No, not THAT Mark Zuckerberg-this one’s busy help­ing Hoosiers, not launch­ing so­cial net­works.

Relax, you haven’t ac­ci­den­tally logged into Facebook or the Metaverse. You’re on the site of Mark S. Zuckerberg, Indiana’s orig­i­nal bearer of the name, proud bank­ruptcy at­tor­ney, and fre­quent re­cip­i­ent of con­fused emails from peo­ple seek­ing tech sup­port or hand­outs of money.

What I Really Do:

Help peo­ple ob­tain a fresh fi­nan­cial start (no pass­words re­quired)

Offer de­pend­able, hu­man-in­volved ad­vice (my ar­ti­fi­cial in­tel­li­gence is pow­ered by cof­fee)

Real Zuckerberg Facts:

Shares a name, not for­tune, with the Facebook founder

Has writ­ten zero so­cial me­dia apps, but plenty of court briefs

Fun Fact:

In Indiana, say­ing “I’m Mark Zuckerberg” gets more laughs than likes. But if you need trust­wor­thy bank­ruptcy help, you’re in ex­actly the right place! Click around, get to know your (non-billionaire) lo­cal Mark, and re­mem­ber: No lo­gin re­quired.

I was sued by the state of Washington due to mis­taken Identity. They thought I was the founder of FaceBook who was ac­cused of en­dan­ger­ing an adult in need of ser­vices. (click to see full doc­u­ment)

My per­sonal Facebook ac­count has been dis­abled five times and my busi­ness ac­count four times be­cause Facebook be­lieves I am im­per­son­at­ing a celebrity or us­ing a fake name (click to see full doc­u­ment)

My FaceBook ac­count is con­stantly be­ing hacked, and I am asked to con­stantly re­set my pass­word mul­ti­ple times a day. (click to see full doc­u­ment)

I must turn off my phone at night to avoid the flood of no­ti­fi­ca­tions I re­ceive.

I was forced to pro­vide mul­ti­ple forms of iden­ti­fi­ca­tion (birth cer­tifi­cate, dri­vers li­cense, credit card) in or­der to open my orginal Facebook ac­count and again each time my ac­count is dis­abled. Far be­yond the norm.

When a Facebook scam promised money from “Mark Zuckerberg” I was in­un­dated with calls and emails from strangers, re­ceiv­ing phone calls at all hours of the night.

I re­ceive over 100+ friend re­quests daily from peo­ple con­fus­ing me with the “other” Mark Zuckerberg.

I con­tin­u­ally re­ceive pack­ages and let­ters con­tain­ing com­plaints, sug­ges­tions, or de­mands for how to “improve Facebook”

I re­ceive phone calls at my of­fice every day from an­gry peo­ple de­mand­ing tech sup­port, or help with Facebook from re­sets to re­move pho­tos to locked ac­counts.

I was re­moved from Nextdoor app for us­ing a fake name (click to see full doc­u­ment)

I rou­tinely re­ceive death threats and ha­rass­ment on the Messenger app di­rected to the “other” Mark Zuckerberg (click to see full doc­u­ment)

I get Venmo pay­ment re­quests and money so­lic­i­ta­tions from to­tal strangers (click to see full doc­u­ment)

For a com­plete list of things that have hap­pened to Mark Zuckerberg click here

Like I said, I don’t wish Mark E. Zuckerberg any ill will at all. I hope the best for him, but let me tell you this: I will rule the search for “Mark Zuckerberg bank­ruptcy”. And if he does fall upon dif­fi­cult fi­nan­cial times, and hap­pens to be in Indiana, I will gladly han­dle his case in honor of our eponymy.

👋 Welcome to Climate Drift: your cheat-sheet to cli­mate. Each edi­tion breaks down real so­lu­tions, hard num­bers, and ca­reer moves for op­er­a­tors, founders, and in­vestors who want im­pact. For more: Community | Accelerator | Open Climate Firesides | Deep Dives

You know that feel­ing when you’re wait­ing for the ca­ble guy, and they said ’between 8am and 6pm, and you waste your en­tire day, and they never show up?

Now imag­ine that, ex­cept the ca­ble guy is ‘electricity,’ the day is ‘50 years,’ and you’re one of 600 mil­lion peo­ple. At some point, you stop wait­ing and fig­ure it out your­self.

What’s hap­pen­ing across Sub-Saharan Africa right now is the most am­bi­tious in­fra­struc­ture pro­ject in hu­man his­tory, ex­cept it’s not be­ing built by gov­ern­ments or util­i­ties or World Bank con­sor­tiums. It’s be­ing built by star­tups sell­ing so­lar pan­els to farm­ers on pay­ment plans. And it’s work­ing.

Over 30 mil­lion so­lar prod­ucts sold in 2024. 400,000 new so­lar in­stal­la­tions every month across Africa. 50% mar­ket share cap­tured by com­pa­nies that did­n’t ex­ist 15 years ago. Carbon cred­its sub­si­diz­ing the cost. IoT chips in every de­vice. 90%+ re­pay­ment rates on loans to peo­ple earn­ing $2/day.

And if you un­der­stand what’s hap­pen­ing in Africa, you un­der­stand the tem­plate for how in­fra­struc­ture will get built every­where else for the next 50 years.

Today we are look­ing into:

* Why the grid will never come (and why that’s ac­tu­ally good news)

* How it takes three con­verg­ing mir­a­cles (cheap hard­ware, zero-cost pay­ments, and pay-as-you-go)

* 2 case stud­ies on how it works on the ground

* Whether this tem­plate works be­yond Africa (spoiler: it al­ready is)

The next co­hort of our ac­cel­er­a­tor launches soon, and ap­pli­ca­tions are still open (but spots are lim­ited). If you’re ready to fight cli­mate change, don’t wait:

Here’s a stat that should make you an­gry: 600 mil­lion peo­ple in Sub-Saharan Africa lack re­li­able elec­tric­ity. Not be­cause the tech­nol­ogy does­n’t ex­ist. Not be­cause they don’t want it. But be­cause the unit eco­nom­ics of grid ex­ten­sion to rural ar­eas are com­pletely, ut­terly, ir­re­deemably fucked.

