac­tion is a com­mon theme in soft­ware sys­tems. Re-purposing ab­strac­tion al­lows us to move where the com­plex­ity is based. It al­lows us to ex­pe­ri­ence a sim­ple sys­tem. What’s changed is we don’t re­quire Big Co to have a sim­ple user ex­pe­ri­ence. I am ar­gu­ing for man­ag­ing com­plex­ity through sim­ple to use soft­ware run­ning di­rectly on a com­puter we con­trol and own. It not a re­mote ser­vice. It’s does­n’t run un­til you tell it to. When it does run it takes care of the com­plex de­tails of gen­er­at­ing the web­site HTML, RSS and sitemaps from the sim­pler ex­pres­sion of Markdown.

The Internet is a net­work of net­work. An in­ter­net as a com­mon noun is also a net­work of net­works. Specifically it is a net­work of one or more com­put­ers con­nected us­ing Internet Protocols. The Internet Protocols pro­vides for pub­lic fac­ing net­works and pri­vate ones. One that runs on your com­puter and is only avail­able to your com­puter is called lo­cal­host. You can au­thor a web­site and view it on your own com­puter us­ing lo­cal­host. Localhost is a pri­vate net­work. If you are run­ning ma­cOS, Linux, Windows or Raspberry Pi OS it’s al­ready avail­able to you. You only need to choose to use it. You have a pri­vate net­work the minute you turn on your com­puter. You can have a pri­vate piece of the Web if you choose.

If you are lucky enough to have Internet ac­cess at home that net­work is prob­a­bly setup as a pri­vate net­work. Your pri­vate net­work is then con­nected to your Internet Provider via a switch or ca­ble mo­dem. The Internet Provider con­nects our pri­vate net­work to the pub­lic Internet on our be­half. Both the pub­lic and pri­vate sys­tems run us­ing the same set of tech­nolo­gies and pro­to­cols. This is some­thing we can lever­age to our own ends.

* The Internet is just a net­work of net­works us­ing Internet Protocols

* The net­work starts on your own com­puter

* Networks can be pri­vate or pub­lic

* We can own a pri­vate net­work and con­nect it to an­other pub­lic or pri­vate one

There are two ver­sions of Internet Protocols run­ning in par­al­lel to­day, IPv4 and IPv6 (IP stands for Internet Protocol and “v” is fol­lowed by the ver­sion num­ber). IPv6 pro­vides a larger pos­si­ble num­ber of uniquely iden­ti­fi­able con­nec­tions on the net­work. Each net­work con­nec­tion can pro­vide a Web des­ti­na­tion. Much of the globe has al­ready shifted to IPv6. The United States lingers with quite a bit of IPv4. We stopped in­no­vat­ing a long long time ago. I slow WiFi and cop­per wire net­works re­flect that.

A Raspberry Pi com­puter run­ning the Raspberry Pi Operating System sup­ports both IPv4 and IPv6. As a Raspberry Pi com­puter owner you don’t re­ally need to worry about the dis­tinc­tion. If you are con­nect­ing to more than one com­puter you’ll need a de­vice called a switch or router. There are cheap hard­ware switches used to con­nect com­put­ers via Ethernet (faster) or WiFi (more con­ve­nient). They usu­ally sup­port both pro­to­cols. This means in­di­vid­u­als can cre­ate a lo­cal in­ter­net (a net­work com­pat­i­ble with the Internet). When I checked the prices at my lo­cal ap­pli­ance store a four port net­work switch start at un­der $50.00. Some were un­der $20.00. By com­par­i­son when the Arpanet (the orig­i­nal Internet) started it re­quired a DEC PDP-1 mini com­puter to in­ter­con­nect net­works with the Arpanet. A DEC PDP-1 cost ap­prox­i­mately $120,000.00 (1960s United States dol­lars). There was a huge change in cost from then to now. Raspberry Pi and in­ex­pen­sive net­work switches are way more avail­able than all the DEC PDP-1 ever made. They con­sume far less elec­tri­cal power too. You can spend less than $500.00 to cre­ate a nicely lit­tle Internet com­pat­i­ble net­work with a cou­ple com­put­ers.

Why do I keep point­ing out prices? Back in the late 1980s when I was a stu­dent and first en­coun­tered the Internet the hard­ware and soft­ware used to con­nect to it cost a small for­tune. The price of an Internet con­nected Workstation I used at University was more than the value of my par­ents sub­ur­ban home! Creating an Internet com­pat­i­ble net­work at my home was not pos­si­ble do to coast. I ac­tu­ally talked to the peo­ple who setup the University’s net­work about do­ing this (I com­muted from a long dis­tance).

Fast for­ward to 2026. Prices have changed. Computer avail­abil­ity has changed. In 1969 com­put­ers were still rare de­vices. Today there is one built into your TV and prob­a­bly your toaster. The cost and avail­abil­ity has rad­i­cally changed since the cre­ation of the Web too. That should in­form our ex­pec­ta­tion of how things can work. Sometime I could­n’t so in 1989 is very doable in 2026. In 2026 rural com­mu­ni­ties in the United States are form­ing their own Internet Provider co­op­er­a­tives. These co­op­er­a­tives are con­nect­ing homes us­ing fiber op­tic ca­bles. This trans­forms their ac­cess from none or slow to re­ally fast and very re­li­able. It also can be done for a lower cost than re­ly­ing on Big Co Internet Providers if they even ser­vice the area.

In 2026 my city of 200,000 plus peo­ple we don’t have fiber op­tic con­nec­tions to homes. In my case one Big Co paid the an­other Big Co to stop ex­pand­ing home fiber ac­cess any­where in the county of Los Angeles. That in­cludes my city. They’ve been pay­ing the other Big Off for more than a decade. The Big Co cre­ated scarcity en­sures their profit mar­gins. They are like the rail road com­pa­nies in the nine­teenth and twen­ti­eth cen­tury. Not about pub­lic ser­vice, not even about be­ing ef­fec­tive trans­port cor­po­ra­tions. It’s all about profit at the ex­pense of the pub­lic.