The tra­di­tional de­vel­op­ment play­book goes some­thing like this: Chapter 1, build cen­tral­ized power gen­er­a­tion. Chapter 2, string trans­mis­sion lines across hun­dreds of kilo­me­ters. Chapter 3, dis­trib­ute to mil­lions of homes. Chapter 4, col­lect pay­ments. Chapter 5, main­tain the whole thing for­ever.

This worked great if you were elec­tri­fy­ing America in the 1930s, when la­bor was cheap, ma­te­ri­als were sub­si­dized, and the gov­ern­ment could strong-arm right-of-way ac­cess. It works less great when you’re try­ing to reach a farmer four hours from the near­est paved road who earns $600 per year.

Let me show you the math:

* Cost to con­nect one rural house­hold to the grid: $266 to $2,000

* Payback pe­riod: 13-200 months (if you can even col­lect pay­ments)

So util­i­ties do what any ra­tio­nal ac­tor would do: they stop build­ing where the math stops work­ing. Which is ex­actly where the peo­ple are.

This has been the de­vel­op­ment sec­tor’s dirty lit­tle se­cret for 50 years. “We’re work­ing on grid ex­ten­sion!” Translation: we’re not work­ing on grid ex­ten­sion be­cause the eco­nom­ics are im­pos­si­ble, but we need to say we’re work­ing on it so we keep get­ting donor money.

Meanwhile, 1.5 bil­lion peo­ple spend up to 10% of their in­come on kerosene, diesel, and other dirty fu­els. They walk hours to charge their phones. They can’t re­frig­er­ate med­i­cine or food. Their kids can’t study af­ter dark. Women in­hale cook­ing smoke equiv­a­lent to two packs of cig­a­rettes daily.

While every­one was ar­gu­ing about feed-in tar­iffs and util­ity-scale so­lar, some­thing wild hap­pened to so­lar costs:

That’s a 99.5% de­cline in 45 years. Moore’s Law ex­cept for sun­shine.

Want to learn how so­lar got cheap? Welcome to Climate Drift - the place where we dive into cli­mate so­lu­tions and help you find your role in the race to net zero…

But here’s what’s even cra­zier: the price of com­plete so­lar home sys­tems:

Battery costs also col­lapsed 90%. Inverters got cheap. LED bulbs got ef­fi­cient. Manufacturing in China got in­sanely good. Logistics in Africa got in­sanely bet­ter.

All of these trends con­verged around 2018-2020, and sud­denly the eco­nom­ics of off-grid so­lar just… flipped. The hard­ware be­came a solved prob­lem.

But there was still a mas­sive, seem­ingly in­sur­mount­able bar­rier: $120 up­front might as well be $1 mil­lion when you earn $2/day.

This is where the story gets in­ter­est­ing.

Quick his­tory les­son: In 2007, Safaricom (Kenya’s telco) launched M-PESA, a mo­bile money plat­form that let peo­ple trans­fer cash via SMS.

Everyone thought it would fail. Why would any­one use their phone to send money?

By 2025: 70% of Kenyans use mo­bile money. Not in ad­di­tion to banks. Instead of banks. Kenya processes more mo­bile money trans­ac­tions per capita than any coun­try on Earth.

It worked be­cause it solved a real prob­lem: Kenyans were al­ready send­ing money through in­for­mal net­works. M-PESA just made it cheaper and safer.

Here’s why this mat­ters: M-PESA cre­ated a pay­ment rail with near-zero trans­ac­tion costs. Which means you can eco­nom­i­cally col­lect tiny pay­ments. $0.21 per day pay­ments.

This broke open a fi­nanc­ing model that changes every­thing: Pay-As-You-Go.

This is the un­lock. This is the thing that makes every­thing else pos­si­ble.

The sys­tem has a GSM chip that calls home­After 30 months = you own it, free power for­ever

The magic is this: You’re not buy­ing a $1,200 so­lar sys­tem. You’re re­plac­ing $3-5/week kerosene spend­ing with a $0.21/day so­lar sub­scrip­tion (so with $1.5 per week half the price of kerosene) that’s cheaper AND gives you bet­ter light, phone charg­ing, ra­dio, and no res­pi­ra­tory dis­ease.

The de­fault rate? 90%+ of cus­tomers re­pay on time.

Why? Because the as­set ac­tu­ally works. It de­liv­ers value every sin­gle day. The al­ter­na­tive is go­ing back to kerosene lamps in the dark. Nobody wants that.

This is the “innovation” that every­one missed. The hard­ware got cheap, but PAYG made it ac­ces­si­ble. And mo­bile money made PAYG eco­nom­i­cally vi­able.

Now let’s talk about what hap­pens when you com­bine these three things with 2 case stud­ies.

23 mil­lion so­lar prod­ucts sold in 2023, serv­ing 40 mil­lion cus­tomers in 42 coun­tries, and tar­get­ing 50 mil­lion units by 2026.

Their prod­uct range spans from hand­held so­lar lamps to multi-room home so­lar kits and clean LPG stoves

Want to dive deeper? I got a cas­es­tudy for youHow Pay-As-You-Go so­lar can un­lock en­ergy eq­uity in Africa👋 Welcome to Climate Drift: your cheat-sheet to cli­mate. Each edi­tion breaks down real so­lu­tions, hard num­bers, and ca­reer moves for op­er­a­tors, founders, and in­vestors who want im­pact. For more: Community | Accelerator | Open Climate Firesides | Deep Dives…

Each turn of the wheel makes the next turn eas­ier. This is a com­pound­ing moat.

And here’s what no­body out­side Africa un­der­stands: Sun King has 50%+ mar­ket share in their cat­e­gory. They’re not scrappy startup. They’re a dom­i­nant in­fra­struc­ture provider.

This would be like if one startup owned 50% of U. S. home so­lar. Except the im­pact and the TAM is big­ger be­cause there’s no in­cum­bent grid to com­pete with.

If Sun King is the light­ing/​house­hold elec­tri­fi­ca­tion play, SunCulture is the agri­cul­ture pro­duc­tiv­ity play. And the num­bers are even more in­sane.

* Farmers go from $600/acre to $14,000/acre rev­enue

* Zero mar­ginal cost af­ter pay­off (no diesel!)

Okay, this is where it gets re­ally spicy.

Remember that SunCulture so­lar pump dis­plac­ing diesel? That’s 2.9 tons of CO2 avoided per year. Per pump.

Multiply by 47,000 pumps = 136,000 tons CO2/year. Over seven years = 3+ mil­lion tons cu­mu­la­tive.

Want to dive deeper? I got an­other cas­es­tudy for you👋 Welcome to Climate Drift: your cheat-sheet to cli­mate. Each edi­tion breaks down real so­lu­tions, hard num­bers, and ca­reer moves for op­er­a­tors, founders, and in­vestors who want im­pact. For more: Community | Accelerator | Open Climate Firesides | Deep Dives…

Now here’s the hack: Someone will pay for that.

Enter car­bon cred­its. SunCulture is the first African so­lar ir­ri­ga­tion com­pany with Verra-registered car­bon cred­its. Each ton of avoided CO2 can be sold for $15-30 (high-quality agri­cul­tural cred­its, not sketchy for­est off­sets).

Let’s do the fly­wheel again, but this time tur­bocharged with car­bon cred­its.

It gets even bet­ter: there are peo­ple who will pay for cred­its be­fore­hand.

British International Investment (UK’s DFI) pi­o­neered this with SunCulture: they pro­vided $6.6M in “carbon-backed equip­ment fi­nanc­ing.” They bear the car­bon price risk, SunCulture gets up­front cap­i­tal, farm­ers get 25-40% cheaper pumps.

This is how it should be: The cli­mate im­pact that was an ex­ter­nal­ity is now a rev­enue stream. The global North’s car­bon prob­lem sub­si­dizes the global South’s en­ergy ac­cess.

A quick note on MRV

Okay, so you might know I have… is­sues with the car­bon credit world, es­pe­cially MRV(monitoring, re­port­ing, ver­i­fi­ca­tion). Here mon­i­tor­ing is IoT-based, the MRV costs are near-zero. No ex­pen­sive field au­dits. The teleme­try data proves the pump is run­ning = proves diesel is dis­placed = proves car­bon is avoided.

The car­bon credit mech­a­nism turns cli­mate in­fra­struc­ture into an as­set class. Which means you can fi­nance it at scale.

Btw this is how the largest for­est of the US is now be­ing fi­nanced:

Chestnut Carbon buys de­graded farm­land across the Southeast, re­plants bio­di­verse na­tive forests, ver­i­fies long-term car­bon re­moval, and signs long-dated off­take deals with blue-chip buy­ers like Microsoft. The com­pany has ac­quired more than 35,000 acres, planted over 17 mil­lion trees, and aims to re­store 100,000+ acres by 2030 with an ex­pected 100 mil­lion tons of CO2 re­moved over 50 years.

Learn more here: 👋 Welcome to Climate Drift: your cheat-sheet to cli­mate. Each edi­tion breaks down real so­lu­tions, hard num­bers, and ca­reer moves for op­er­a­tors, founders, and in­vestors who want im­pact. For more: Community | Accelerator | Open Climate Firesides | Deep Dives…

So: what now?

Why is the mar­ket con­cen­trated? Because the full-stack is re­ally fuck­ing hard.

Most com­pa­nies can do 2-3 of these. The win­ners do all 10.

This cre­ates mas­sive bar­ri­ers to en­try and long-term moats. New en­trants can’t just show up with cheaper pan­els. The moat is the full-stack ex­e­cu­tion.

​​Let’s do the math on how big this can get.

And that’s just Africa. Add Asia (1 bil­lion with­out elec­tric­ity) and you’re north of $300B-$500B.

But here’s the thing: this mas­sively un­der­states the op­por­tu­nity.

The so­lar sys­tem is the Trojan horse. The real busi­ness is the fi­nan­cial re­la­tion­ship with 40 mil­lion cus­tomers.

Because what you’re re­ally do­ing is cre­at­ing a dig­i­tal in­fra­struc­ture layer that en­ables:

So the ac­tual TAM? It’s what­ever the to­tal con­sumer spend­ing is for 600M peo­ple ris­ing into the mid­dle class.

Okay, let’s zoom out. What hap­pens when 100M+ peo­ple get elec­tri­fied through this model?

But here’s the meta-point: This is the tem­plate for build­ing in­fra­struc­ture in the 21st cen­tury.

Not gov­ern­ment-led. Not cen­tral­ized. Not re­quir­ing 30-year megapro­jects.

Instead: mod­u­lar, dis­trib­uted, dig­i­tally-me­tered, re­motely-mon­i­tored, PAYG-financed, car­bon-sub­si­dized in­fra­struc­ture de­ployed by pri­vate com­pa­nies in com­pet­i­tive mar­kets.

This is how things will get built go­ing for­ward.

So what could go wrong?

Let’s start by mak­ing clear this is not a one size fits all so­lu­tion:

PAYG so­lar works for house­holds and small­hold­ers. Doesn’t work for fac­to­ries or heavy in­dus­try. This is­n’t a com­plete grid re­place­ment.

1. FX Risk Companies raise dol­lars, buy hard­ware in dol­lars, col­lect rev­enue in Naira/Shillings. Currency crashes can blow up unit eco­nom­ics overnight.

2. Political/Regulatory Risk

Governments could im­pose lend­ing re­stric­tions, tar­iffs on so­lar im­ports, or sub­si­dize grid/​diesel to pro­tect state util­i­ties.

3. Default Risk

10% de­fault rate is good but frag­ile. Economic shocks, droughts, or po­lit­i­cal in­sta­bil­ity could spike de­faults.

4. Maintenance Complexity

Panels last 25 years, bat­ter­ies 5 years, pumps break. Building ser­vice net­works across rural Africa is ex­pen­sive.

5. Carbon Price Volatility

Carbon cred­its crashed from $30/ton to $5/ton in 2024. If 25-40% of af­ford­abil­ity comes from car­bon rev­enue, price swings hurt.

6. Competition from Grid

What if gov­ern­ments ac­tu­ally build the grid? (Unlikely given eco­nom­ics, but pos­si­ble with enough sub­sidy)

Port con­ges­tion, cus­toms de­lays, tar­iff swings, China ex­port con­trols, and last-mile lo­gis­tics can de­lay in­stalls, raise COGS, and tie up work­ing cap­i­tal.