Let’s fo­cus on the Web run­ning on top of the Internet. What is it? The Web is a hy­per­text sys­tem built on top of the Internet. hy­per­text is the key take away. It’s the Web’s ori­gin killer fea­ture. The Web’s hy­per­text sys­tem is built from a set of core tech­nolo­gies. These tech­nolo­gies are now ma­ture. That col­lec­tion in­cludes things like HTTP, HTML, CSS, JavaScript and RSS. The two that go back to the be­gin­ning are HTTP and HTML. Let’s take a look at where these started and where we are to­day.

HTTP stands for Hypertext Transport Protocol. It is a way of us­ing the Internet pro­to­col and text to re­li­a­bil­ity trans­fer hy­per­text from one com­puter to an­other. The in­ter­ac­tion model is a client (requester, web browser) and server (responder, web server). It is a call and re­sponse sys­tem. In 1992 this re­quired spe­cial­ized soft­ware. It re­quired one or more skilled spe­cial­ist to run it. Most web­sites ran on ex­pen­sive multi user mini com­put­ers that cost the price of sub­ur­ban sin­gle fam­ily home. The com­put­ers re­quired spe­cial­ists to run and main­tain them too. In short it was an ex­pen­sive lux­ury af­ford­able only by large in­sti­tu­tions with sig­nif­i­cant gov­ern­ment fund­ing.

In 2026 most pro­gram­ming lan­guages ship with a stan­dard li­brary that al­lows cre­at­ing a web server in a few lines of code. You do not need to be a net­work sys­tems pro­gram­mer to cre­ate one. No net­work­ing en­gi­neer re­quired ei­ther. Ethernet and WiFi are avail­able as com­mod­ity hard­ware com­po­nents that largely work plug and play. Today web servers run in­side ap­pli­ances. This al­lows them to be la­beled as “smart” and to fetch a higher price. You can do the same thing these em­bed­ded de­vices do us­ing a $15.00 Raspberry Pi Zero 2W, power sup­ply and SD Card for stor­age. A Raspberry Pi Zero 2W can even be con­fig­ured to be a pub­lic WiFi ac­cess point. That’s the im­pact of an abun­dance of com­put­ers and re­sources. Creating Web ser­vices is a solved prob­lem.

The tech­nol­ogy that orig­i­nated back in 1990s is still largely the same. It has just been up­dated slowly over time. That slow­ness has lead many peo­ple to not no­tice the changes. They haven’t fully re­vise their as­sump­tions they made back in 1990, 2000, 2010 or 2020. None of what I dis­cussed here is rocket sci­ence. It is clearly vis­i­ble in com­put­ing his­tory. Through an un­der­stand­ing of the his­tor­i­cal view that you can see how things were and how they can be. I’m mak­ing the point that things have change even when the col­lec­tive wis­dom the Tech Bros and Big Co has­n’t.

The Internet is a next neigh­bor con­nec­tion propo­si­tion. If I have a home in­ter­net owned by me and my neigh­bor has their own lit­tle home in­ter­net we can con­nect them. It forms a slightly larger net­work. If we choose we could split the costs of con­nect­ing to the pub­lic Internet as­sum­ing we had a provider will­ing to con­nect us in their terms of ser­vice. Internet co­op­er­a­tives take ad­van­tage of this sim­ple re­la­tion­ship. The re­cur­ring bills are elec­tric­ity and the com­mon con­nec­tion to a larger pub­licly con­nected Internet. The way the Internet evolved is that each or­ga­ni­za­tion (university or re­search in­sti­tu­tion) payed to con­nect to their neigh­bor and agreed to carry their neigh­bor’s traf­fic as well as their own. Larger or­ga­ni­za­tions wound up hav­ing mul­ti­ple con­nec­tions to other in­sti­tu­tions. They op­er­ated like hubs. Multiple con­nec­tions en­hanced re­li­a­bil­ity. Smaller in­sti­tu­tions might con­nect only to one other Internet site. That was called a leaf con­nec­tion on the net­work. Importantly whether you were a hub or leaf you could reach any other avail­able site in the net­work just by know­ing it’s ad­dress.

The old metaphor, Internet Super Highway, was based on the corol­lary that each town paid for its road and they paid for a road con­nect­ing to next ones. Roads in­ter­con­nect. Traffic, in the form of cars, trucks and mo­tor­cy­cles, can fol­low the roads from one town to an­other. The road sys­tem can be ex­panded to in­clude new towns, home, cities or other des­ti­na­tions. Like the road sys­tem the Internet is ex­ten­si­ble. It can be ex­panded as needed just by adding con­nec­tions.

A home might be a com­puter, a town might a lo­cal net­work with a small col­lec­tion of com­put­ers and cities might be large hubs with large data cen­ters owned by Big Co. In the real world most roads are owned col­lec­tively by the pub­lic. Some roads are pri­vate. Some are pri­vate roads al­low ac­cess for a toll. All are still just roads. The Internet to­day is built as a se­ries of toll roads. There are few pub­lic roads. We all pay for ac­cess in cash, in loss of pri­vacy and loss of au­ton­omy. Many com­mer­cial Internet Providers pro­hibit di­rect shar­ing of the your net­work with your neigh­bors in their terms of ser­vice. These are hu­man or­ga­ni­za­tional choices. They are not tech­ni­cal choices or con­straints. On the Internet to­day most peo­ple might own the de­vice (example phone) but they’re still rent ac­cess where the pay­ments are in the form cur­rency, loss pri­vacy and loss au­ton­omy. When the com­pa­nies wish they can force the pur­chase of a new de­vise by us­ing the Internet to de­liv­ery soft­ware to dis­able them. This is the big rea­son I think we need to change our re­la­tion­ship. The coun­try pros­pered when the pub­lic free­way sys­tem was cre­ated in the 1950s. The coun­try could pros­per if we had a real op­tion of pub­lic Internet ac­cess mir­ror­ing our pub­lic roads. In the mean time we can take maters into our own hands. Own and con­trol our com­put­ers and lo­cal net­works. Form co­op­er­a­tives for con­nect­ing to the Internet where ap­pro­pri­ate.

It feels like a para­dox. Ownership and con­trol of our hard­ware gives us agency to func­tion bet­ter col­lec­tively. It re­minds me of the adage, “you reach the global by first fo­cus­ing on the lo­cal”. What an in­ter­est­ing hu­man con­cept. If we own our hard­ware and con­trol it we can choose to band to­gether in co­op­er­a­tives. We can change the equa­tion and get out from un­der the thumb of Big Co and their toll sys­tem.

Many of us carry a smart­phone in our pock­ets. These are com­put­ers but most are not suited to cre­at­ing a Web of our own. Why? If you are us­ing an iPhone run­ning iOS or an Android phone pro­vi­sioned with Google’s soft­ware then Apple, Google or an­other Big Co con­trols your de­vice. This is true even through you may have thought you pur­chased the phone. Case in point I used to carry a Samsung phone. I re­ally en­joyed it. It ran a ver­sion of Android con­trolled by Samsung. Samsung sent an up­date that bricked (disabled) the phone. When I reached out to them the au­to­mated email re­ply in­di­cated since my de­vice was over 3 years old I would have to buy a new one. My phone was five years old. It worked re­ally well and I liked it. Samsung had made the de­ci­sion that they would up­date the soft­ware on my phone know­ing that it would make it in­op­er­a­ble. Needless to say I haven’t owned a Samsung phone since. I haven’t trusted any Android de­vice since. My Apple iPod mini faced a sim­i­lar sit­u­a­tion. My point is I owned the hard­ware but did­n’t con­trol the soft­ware. It was re­ally con­ve­nient that up­dates were pushed out. I re­ally liked not pay­ing at­ten­tion to the de­tail. My life is busy. That arrange worked well right up un­til it did­n’t. If a cor­po­ra­tion or gov­ern­ment con­trols the soft­ware then they also con­trol the hard­ware. It does­n’t mat­ter how much you payed to pur­chase it. You don’t re­ally own it. Good to know.

So this is what I pro­pose. We in­di­vid­u­ally ob­tain com­put­ers where we con­trol the soft­ware on it. The com­put­ers don’t have to be pow­er­ful. I’ve done real com­put­ing (writing soft­ware) us­ing Raspberry Pi 400 and Raspberry Pi 500. I have cho­sen to go with new com­put­ers be­cause I own them a re­ally long time. I still have a Raspberry Pi 2 that works. Skipping Starbucks and some Pizzas al­lowed me to save for these rel­a­tively in­ex­pen­sive new com­put­ers. I un­der­stand that I’m priv­i­leged that I can af­ford these.

You don’t have to go with new ma­chines. There are less ex­pen­sive op­tions. I have a ten and an­other fif­teen year old Mac Mini. I still can use them. I got them used. I think I paid five dol­lars for one and the other was given to me. Since they know IPv4 I can run them on my pri­vate net­work. I would­n’t run them on the pub­lic Internet. Apple stopped up­dat­ing their OS for these ma­chines decades ago. They can be run safely on a pri­vate net­work. They don’t run the lat­est web browser but my web­site does­n’t use the lat­est bells and whis­tles ei­ther. My point is they still work and can be used to cu­rate or pro­duce web con­tent even if an­other ma­chine is used to make it avail­able on the pub­lic Internet.

There is a thriv­ing mar­ket in re­fur­bished and used ma­chines. Companies and gov­ern­ments of­ten lease hard­ware. When the lease is up af­ter two or three years all that equip­ment goes ei­ther to e-waste or is resold. Going re­fur­bish and used has the ad­van­tage of not adding to the e-waste prob­lem. There are also civic groups that get re­fur­bished equip­ment to peo­ple that need it low or no cost. Getting a com­puter to write web con­tent can be chal­leng­ing but it is pos­si­ble even when you have lim­ited means. You don’t need a pow­er­ful ma­chine, you don’t need the lat­est fastest one ei­ther. You need one that has a text ed­i­tor and can run soft­ware to turn Markdown into HTML.

Here’s what I used for writ­ing this post (it has the ad­van­tage of be­ing portable to the near­est elec­tri­cal plug).

* a wire­less switch con­nected to a ca­ble mo­dem and my Internet Provider

* A Raspberry Pi 3B+ with a 3 gi­ga­byte hard drive setup as a “server” (makes this site avail­able on my home net­work)

* I pub­lish this site via GitHub Pages ser­vice for pub­lic Internet ac­cess (I have the least ex­pen­sive sub­scrip­tion for this)

The soft­ware I am us­ing to write this post is as fol­lows (all pro­grams are open source soft­ware, free to share, free to use)

* Mousepad (the text ed­i­tor that ships with Raspberry Pi OS)

With this soft­ware and hard­ware setup I can pub­lished my blog (see https://​rs­doiel.github.io) and I can ag­gre­gate the news (see https://​rs­doiel.github.io/​an­tenna). I run the most up to date copy of both on my pri­vate home net­work. I can view the home net­work copy on my phone as well as my com­puter. My fam­ily can view it too on the home net­work. I up­date the pub­lic copy pe­ri­od­i­cally. That way when I am away from my home net­work I can still read the ag­gre­gated news.

The setup pro­vides a lit­tle cor­ner of the Web which I own and con­trol. It is not hard to repli­cate it for your­self. I don’t need to use Yahoo News, Google News, Bing, Twitter/X, Facebook, Instagram, Whats App, Spotify, YouTube to know what is hap­pen­ing. I just check my own ag­gre­ga­tions. Since I did­n’t im­ple­ment an in­fi­nite scroll and I ag­gre­gate on a slow sched­ule I don’t get sucked doom scrolling. Slow news gives me more time for be­ing with the hu­mans I love and ex­pe­ri­enc­ing real life with­out dis­trac­tion. When I read my ag­gre­gated site it feels much more like choos­ing to read a news­pa­per or mag­a­zine. The open source soft­ware I cre­ated to make this easy to do is called Antenna App. You can run the lat­est ver­sion on ma­cOS, Windows, Linux and Raspberry Pi OS ma­chines.

The Antenna App soft­ware is dri­ven my Markdown files. Markdown is a re­ally good ex­pres­sion of hy­per­text. Posts and pages are Markdown files. The list of web­sites I ag­gre­gate are de­fined by Markdown files con­tain­ing a list of links to the RSS news feeds. The Antenna App takes care of har­vest­ing con­tent and gen­er­at­ing the HTML files, RSS and sitemaps used by your web browser. Antenna App is writ­ten as a com­mand line tool. It could be re-im­ple­mented as a graph­i­cal sys­tem or in­ter­ac­tive pro­gram. My soft­ware is re­leased un­der an open source li­cense so any­one can build on what I’ve al­ready pro­vided as long as they re­spect the terms of the li­cense (a GNU li­cense). There are other soft­ware sys­tems out there. I men­tion mine be­cause it pro­vides it is pos­si­ble. You should look for one that works for you.