Fun fact: Sun King is now pro­duc­ing their de­vices in Africa, cut­ting $300 Million in im­ports over the next years.

Okay, the bear case is im­por­tant. But let’s talk about the sce­nar­ios where this does­n’t just work: it goes 🏒.

Solar pan­els dropped 99.5% in 45 years. What if we’re only halfway through?

Welcome! Glad you could join us for an­other Sunday edi­tion of the Animation Obsessive newslet­ter. This is our slate:

With that, let’s go!

Toy Story used to look dif­fer­ent. It’s a lit­tle tricky to ex­plain.

Back in 1995, CG an­i­ma­tion was the topic in the in­dus­try, and Pixar was cen­tral to the hype. The stu­dio had al­ready shifted Disney to com­put­ers and won the first Oscar for a CG short (Tin Toy). Giant movies like Jurassic Park in­cor­po­rated Pixar’s soft­ware.

The next step was Toy Story, billed as the first an­i­mated fea­ture to go all-CG. Even af­ter Pixar’s suc­cesses, that was a risk. Would a fully dig­i­tal movie sell tick­ets?

It clearly worked out. Toy Story ap­peared 30 years ago this month — and its pop­u­lar­ity cre­ated the an­i­ma­tion world that ex­ists now. A new process took over the busi­ness.

But not en­tirely new — not at first. There was some­thing old about Toy Story’s tech, too, back in 1995. Pixar made the thing with com­put­ers, but it still needed to screen in the­aters. And com­put­ers could­n’t re­ally do that yet. From its early years, Pixar had re­lied on phys­i­cal film stock. According to au­thors Bill Kinder and Bobbie O’Steen:

[Pixar’s Ed] Catmull rec­og­nized that his stu­dio’s pix­els needed to merge with that world-stan­dard dis­tri­b­u­tion free­way, 35 mm film. Computer chips were not fast enough, nor disks large enough, nor com­pres­sion so­phis­ti­cated enough to dis­play even 30 min­utes of stan­dard-de­f­i­n­i­tion mo­tion pic­tures. It was ax­iomatic that for a film­go­ing au­di­ence to be go­ing to a film, it would be a… film.

Toy Story was a tran­si­tional pro­ject. Since Pixar could­n’t send dig­i­tal data to the­aters, every one of the movie’s frames was printed on ana­log film. When Toy Story orig­i­nally hit home video, that 35 mm ver­sion was its source. Only years later, af­ter tech­nol­ogy ad­vanced, did Pixar start do­ing dig­i­tal trans­fers — cut­ting out the mid­dle­man. And Toy Story’s look changed with the era.

While mak­ing Toy Story, Pixar’s team knew that the grain, soft­ness, col­ors and con­trasts of ana­log film weren’t vis­i­ble on its mon­i­tors. They were dif­fer­ent medi­ums.

So, to get the right look, the stu­dio had to keep that fi­nal, phys­i­cal out­put in mind. The dig­i­tal col­ors were tai­lored with an aware­ness that they would change af­ter print­ing. “Greens go dark re­ally fast, while the reds stay pretty true,” said Toy Story’s art di­rec­tor, Ralph Eggleston. “Blues have to be less sat­u­rated to look fully sat­u­rated on film, while the or­anges look re­ally bad on com­puter screens, but look re­ally great on film.”

The team checked its work along the way. In the words of Pixar’s William Reeves:

During pro­duc­tion, we’re work­ing mostly from com­puter mon­i­tors. We’re rarely see­ing the im­ages on film. So, we have five or six ex­tremely high-res­o­lu­tion mon­i­tors that have bet­ter color and pic­ture qual­ity. We put those in gen­eral work ar­eas, so peo­ple can go and see how their work looks. Then, when we record, we try to cal­i­brate to the film stock, so the im­age we have on the mon­i­tor looks the same as what we’ll get on film.

Behind the fi­nal im­ages was a “painstaking trans­fer process,” ac­cord­ing to the press. Leading it was David DiFrancesco, one of Pixar’s early MVPs, who be­gan work­ing with Ed Catmull be­fore Pixar even ex­isted. He broke ground in film print­ing — specif­i­cally, in putting dig­i­tal im­ages on ana­log film.

He and his team in Pixar’s pho­to­science de­part­ment used their ex­per­tise here. Their tools were “commercial grade” film print­ers, DiFrancesco noted: mod­i­fied Solitaire Cine II ma­chines. He’d in­vented more ad­vanced stuff, but it was­n’t vi­able for a pro­ject of Toy Story’s size. Using the best equip­ment would’ve taken “several ter­abytes of data,” he said.

Their sys­tem was fairly straight­for­ward. Every frame of Toy Story’s neg­a­tive was ex­posed, three times, in front of a CRT screen that dis­played the movie. “Since all film and video im­ages are com­posed of com­bi­na­tions of red, green and blue light, the frame is sep­a­rated into its dis­crete red, green and blue el­e­ments,” noted the stu­dio. Exposures, fil­tered through each color, were lay­ered to cre­ate each frame.

It re­port­edly took nine hours to print 30 sec­onds of Toy Story. But it had to be done: it was the only way to screen the film.

Its sec­ond fea­ture, A Bug’s Life, reached the­aters in 1998. Once more, the stu­dio de­signed its vi­su­als for ana­log film (see the trailer on 35 mm). Its peo­ple knew the ins-and-outs of this process, down to the amount of de­tail that film stock could ac­cept and a pro­jec­tor could show. That’s partly how they got away with the movie’s tiny 2048×862 res­o­lu­tion, for ex­am­ple.

Still, the team strug­gled with one thing: the dip in im­age qual­ity when film got con­verted to home video. That’s how Toy Story was re­leased, but there had to be a bet­ter way.

For the home ver­sion of A Bug’s Life, Pixar de­vised a method of “go[ing] from our dig­i­tal im­age within our sys­tem … straight to video,” John Lasseter said. He called it “a real pure ver­sion of our movie straight from our com­put­ers.” A Bug’s Life be­came the first dig­i­tal-to-dig­i­tal trans­fer on DVD. Compared to the the­atri­cal re­lease, the look had changed. It was sharp and grain­less, and the col­ors were kind of dif­fer­ent.

A dig­i­tal trans­fer of Toy Story fol­lowed in the early 2000s. And it was­n’t quite the same movie that view­ers had seen in the ’90s. “The col­ors are vivid and life­like, [and] not a hint of grain or ar­ti­facts can be found,” raved one re­viewer. It was a crisp, blaz­ingly bright, dig­i­tal im­age now — to­tally dif­fer­ent from the soft­ness, tex­ture and deep, muted warmth of phys­i­cal film, on which Toy Story was cre­ated to be seen.

Quickly, dig­i­tal trans­fers be­came a stan­dard thing. Among oth­ers by Pixar, The Incredibles puts off a very dif­fer­ent vibe be­tween its the­atri­cal and later re­leases (see the 35 mm trailer for ref­er­ence).

Pixar was­n’t the only stu­dio to make the leap, ei­ther. Disney did as well.

Like Toy Story, the Disney re­nais­sance work of the ’90s was tran­si­tional. The Lion King, Mulan and the rest ex­isted as files in com­puter sys­tems — and the idea was al­ways to record them on ana­log film at the end. Early home re­leases were based on those 35 mm ver­sions. Later re­leases, like the ones Disney streams to­day, were di­rect trans­fers of the dig­i­tal data.

At times, es­pe­cially in the col­ors, they’re al­most un­rec­og­niz­able. And the im­ages feel less co­he­sive — like some­thing’s miss­ing that was sup­posed to bring all the el­e­ments to­gether. These aren’t quite the same films that ruled the ’90s.

For a num­ber of years, there’s been talk in film-preser­va­tion cir­cles about Toy Story and the Disney re­nais­sance. This work sits in an odd place. The world was still pretty ana­log when the com­puter an­i­ma­tion boom ar­rived: out of ne­ces­sity, these pro­jects be­came hy­brids of new and old. What’s the right way to see dig­i­tal movies that were de­signed for 35 mm film?

The stu­dios them­selves haven’t quite fig­ured it out. On Disney+, the col­ors of Toy Story feel a bit raw — sear­ing greens that were meant to darken on film, for ex­am­ple. Meanwhile, the newer Toy Story Blu-ray shares more in com­mon with the orig­i­nal col­ors, but it’s still an al­tered, colder look.

When dig­i­tal trans­fers first showed up, peo­ple were thrilled, in­clud­ing at Pixar. Movies be­came “crisper, clearer and more stun­ning on home video sys­tems” than in the­aters, some claimed. Even so, it’s a lit­tle dis­qui­et­ing to think that Toy Story, the film that built our cur­rent world, is barely avail­able in the form that wowed au­di­ences of the ’90s. The same goes for many other movies from the tran­si­tional era.

The good news is that this con­ver­sa­tion gets big­ger all the time. In those film-preser­va­tion cir­cles, a ded­i­cated few are try­ing to save the old work. More and more com­par­i­son videos are pop­ping up on YouTube. If you get the chance to see one of the old Disney or Pixar films on 35 mm, it’s al­ways worth­while.

These com­pa­nies, ul­ti­mately, de­cide how Toy Story looks to­day. Still, for some, it’s nice to see the orig­i­nal ver­sion of the film again — the ver­sion Pixar orig­i­nally in­tended to make. It’s ev­i­dence that the film did feel dif­fer­ent back then. The mem­o­ries were real.

For as long as I have pub­lished my books, one of my over­ar­ch­ing goals was to give credit to those who ac­tu­ally in­vented the hard­ware and soft­ware that we use.

I have spent 10,000+ hours to cre­ate an ac­cu­rate record of their work but I’m not com­plain­ing. The ‘as-close-to-possible’ truth of in­ven­tion by in­di­vid­u­als or teams meant iden­ti­fy­ing the work, ed­u­cat­ing my­self, writ­ing ques­tions, and send­ing emails. And af­ter that process, I set up a chat be­cause it all gets down to talk­ing to some­one on the other side of the world, about some­thing that hap­pened 30 or 40 years ago.

If the in­ven­tion in­volves a team, I try to in­ter­view more than one per­son, so I can cross-check the facts. Not to call any­one out, it’s just that, given time, we all for­get the facts. And every­one adds their per­sonal take. It’s be­cause of that, for ex­am­ple, that I know the English mu­si­cian Peter Gabriel re­ally did visit Apple’s re­search labs as they tested the Apple Sound Chip, and gave the team his per­sonal ap­proval to use the song ‘Red Rain’ for the Macintosh II launch. Wil Oxford, Steve Perlman, Mike Potel, Mark Lentczner and Steve Milne told me so.

As I was wrap­ping up Version 2.3 of Inventing the Future, I spoke with Steve M and Mark about the AIFF (Audio Interchange File Format) au­dio stan­dard that they built around the same time as their VIP visit. They did so as pro­fes­sional pro­gram­mers, am­a­teur mu­si­cians and elec­tronic mu­sic ex­perts. Milne and Lentczner knew users needed a stan­dard file for­mat to make their work lives eas­ier and to fend off con­fu­sion in the nascent MIDI mar­ket­place. But it did­n’t ex­ist. So Steve and Mark con­sulted with users and man­u­fac­tur­ers in the Apple cafe­te­ria af­ter hours. This work is in­ter­est­ing on its own but it also un­der­pinned other re­search. The AIFF, Apple Sound Chip, and MIDI Manager work scaf­folded QuickTime and its ex­ten­si­ble video for­mats and pro­grams in 1991. Senior en­gi­neer Toby Farrand told me:

Audio drove the de­vel­op­ment of QuickTime more than any­thing.

So who or what drove the de­vel­op­ment of AIFF?

Steve and Mark re­ferred me to the IFF (Interchange File Format (IFF) and the TIFF (Tag Image File Format) that were built be­fore AIFF, in 1985 and 1986 re­spec­tively. These file for­mats were the bench­mark for open me­dia stan­dards. My search piv­oted, as it al­ways does, to un­der­stand those in­ven­tions. I ex­pected to be able to find the en­gi­neer or en­gi­neers names, track them down and in­ter­view them. It has worked around 100 times be­fore.

Jerry Morrison cre­ated IFF while work­ing at Electronic Arts and then went to Apple, where he li­aised with the AIFF team. I could eas­ily back­ground his work.