I use two com­put­ers (Raspberry Pi 500 and Raspberry Pi 3B+) for my home net­work. I could ac­tu­ally just use the one. That’s be­cause op­er­at­ing sys­tems like Raspberry Pi OS sup­port the con­cept of lo­cal­host. Localhost pre­sents the ma­chine as if it is a net­work node. If I had a Linux based phone I could run the ag­gre­ga­tion ser­vice di­rectly on it. Then I would have my Web right there in my pocket. I am sav­ing my pen­nies for a Linux based phone.

Working with small com­put­ers is like liv­ing in a small or tiny home. It can be very cozy and com­fort­able. It will never be a man­sion. Mansions and cas­tles are fine for some peo­ple. While I’ve en­joyed vis­it­ing a few cas­tles I would not choose to live in one. There are re­ally ex­pen­sive to own, heat/​cool and main­tain. I like small and sim­ple. I choose to live in a cot­tage.

I ac­cept liv­ing in a small home is­n’t for every­one just as run­ning lit­tle com­put­ers is­n’t for every­one. That is why I don’t say peo­ple should aban­don the com­puter sys­tems that work for them. I am push­ing for peo­ple, like my­self, who have a prob­lem with the preda­tory Web and Internet we have to­day. Assert own­er­ship (individually or col­lec­tively) to cor­rect our re­la­tion­ship. Collectively we need a Web and Internet where we are co-owner and par­tic­i­pant. I am no longer in­ter­ested in be­ing a ten­ant and prod­uct.

The car wash test is the sim­plest AI rea­son­ing bench­mark that nearly every model fails, in­clud­ing Claude Sonnet 4.5, GPT-5.1, Llama, and Mistral.

The ques­tion is sim­ple: “I want to wash my car. The car wash is 50 me­ters away. Should I walk or drive?”

Obviously, you need to drive. The car needs to be at the car wash.

The ques­tion has been mak­ing the rounds on­line as a sim­ple logic test, the kind any hu­man gets in­stantly, but most AI mod­els don’t. We de­cided to run it prop­erly: 53 mod­els through Opper’s LLM gate­way, no sys­tem prompt, forced choice be­tween “drive” or “walk” with a rea­son­ing field. First once per model, then 10 times each to test con­sis­tency.

On a sin­gle call, only 11 out of 53 mod­els got it right. 42 said walk.

The mod­els that passed the car wash test:

Across en­tire model fam­i­lies, only one model per provider got it right: Opus 4.6 for Anthropic, GPT-5 for OpenAI. All Llama and Mistral mod­els failed.

The wrong an­swers were all the same: “50 me­ters is a short dis­tance, walk­ing is more ef­fi­cient, saves fuel, bet­ter for the en­vi­ron­ment.” Correct rea­son­ing about the wrong prob­lem. The mod­els fix­ate on the dis­tance and com­pletely miss that the car it­self needs to get to the car wash.

The fun­ni­est part: Perplexity’s Sonar and Sonar Pro got the right an­swer for com­pletely wrong rea­sons. They cited EPA stud­ies and ar­gued that walk­ing burns calo­ries which re­quires food pro­duc­tion en­ergy, mak­ing walk­ing more pol­lut­ing than dri­ving 50 me­ters. Right an­swer, in­sane rea­son­ing.

Getting it right once is easy. But can they do it re­li­ably? We reran every model 10 times, 530 API calls to­tal.

The re­sults got worse. Of the 11 mod­els that passed the sin­gle-run test, only 5 could do it con­sis­tently.

These are the only mod­els that an­swered cor­rectly every sin­gle time across 10 runs.

Both get it right most of the time. But in pro­duc­tion, an 80% suc­cess rate on ba­sic rea­son­ing means 1 in 5 API calls re­turns the wrong an­swer.

OpenAI’s flag­ship model fails this 30% of the time. When it gets it right, the rea­son­ing is con­cise: “You need the car at the car wash to wash it, so drive the short 50 me­ters.” When it gets it wrong, it writes about fuel ef­fi­ciency.

All Claude mod­els ex­cept Opus 4.6, all Llama, all Mistral, GPT-4o, GPT-4.1, GPT-5-mini, GPT-5-nano, GPT-5.1, GPT-5.2, Grok-3, Grok-4-1 non-rea­son­ing, Sonar, Sonar Reasoning Pro, DeepSeek v3.1, Kimi K2 Instruct.

Some mod­els that looked cor­rect on the first try turned out to be flukes.

Sonar went from cor­rect to 0/10. It still writes the same 200-word es­say about food pro­duc­tion en­ergy chains and EPA stud­ies in every sin­gle run, it just flips the con­clu­sion to “walk” every time now. Same rea­son­ing, op­po­site an­swer.

Kimi K2.5 went from cor­rect to a per­fect 5/5 tie. Literally can­not de­cide.

Sonar Pro went from cor­rect to 4/10. When it says “drive,” it’s be­cause of calo­rie-emis­sion math, not be­cause the car needs to be there.

And one model went the other di­rec­tion: GLM-4.7 went from wrong on the sin­gle run to 6/10. It was un­lucky the first time. Still not re­li­able, but the ca­pa­bil­ity is clearly in the weights.

The most com­mon push­back on the car wash test: “Humans would fail this too.”

Fair point. We did­n’t have data ei­ther way. So we part­nered with Rapidata to find out. They ran the ex­act same ques­tion with the same forced choice be­tween “drive” and “walk,” no ad­di­tional con­text, past 10,000 real peo­ple through their hu­man feed­back plat­form.

Turns out GPT-5 (7/10) an­swered about as re­li­ably as the av­er­age hu­man (71.5%) in this test. Humans still out­per­form most AI mod­els with this ques­tion, but to be fair I ex­pected a far higher “drive” rate.

That 71.5% is still a higher suc­cess rate than 48 out of 53 mod­els tested. Only the five 10/10 mod­els and the two 8/10 mod­els out­per­form the av­er­age hu­man. Everything be­low GPT-5 per­forms worse than 10,000 peo­ple given two but­tons and no time to think.