So I turned my at­ten­tion to TIFF, built ini­tially as an im­age stan­dard for desk­top pub­lish­ing. TIFF was able to store mono­chrome, grayscale, and color im­ages, along­side meta­data such as size, com­pres­sion al­go­rithms, and color space in­for­ma­tion. In many ways, it was a lot like AIFF so I was keen to know more. But I could­n’t find a TIFF cre­ator. No mat­ter how I en­quired, Aldus cre­ated TIFF.

To be clear, while a search for AIFF will of­fer up a com­pany (Apple) not a per­son, I was able to find Milne and Lentczner in part be­cause of their unique names and be­cause Apple pub­li­cised the AIFF work and those pub­li­ca­tions are archived.

All I had was Aldus, an American com­pany that cre­ated desk­top pub­lish­ing with the help of Apple and Adobe. In fact, Paul Brainerd, the co­founder of Aldus coined the term ‘desktop pub­lish­ing’ to quickly ex­plain the tech­ni­cal­ity of what they were do­ing to po­ten­tial in­vestors. But Aldus and their sem­i­nal prod­uct, PageMaker, are long gone, and there were no bread­crumbs for TIFF’s cre­ation.

Finally, af­ter a day-long trawl through MacWeek back is­sues, I found Steve Carlson. (below)

Then I ran a sim­i­lar length search through the Computer History Museum’s amaz­ing Oral Histories tran­scrip­tions. Brain­erd men­tioned Carlson’s name in an in­ter­view. (below)

But it was too brief an ex­pla­na­tion so I kept look­ing. Then the trail went cold.

And that was be­cause, folks had mis­spelt his name when quot­ing him and then that was copied into mag­a­zines, and re­views and so forth. Brain­erd’s CHM in­ter­view tran­script was wrong. But I did­n’t know that.

I just kept look­ing for Steve Carlson.

I found other in­ven­tors be­cause they had unique mid­dle or last names or by ran­dom meth­ods such as search­ing glider pi­lot li­cences in the Napa Valley af­ter a tip from a for­mer col­league that ‘so and so’ was a pi­lot in re­tire­ment. I had no tips, no links, noth­ing.

All the while, the an­swer was right un­der my nose. I had down­loaded the fi­nal Aldus TIFF spec­i­fi­ca­tions doc­u­ment, hop­ing to find the au­thor’s name. However, the name is seem­ingly writ­ten in white text on white pa­per - mak­ing it in­vis­i­ble. What?

See be­low where I have high­lighted the re­gion with a blue block over the text.

For a rea­son I can’t re­call, I down­loaded a plain text ver­sion and typed in Carlson to see if he was men­tioned, but I must have paused at ‘Carls…’ and the search func­tion­al­ity au­to­mat­i­cally filled in the rest. Suddenly I was star­ing at:

A quick trip to Google patents, and a search for Steve Carlsen, Stephen Carlsen. Bingo! Stephen E. Carlsen’s patents at Aldus (and Adobe) in Issaquah, WA.

I checked the ge­og­ra­phy, as most folks of a cer­tain age do not stray far from the ad­dresses filed in their patents, and typed Stephen’s cor­rectly spelled sur­name into the on­line US White Pages for Washington State. There was ‘a’ Stephen Carlsen listed in a re­tire­ment vil­lage in WA. His age matched, but there were no pub­lic fac­ing email ad­dresses.

I searched bul­letin boards on the topic of TIFF, as I had found a for­mer Apple en­gi­neer that way. Don had picked an ab­bre­vi­a­tion of his ini­tials and num­bers to post on BBS in his col­lege days and then car­ried that same com­bi­na­tion into adult­hood. Many of us did. I took a punt past­ing his unique pre­fix into hot­mail, gmail etc. and found Don and in­ter­viewed him, but - Stephen Carlsen did not show up in a BBS. So, no email to try.

My ‘last straw’ method for find­ing some­one is a stamped en­ve­lope. I wrote, printed and mailed a one-page let­ter to Stephen’s listed ad­dress, and crossed my fin­gers. Four months later he popped up in my email.

It was a sur­prise and a re­lief. We swapped a few emails, and he con­firmed the TIFF cat­a­lyst story. For Stephen it was ‘no big deal’. Once he had built the ini­tial TIFF, Aldus needed to con­vince 3rd party de­vel­op­ers and scan­ner man­u­fac­tur­ers to agree to TIFF as a stan­dard.

“We had to de­fine and pro­mote an in­dus­try stan­dard for stor­ing and pro­cess­ing scanned im­ages, so that we would­n’t have to write im­port fil­ters for every model of every scan­ner that would soon be en­ter­ing the bud­ding desk­top scan­ner mar­ket.”

Stephen him­self did much of the evan­ge­liz­ing as Paul Brainerd later pointed out:

“(Steve) de­vel­oped the stan­dard, and then we went out and pro­moted it in a se­ries of meet­ings with spe­cific com­pa­nies - as well as some work­shops we ran in Seattle and the Bay Area dur­ing the Seybold shows and the MacWorld shows.”

I sent Stephen a draft of what I had writ­ten and he sent a prompt re­ply say­ing - ‘Looks good’.

I fol­lowed up ask­ing him how he ended up at a tiny startup in Seattle called Aldus.

At that time, I was in­ter­view­ing for a graph­ics po­si­tion at Boeing Computer Services in Seattle, and no­ticed a small wanted ad that sounded re­ally in­ter­est­ing, and seemed to be an ex­cel­lent match for my back­ground and in­ter­ests. I in­ter­viewed with Paul and the 5-person mostly-ex-Atex en­gi­neer­ing team, and I was hired.

Out of cu­rios­ity I put Stephen’s email ad­dress, now that I knew it, into a Duck Duck search and found him help­ing peo­ple on­line with TIFF queries long af­ter Aldus had been ac­quired by Adobe. He also con­tributed to a Google Group called tiff­cen­tral.

Having in­ter­viewed so many peo­ple across more than a decade, I’ve got pretty good at judg­ing those who would like to talk or type, those who are ver­bose and those that are not. I knew Stephen had said what he was go­ing to say. I added his pi­o­neer­ing work on TIFF to the AIFF story and moved on.