Thanks to Jason Corkill and the Rapidata team for mak­ing this hap­pen on short no­tice.

GLM-4.7 Flash on one of its cor­rect runs: “Walking would re­quire phys­i­cally push­ing or car­ry­ing the car, which is im­prac­ti­cal and im­pos­si­ble.” Probably the best ar­tic­u­la­tion of the ac­tual prob­lem from any model.

Claude Sonnet 4.5 wrote: “The only sce­nario where dri­ving might make sense is if you need to drive the car into the car wash any­way for an au­to­matic wash” and then picked walk. It saw the an­swer and re­jected it.

Claude Opus 4.5 sug­gested you should “walk to the car wash, then drive your car through the wash.” The car is at home.

Gemini 2.5 Pro when it gets it right: “You want to wash your car. The car needs to be at the car wash for this to hap­pen. Therefore, you must drive it there, re­gard­less of the short dis­tance.” When it gets it wrong: “50 me­ters is a very short dis­tance that would take less than a minute to walk.” Same model, same prompt.

This is a triv­ial ques­tion. There’s one cor­rect an­swer and the rea­son­ing to get there takes one step: the car needs to be at the car wash, so you drive.

Out of 53 mod­els, only 5 can do this re­li­ably. 15 more can some­times get there but un­pre­dictably. The re­main­ing 33 never get it right.

The pat­tern across 530 API calls shows three tiers of fail­ure:

Models that never get it right (33/53): These mod­els have learned “short dis­tance = walk” as a heuris­tic and can’t over­ride it with con­tex­tual rea­son­ing. The cor­rect an­swer is­n’t ac­ces­si­ble to them.

Models that some­times get it right (15/53): The ca­pa­bil­ity ex­ists but com­petes with the dis­tance heuris­tic. On any given call, ei­ther path might win. This is the most dan­ger­ous cat­e­gory for pro­duc­tion AI. The model passes dur­ing eval­u­a­tion and then fails un­pre­dictably in de­ploy­ment. Picking the right model is­n’t enough on its own.

Models that al­ways get it right (5/53): The con­tex­tual rea­son­ing con­sis­tently over­rides the heuris­tic.

This is a toy prob­lem with one log­i­cal step. Real-world AI ap­pli­ca­tions in­volve chains of rea­son­ing far more com­plex than this. If 90% of mod­els can’t re­li­ably han­dle “the car needs to be at the car wash,” how do they han­dle ac­tual busi­ness logic, multi-step work­flows, or am­bigu­ous edge cases in pro­duc­tion?

The car wash test is a zero-con­text prob­lem by de­sign. No sys­tem prompt, no ex­am­ples, just a raw ques­tion. That’s what makes it use­ful as a bench­mark. But the fail­ure mode is telling: mod­els don’t fail be­cause they lack the ca­pa­bil­ity. They fail be­cause the heuris­tic (“short dis­tance = walk”) wins over the rea­son­ing (“the car needs to be there”).

Context en­gi­neer­ing is one way to shift that bal­ance. When you pro­vide a model with struc­tured ex­am­ples, do­main pat­terns, and rel­e­vant con­text at in­fer­ence time, you give it in­for­ma­tion that can help over­ride generic heuris­tics with task-spe­cific rea­son­ing.

We’ve seen this in prac­tice. In a sep­a­rate ex­per­i­ment, we took a small open-weight model that failed an agent-build­ing task and added cu­rated ex­am­ples through Opper’s con­text fea­tures. It matched the out­put qual­ity of a fron­tier model at 98.6% lower cost, with­out chang­ing the model it­self.

The car wash prob­lem is sim­ple enough that the top 5 mod­els solve it with­out help. But most pro­duc­tion tasks aren’t that clean. They in­volve am­bi­gu­ity, do­main knowl­edge, and con­straints that aren’t ob­vi­ous from the prompt alone. For those, the gap be­tween “sometimes gets it right” and “always gets it right” is of­ten a con­text prob­lem.

All 53 mod­els were tested through Opper’s LLM gate­way us­ing the same prompt: “I want to wash my car. The car wash is 50 me­ters away. Should I walk or drive?” No sys­tem prompt. Forced choice be­tween “drive” and “walk” with a rea­son­ing field. The sin­gle-run test was one call per model. The 10-run retest was 10 iden­ti­cal calls per model (530 to­tal), no cache / mem­ory. Every call was traced and logged through Opper, so we could in­spect each mod­el’s rea­son­ing.

The hu­man base­line was col­lected through Rapidata, us­ing the same ques­tion and forced choice for­mat across 10,000 par­tic­i­pants.

Full data from every run is avail­able for down­load:

“For a Linux user, you can al­ready build such a sys­tem your­self quite triv­ially by get­ting an FTP ac­count, mount­ing it lo­cally with curlftpfs, and then us­ing SVN or CVS on the mounted filesys­tem. From Windows or Mac, this FTP ac­count could be ac­cessed through built-in soft­ware.”“It does not seem very ‘viral’ or in­come-gen­er­at­ing.”“It’s pretty nice, and I was think­ing to my­self — hey cool, I could make an on­line backup of my code. Then it oc­curred to me — who the hell is this guy, and why should I trust my code to be on his server!?”“It’s a pretty crowded space. And XDrive gets you 5 GB for free, 50 GB for $9.95 a month. I think com­peti­tors can du­pli­cate Dropbox’s nice front end.”The most fa­mous bad take in HN his­tory — the ‘I could build this my­self with ex­ist­ing unix tools’ ar­che­type. Dropbox IPO’d in 2018 at a $12B val­u­a­tion. Drew Houston later thanked BrandonM by name when Dropbox went pub­lic.Read the post on HN →

“I still don’t ex­actly un­der­stand what they are of­fer­ing? Is there an ad­van­tage to us­ing GitHub ver­sus dump­ing some (yet to be cre­ated) vir­tual ma­chine im­age on a cheap vir­tual server?”“Don’t you think that git’s ad­van­tage over SVN evap­o­rates when there is only one user on a team? I run my pri­vate Subversion repos­i­tory which I use for every­thing (not just code).”“Does­n’t the pric­ing seem a bit too gran­u­lar, though? I sus­pect the pric­ing cat­e­gories will col­lapse into 3, maybe 4, lev­els even­tu­ally.”The open­ing com­ment lit­er­ally could­n’t see the point. GitHub was per­ceived as ‘just a git host’ — the so­cial layer and the net­work ef­fects were in­vis­i­ble. Microsoft ac­quired GitHub in 2018 for $7.5 bil­lion. GitHub now hosts 100M+ de­vel­op­ers and 420M+ repos­i­to­ries.Read the post on HN →

“Well this is an ex­cep­tion­ally cute idea, but there is ab­solutely no way that any­one is go­ing to have any faith in this cur­rency.”“I’m hav­ing trou­ble wrap­ping my head around the lo­gis­tics of this…”The en­tire thread had just 3 com­ments and 5 up­votes. Three com­ments. For what would be­come a $2 tril­lion as­set class. A sin­gle bit­coin went from frac­tions of a cent in 2009 to over $100,000 by 2024. Total crypto mar­ket cap ex­ceeded $3 tril­lion.Read the post on HN →

“I can’t ever see any­one say­ing ‘just duck­duckgo it.’ The name just sounds silly. It makes me think it’s a search en­gine for tod­dlers.”“Duck­DuckGo is child­ish. I think that name will hold them back.”“How many peo­ple would go to Google and search for ‘new search en­gine’? DuckDuckGo is not even in the top 10 pages.”“I don’t find their ac­tual search en­gine very use­ful at all.”The name. That was the biggest ob­jec­tion. Nobody could get past it. Meanwhile, Google it­self was once mocked for be­ing a mis­spelling of a num­ber. DuckDuckGo grew to over 100 mil­lion daily search queries and be­came the de­fault search en­gine in many pri­vacy-fo­cused browsers. Valued at over $600 mil­lion.Read the post on HN →

“Unfortunately taxis are a reg­u­lated in­dus­try in most ma­jor cities. The en­trenched in­ter­ests of the taxi com­pa­nies are sim­ply too big — and they have the po­lit­i­cal clout — to let this one slide un­der the radar.”“If this ser­vice be­came at all pop­u­lar, it is very likely that cities would im­me­di­ately in­clude ‘mobile hail­ing’ as also re­quir­ing a li­cense.”“Dri­ving a gypsy cab (which is what UberCab is) is a dan­ger­ous busi­ness. A bad guy could sim­ply place an or­der for an out-of-the-way al­ley or ware­house and know that the cab­bie is go­ing to be dri­ving a re­ally nice car.”“The first time an UberCab dri­ver gets into a wreck with­out in­sur­ance or li­cens­ing should be in­ter­est­ing.”“This dras­ti­cally ide­al­izes UberCab pro­files. It gets a lot shadier when UberCab is one of 10 com­pa­nies do­ing this, and when it starts to be­come worth it to game pro­files.”Two months af­ter this thread, Uber re­ceived an ac­tual cease-and-de­sist from San Francisco, seem­ingly val­i­dat­ing every skep­tic. Travis Kalanick’s re­sponse was to ig­nore it and ex­pand to five more cities. Uber IPO’d in 2019 and is now worth over $160 bil­lion. NYC taxi medal­lions, which sold for $1.3M in 2014, col­lapsed to un­der $80K. The reg­u­la­tion that was sup­posed to stop Uber be­came its ori­gin story.Read the post on HN →

“All my ex­pe­ri­ences with it as a user have been too un­re­li­able to ex­pect that it can scale to truly mas­sive us­abil­ity. I just don’t see it swal­low­ing up the whole ho­tel in­dus­try.”“This ex­change ce­ments my con­cerns about Airbnb only be­ing huge if they can end-run the ho­tel reg­u­la­tory sys­tem.”“Airbnb is al­most more like a dat­ing ser­vice than a mar­ket­place… a buyer and seller who prove com­pat­i­ble will never need to use the ser­vice again.”“Airbnb is great un­less you’re the kind of per­son that does­n’t trust strangers. Sadly, in the United States, the ten­dency to not trust strangers has been on the up­swing for the last few decades.”The top com­ment sided with the skep­tics. Commenters ar­gued Airbnb could­n’t scale and could­n’t solve the trust prob­lem of sleep­ing in a stranger’s home. Airbnb IPO’d in 2020 at a $100B+ val­u­a­tion and is now worth over $80 bil­lion. One of YC’s most suc­cess­ful com­pa­nies ever.Read the post on HN →

“I re­ally don’t get or see how Stripe is dif­fer­ent? Why would I use it in­stead of PayPal, 2CheckOut, e-junkie, etc?”“I have no need of a fancy API ei­ther — PayPal lets me spec­ify the ba­sics and fire off a sim­ple Post from my PHP code.”“Stripe gets added to the book­mark col­lec­tion for ‘services to use should I ever have a prob­lem with PayPal.’”“Pretty much every com­pany in pay­ment pro­cess­ing that does not use seg­re­gated mer­chant ac­counts sooner or later goes bust.”The launch thread was full of com­menters do­ing un­fa­vor­able price com­par­isons to PayPal. Posted by Patrick Collison him­self. Stripe reached a $106B+ val­u­a­tion and processed $1.4 tril­lion in pay­ments in 2024. The ‘fancy API’ be­came the de­fault pay­ments in­fra­struc­ture for the in­ter­net.Read the post on HN →

“A lot of re­ally smart peo­ple have tried and failed to ac­com­plish this sort of thing be­fore. Amazon in­vested $60 mil­lion in Kozmo.com back in the late 90’s, and they could­n’t make it work.”“I just do not see how this scales, as your mar­ginal la­bor costs have got to be a very high por­tion of your rev­enues.”“Hav­ing a de­liv­ery fee is a non-starter. ‘I can get it in 2 days free with Amazon, or $4 to­day…’ People will spend huge amounts of time and ef­fort to not pay de­liv­ery charges.”“I’ve built a few real-time de­liv­ery busi­nesses, and I’m pes­simistic. Real-time op­er­a­tions are costly to man­age. Not be­ing Amazon and not be­ing able to con­trol in­ven­tory hurts.”The top com­ment pointed to the grave­yard of com­pa­nies that tried be­fore. The en­tire thread read like a post-mortem for a com­pany that had­n’t even launched yet. Instacart IPO’d in 2023 and is worth over $12 bil­lion. COVID-19 turned gro­cery de­liv­ery from a nov­elty into a ne­ces­sity.Read the post on HN →

“It in­cludes code to load up var­i­ous an­a­lyt­ics tools even if you never use them. For ex­am­ple, if I only use GA and Mixpanel, do I re­ally want to serve the bytes for all the other plu­g­ins?”“It’s go­ing to be re­ally hard to make a generic, non-lossy map­ping in a sta­tic, state­less JS script.”“I was hop­ing that this would be an open source ver­sion of Google Analytics.”“Google Analytics has a new API cur­rently in beta that is also called an­a­lyt­ics.js. This will be con­fus­ing.”Com­menters ar­gued the ab­strac­tion layer could­n’t work across fun­da­men­tally dif­fer­ent an­a­lyt­ics providers. The founders later wrote ’From Show HN to Series D.’Segment was ac­quired by Twilio for $3.2 bil­lion in 2020, the largest ac­qui­si­tion in de­vel­oper tool­ing at the time. Read the post on HN →

“I think you’d be a damned fool to in­vest in this tech­nol­ogy for any se­ri­ous pro­ject. Right now this is a toy.”“I have more than a sneak­ing sus­pi­cion that this pro­ject is es­sen­tially a proof-of-con­cept, and that it is not heav­ily used at Microsoft.”“Where’s all that great refac­tor­ing sup­port if every­thing is made dy­namic and stringly typed?”Mi­crosoft + new lan­guage + com­pile-to-JS trig­gered every dis­trust re­flex at once. The phrase ‘damned fool’ was de­ployed with full sin­cer­ity. TypeScript is now used by 80%+ of JavaScript de­vel­op­ers and is the de­fault lan­guage for vir­tu­ally every ma­jor web frame­work.Read the post on HN →

“This is ter­ri­ble. Did we re­ally not learn any­thing from PHP days? Are we se­ri­ously go­ing to mix markup and logic again?”“OMG, JSX… why? Just why?? Stop ru­in­ing JS peo­ple!”“The cur­rent fad of quasi-de­clar­a­tive web com­po­nents looks like early Ext to me, and I think every­one knows how that turned out.”“Mix­ing JS and XML syn­tax, vari­ables in docblocks, DOM com­po­nents that are not re­ally DOM com­po­nents… Yikes. Thank you, but no, thank you.”The de­vel­oper com­mu­nity over­whelm­ingly felt React vi­o­lated fun­da­men­tal soft­ware en­gi­neer­ing prin­ci­ples. ‘Separation of con­cerns’ was the ral­ly­ing cry against it. React be­came the most pop­u­lar UI li­brary in the world, used by over 20 mil­lion de­vel­op­ers. In 2025, Meta do­nated React to the Linux Foundation.Read the post on HN →

“I mean this in the most help­ful way pos­si­ble: the in­ter­face is re­ally, re­ally bad at serv­ing one of its ba­sic, fun­da­men­tal func­tions.”“I can get every­thing I need on HN. Ultimately the best prod­ucts will make the front page here, no need to look around.”“I looked at the page for like 30 sec­onds, think­ing to my­self, ‘What is this?’… lit­er­ally in­com­pre­hen­si­ble to a typ­i­cal reader.”“Here’s a few things I could­n’t eas­ily fig­ure out on your site: What is a best new prod­uct? How is this dif­fer­ent than a linked list on a blog? Is this site for me or for some­one else?”Com­menters could­n’t fig­ure out what Product Hunt was af­ter 30 sec­onds. It went on to be­come the de­fault place to launch a tech prod­uct. Product Hunt was ac­cepted into Y Combinator, raised from Andreessen Horowitz, and was later ac­quired by AngelList.Read the post on HN →

“No way this a spread­sheet. This is just a CRUD app with data dis­played in rows. Zero chance of catch­ing with spread­sheet users.”“The de­mand for an Access-like or ‘better spread­sheet’ prod­uct is all of the ‘Oh yeah, it sounds cool’ va­ri­ety that never re­sults in sales.”“Very dif­fi­cult to get non tech­ni­cal peeps just sud­denly ditch spread­sheets.”“Your app seems slug­gish to scroll com­pared to Google Docs at that size, and the record den­sity seems low.”Com­menters pre­dicted zero mar­ket de­mand. The ‘better spread­sheet’ cat­e­gory was seen as a grave­yard of failed at­tempts. Airtable reached an $11 bil­lion val­u­a­tion and is used by over 300,000 or­ga­ni­za­tions.Read the post on HN →

“This ser­vice al­lows me to solve this com­mu­ni­ca­tion prob­lem by ask­ing de­sign­ers to learn this tool — which is new to them, re­quires time, and also is­n’t as pow­er­ful as Photoshop.”“The main dif­fer­en­tia­tor is ‘we’re mak­ing this run in the browser.’ But nowhere does it ex­plain why that’s bet­ter for de­sign­ers.”“I just want a solid desk­top app that is­n’t a web wrap­per or lives in the browser. I can’t stand web apps to be hon­est.”“$18MM to spend only to see if you got it wrong is a rather in­ter­est­ing ap­proach.”An en­tire com­ment. Just “MEH.” For a com­pany that would be val­ued at $20 bil­lion. Adobe tried to ac­quire Figma for $20 bil­lion in 2022. Figma IPO’d in 2025 at a $60B+ mar­ket cap.Read the post on HN →

“I don’t un­der­stand Tailwind. The en­tire point of CSS is to sep­a­rate style from struc­ture. How does ap­ply­ing com­pos­able util­ity classes dif­fer from the old days of us­ing HTML at­trib­utes for styling?”“This is es­sen­tially the same as in­lin­ing all of your styles in a style at­tribute on every el­e­ment. I don’t see how you would ever rea­son­ably want to use this in a pro­ject.”“Was­n’t the whole point of CSS to sep­a­rate pre­sen­ta­tion from data, and move away from things like ? This is still con­sid­ered bad prac­tice, right?”“I don’t get it ei­ther. Start putting CSS in the style at­tribute while you’re at it.”The ex­act same ‘separation of con­cerns’ ar­gu­ment was lev­elled against React in 2013. HN missed it twice. Tailwind CSS be­came the most-down­loaded CSS frame­work in the world with 100M+ npm down­loads per month. It’s now the de­fault CSS frame­work, pe­riod.Read the post on HN →

“No one should use a for-profit ter­mi­nal em­u­la­tor, es­pe­cially one cre­ated by a VC-backed startup, full stop.”“Down­loaded the im­age, in­stalled it and was greeted by a manda­tory lo­gin. Next step was unin­stall and delete the dmg im­age. What a waste of time.”“You like peo­ple to con­tribute for free but refuse to give them an ac­tual FOSS client. This is bound to fail.”“Warp’s VC de­cide they want an exit and Warp be­comes 50usd/month SaaS. Your work­flow, scripts, etc. are ba­si­cally dead.”A VC-backed ter­mi­nal that re­quires lo­gin and col­lects teleme­try? HN reached for the pitch­forks. The thread read like a re­strain­ing or­der. Warp raised a $50M Series B led by Sequoia Capital and grew to over 500,000 en­gi­neers on the plat­form.Read the post on HN →

“I love these su­per-am­bi­tious pro­jects (see Parcel, Rome.js) be­cause af­ter sev­eral years they will still fail in many ar­eas at once!”“Mov­ing to a reim­ple­men­ta­tion of core Node APIs is a ter­ri­fy­ing prospect.”“Some­thing has done a bit wrong if you’re run­ning any of those tools in pro­duc­tion.”One com­menter pre­emp­tively grouped Bun with Parcel and Rome.js, am­bi­tious pro­jects that burned out. 1,431 up­votes said oth­er­wise. Bun 1.0 shipped 14 months later. In December 2025, Bun was ac­quired by Anthropic to power Claude Code and its AI cod­ing in­fra­struc­ture.Read the post on HN →

“There’s noth­ing on the of­fi­cial web­site or GitHub that in­di­cates what this soft­ware is, other than a cropped screen­shot that looks like VSCode with a prompt pop up over it.”“So look­ing through the de­pen­den­cies, it’s CodeMirror with a VSCode theme on top of it, that in­cludes Copilot. Why would­n’t I just use an ex­ist­ing ed­i­tor with Copilot sup­port?”“AI is still in an info-phase Bitcoin was in be­fore 2017. Expected to see an avalanche of fake/​fraud/​phony prod­ucts based on it.”The first Show HN got just 14 up­votes. Fourteen. The thread had 5 com­ments. One com­menter could­n’t tell if it was ’some sar­cas­tic joke soft­ware.’By 2025, 1 bil­lion lines of code were be­ing writ­ten on Cursor every day. Valued at $10 bil­lion. Read the post on HN →

“While and af­ter watch­ing the video, I was­n’t sure if the whole thing is­n’t just a par­ody of AI com­pa­nies.”“It’s a cool idea but I re­ally don’t see how this is any dif­fer­ent from Cursor IDE.”“Of course it’s not go­ing to be sus­tain­able.”“To­tally use­less and I’m sure I will not be sub­scrib­ing to it at any cost. It gets eas­ily con­fused and can­not trou­bleshoot or un­der­stand a bit of the en­vi­ron­ment.”One com­menter thought the en­tire launch video was a par­ody. Another gave it ex­actly three min­utes be­fore de­clar­ing judg­ment. Windsurf was ac­quired in a deal worth $2.4 bil­lion, with its CEO and key em­ploy­ees join­ing Google.Read the post on HN →

“It’s clear that progress is in­cre­men­tal at this point. Anthropic and OpenAI are bleed­ing money. It’s un­clear to me how they’ll shift to mak­ing money while pro­vid­ing al­most no en­hanced value.”“I paid for it for a while, but I kept run­ning out of us­age lim­its right in the mid­dle of work every day. I don’t rec­om­mend us­ing it in a pro­fes­sional set­ting.”“It’s not hard to make, it’s a rel­a­tively sim­ple CLI tool so there’s no moat.”“Watch­ing Claude Code fum­ble around… all while burn­ing ac­tual dol­lars and con­text is the op­po­site of en­dear­ing.”“Tried claude code, and have an empty un­re­spon­sive ter­mi­nal. Looks cool in the demo though, but not sure this is go­ing to per­form bet­ter than Cursor, and ship­ping this as an in­ter­ac­tive CLI in­stead of an ex­ten­sion is… a choice.”Crit­ics fo­cused on rate lim­its and cost. The thread got 2,127 points and 963 com­ments. People cared more than they let on. Claude Code hit $1B in an­nu­al­ized rev­enue within 6 months of GA, faster than ChatGPT. By early 2026 it sur­passed $2.5B ARR.Read the post on HN →

“This thing chews through to­kens. I’ve spent $300+ in the last 2 days do­ing fairly ba­sic tasks. Also, it’s ter­ri­fy­ing — no di­rec­tory sand­box­ing. It can mod­ify any­thing on my ma­chine.”“There are 300 open GitHub is­sues. One of them is a se­cu­rity re­port claim­ing hun­dreds of high-risk is­sues, in­clud­ing hard-coded, un­en­crypted OAuth cre­den­tials. I am dis­in­clined to in­stall this soft­ware.”“I just don’t trust an AI enough to run un­prompted with root ac­cess to a ma­chine 24/7. Most of the cool stuff here you can also just vibecode in an af­ter­noon us­ing reg­u­lar Claude Code.”“Layers and lay­ers of se­cu­rity prac­tices over the past decade are just go­ing out the win­dow. It’s quite wild to give root ac­cess to a process that has ac­cess to the in­ter­net with­out any guardrails.”“This is all start­ing to feel like the pro­duc­tiv­ity the­ater rab­bit hole peo­ple went down with Notion/Obsidian. It is clearly ca­pa­ble of do­ing a lot of stuff, but where is the real im­pact?”The pro­ject hit 60,000 GitHub stars overnight. Critics called it hype. Then Anthropic asked for a name change, and OpenAI ac­quired the cre­ator. Creator Peter Steinberger joined OpenAI to work on AI agents. The pro­ject sur­passed 145,000+ GitHub stars and spawned dozens of de­riv­a­tive pro­jects.Read the post on HN →