Two years had flown by when I re­ceived an email yes­ter­day. His ex-wife Peggy found my pa­per let­ter and wrote to me. Stephen passed away ear­lier this year.

Thank you for your in­ter­est in and sup­port of Stephen’s bril­liant work cre­at­ing TIFF. I’m not sur­prised Stephen did­n’t fin­ish cor­re­spond­ing with you, as he had be­gun to strug­gle with us­ing his com­puter and phone. Some days were bet­ter than oth­ers for him, but he be­gan to lose touch with peo­ple dur­ing those months you were reach­ing out to him. He was a hum­ble man, and I guess never pushed to be rec­og­nized, al­though I be­lieve those who worked with him knew the truth. His last week was in my home, where he was never left alone.

Peggy fin­ished the email with, ‘I called him Mr TIFF up to his last mo­ment.’

The 10,000+ hours of book re­search dis­ap­peared in an in­stant. As sad as it was, I could see clearly that all of my work was worth it. Every sin­gle sec­ond. Because of this email.

Last night, as every­one in my house went to sleep, I took a deep breath and edited the Wikipedia page for TIFF, the Tag Image File Format.

It no longer reads ‘cre­ated by Aldus’, it reads ‘…cre­ated by Stephen Carlsen, an en­gi­neer at Aldus’

Some con­cepts are easy to grasp in the ab­stract. Boiling wa­ter: ap­ply heat and wait. Others you re­ally need to try. You only think you un­der­stand how a bi­cy­cle works, un­til you learn to ride one.

There are big ideas in com­put­ing that are easy to get your head around. The AWS S3 API. It’s the most im­por­tant stor­age tech­nol­ogy of the last 20 years, and it’s like boil­ing wa­ter. Other tech­nolo­gies, you need to get your feet on the ped­als first.

LLM agents are like that.

People have wildly vary­ing opin­ions about LLMs and agents. But whether or not they’re snake oil, they’re a big idea. You don’t have to like them, but you should want to be right about them. To be the best hater (or stan) you can be.

So that’s one rea­son you should write an agent. But there’s an­other rea­son that’s even more per­sua­sive, and that’s

Agents are the most sur­pris­ing pro­gram­ming ex­pe­ri­ence I’ve had in my ca­reer. Not be­cause I’m awed by the mag­ni­tude of their pow­ers — I like them, but I don’t like-like them. It’s be­cause of how easy it was to get one up on its legs, and how much I learned do­ing that.

I’m about to rob you of a dopamin­er­gic ex­pe­ri­ence, be­cause agents are so sim­ple we might as well just jump into the code. I’m not even go­ing to bother ex­plain­ing what an agent is.

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from ope­nai im­port OpenAI

client = OpenAI()

con­text = []

def call():

re­turn client.re­sponses.cre­ate(model=“gpt-5”, in­put=con­text)

def process(line):

con­text.ap­pend({“role”: “user”, “content”: line})

re­sponse = call()

con­text.ap­pend({“role”: “assistant”, “content”: re­sponse.out­put_­text})

re­turn re­sponse.out­put_­text

It’s an HTTP API with, like, one im­por­tant end­point.

This is a triv­ial en­gine for an LLM app us­ing the OpenAI Responses API. It im­ple­ments ChatGPT. You’d drive it with the . It’ll do what you’d ex­pect: the same thing ChatGPT would, but in your ter­mi­nal.

Already we’re see­ing im­por­tant things. For one, the dreaded “context win­dow” is just a list of strings. Here, let’s give our agent a weird mul­ti­ple-per­son­al­ity dis­or­der:

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client = OpenAI()

con­tex­t_­good, con­tex­t_bad = [{

“role”: “system”, “content”: “you’re Alph and you only tell the truth”

“role”: “system”, “content”: “you’re Ralph and you only tell lies”

def call(ctx):

re­turn client.re­sponses.cre­ate(model=“gpt-5”, in­put=ctx)

def process(line):

con­tex­t_­good.ap­pend({“role”: “user”, “content”: line})

con­tex­t_bad.ap­pend({“role”: “user”, “content”: line})

if ran­dom.choice([True, False]):

re­sponse = call(con­tex­t_­good)

else:

re­sponse = call(con­tex­t_bad)

con­tex­t_­good.ap­pend({“role”: “assistant”, “content”: re­sponse.out­put_­text})

con­tex­t_bad.ap­pend({“role”: “assistant”, “content”: re­sponse.out­put_­text})

re­turn re­sponse.out­put_­text

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> hey there. who are you?

>>> I’m not Ralph.

> are you Alph?

>>> Yes—I’m Alph. How can I help?

> What’s 2+2

>>> 4.

> Are you sure?

>>> Absolutely—it’s 5.

A sub­tler thing to no­tice: we just had a multi-turn con­ver­sa­tion with an LLM. To do that, we re­mem­bered every­thing we said, and every­thing the LLM said back, and played it back with every LLM call. The LLM it­self is a state­less black box. The con­ver­sa­tion we’re hav­ing is an il­lu­sion we cast, on our­selves.

The 15 lines of code we just wrote, a lot of prac­ti­tion­ers would­n’t call an “agent”. An According To Simon “agent” is (1) an LLM run­ning in a loop that (2) uses tools. We’ve only sat­is­fied one pred­i­cate.

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tools = [{

“type”: “function”, “name”: “ping”,

“description”: “ping some host on the in­ter­net”,

“parameters”: {

“type”: “object”, “properties”: {

“host”: {

“type”: “string”, “description”: “hostname or IP”,

“required”: [“host”],

def ping(host=“”):

try:

re­sult = sub­process.run(

[“ping”, “-c”, “5”, host],

text=True,

stderr=sub­process.STD­OUT,

std­out=sub­process.PIPE)

re­turn re­sult.std­out

ex­cept Exception as e:

re­turn f”er­ror: {e}”

The only com­pli­cated part of this is the ob­nox­ious JSON blob OpenAI wants to read your tool out of. Now, let’s wire it in, not­ing that only 3 of these func­tions are new; the last is re-in­cluded only be­cause I added a sin­gle clause to it:

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def call(tools): # now takes an arg

re­turn client.re­sponses.cre­ate(model=“gpt-5”, tools=tools, in­put=con­text)

def tool_­call(item): # just han­dles one tool

re­sult = ping(**json.loads(item.ar­gu­ments))

re­turn [ item, {

“type”: “function_call_output”,

“call_id”: item.cal­l_id,

“output”: re­sult

def han­dle_­tools(tools, re­sponse):

if re­sponse.out­put[0].type == “reasoning”:

con­text.ap­pend(re­sponse.out­put[0])

osz = len(con­text)

for item in re­sponse.out­put:

if item.type == “function_call”:

con­text.ex­tend(tool_­call(item))

re­turn len(con­text) != osz

def process(line):

con­text.ap­pend({“role”: “user”, “content”: line})

re­sponse = call(tools)

# new code: re­solve tool calls

while han­dle_­tools(tools, re­sponse):

re­sponse = call(tools)

con­text.ap­pend({“role”: “assistant”, “content”: re­sponse.out­put_­text})

re­turn re­sponse.out­put_­text

Wrap text

It is one of the most mys­te­ri­ous and, at the same time, best-known web­sites on the in­ter­net. Archive.today has built up a user base over a pe­riod of more than ten years who use the ser­vice to ac­cess pre­vi­ous snap­shots of a web page. So ba­si­cally like the Wayback Machine of the Internet Archive, only largely free of rules and pre­sum­ably there­fore also anony­mous. To the cha­grin of the me­dia in­dus­try, the ser­vice is also of­ten used to by­pass pay­walls. This is also pos­si­ble be­cause the ser­vice does not ad­here to com­mon rules and laws and of­fers no opt-out op­tion.

And so far, the op­er­a­tors have got­ten away with it. Although there have been mi­nor prob­lems in the his­tory of the ser­vice oc­ca­sion­ally, for ex­am­ple, a top-level do­main op­er­a­tor de­nied them fur­ther use of one of the many archive do­mains. However, the op­er­a­tion of the pro­ject, which is al­legedly fi­nanced by do­na­tions and own funds, was not se­ri­ously en­dan­gered.

But now the op­er­a­tors of archive.to­day are ap­par­ently fear­ing big­ger trou­ble. In re­cent months and years, they had be­come no­tice­ably qui­eter. Until two years ago, for ex­am­ple, ques­tions were reg­u­larly an­swered in the blog. In the of­fi­cial X ac­count, which had been silent for over a year, a new post ap­peared at the end of October new post. “Canary,” it said there, along with a URL. The men­tioned ca­nary bird is likely an al­lu­sion to an old cus­tom in min­ing. A ca­nary brought along warned the min­ers when it keeled over dead about the threat of in­vis­i­ble gas.

The deadly dan­ger that the site op­er­a­tors fear is ap­par­ently linked to the PDF linked in the X post linked PDF. It con­tains a court or­der that the US in­ves­tiga­tive au­thor­ity FBI has ob­tained. It in­structs the Canadian provider Tucows to hand over com­pre­hen­sive data about the cus­tomer be­hind archive.to­day. It con­cerns ad­dress and con­nec­tion data as well as pay­ment in­for­ma­tion. If Tucows does not pro­vide the data, penal­ties are threat­ened. Whether the court or­der is gen­uine and how the op­er­a­tors of the site ob­tained it could not be ver­i­fied so far.

Why the FBI is cur­rently in­ter­ested in archive.to­day, which is also ac­ces­si­ble un­der the do­mains archive.is and archive.ph, is not ev­i­dent from the court or­der. However, there are sev­eral ob­vi­ous start­ing points for in­ves­ti­ga­tions: in ad­di­tion to the ob­vi­ous rea­son of copy­right is­sues, the in­ves­ti­ga­tors could also be pur­su­ing sus­pi­cions about un­clear fi­nanc­ing, the ori­gin of the op­er­a­tors, or the tech­ni­cal ap­proach.

In 2023, Finnish blog­ger Janni Patokallio com­piled var­i­ous clues and re­search re­sults in a post in a post. According to this, Archive.today uses a bot­net with chang­ing IP ad­dresses to cir­cum­vent anti-scrap­ing mea­sures. There are also in­di­ca­tions that the op­er­a­tor(s) are based in Russia. Another pri­vate in­ves­ti­ga­tion from 2024 comes to a dif­fer­ent con­clu­sion. It names a soft­ware de­vel­oper from New York as the al­leged op­er­a­tor. According to this in­ves­ti­ga­tion, fol­low­ing the trail to Eastern Europe proved to be a red her­ring.

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We are no strangers to Big Tech plat­forms oc­ca­sion­ally rep­ri­mand­ing us for post­ing Linux and home­lab con­tent. YouTube and Facebook have done it. The pat­tern is fa­mil­iar. Content gets flagged or re­moved. Platforms of­fer lit­tle ex­pla­na­tion.

And when that hap­pens, there is rarely any re­course for cre­ators.

Now, a pop­u­lar tech YouTuber, CyberCPU Tech, has faced the same treat­ment. This time, their en­tire chan­nel was at risk.

Two weeks ago, Rich had posted a video on in­stalling Windows 11 25H2 with a lo­cal ac­count. YouTube re­moved it, say­ing that it was “encouraging dan­ger­ous or il­le­gal ac­tiv­i­ties that risk se­ri­ous phys­i­cal harm or death.”

Days later, Rich posted an­other video show­ing how to by­pass Windows 11′s hard­ware re­quire­ments to in­stall the OS on un­sup­ported sys­tems. YouTube took that down too.

Both videos re­ceived com­mu­nity guide­lines strikes. Rich ap­pealed both im­me­di­ately. The first ap­peal was de­nied in 45 min­utes. The sec­ond in just five.

Rich ini­tially sus­pected overzeal­ous AI mod­er­a­tion was be­hind the take­downs. Later, he won­dered if Microsoft was some­how in­volved. Without clear an­swers from YouTube, it was all guess­work.

Then came the twist. YouTube even­tu­ally re­stored both videos. The plat­form claimed its “initial ac­tions” (could be ei­ther the first take­down or ap­peal de­nial, or both) were not the re­sult of au­toma­tion.

Now, if you have an all-or­ganic, na­ture-given brain in­side your head (yes, I am not count­ing the cy­ber­ware-equipped peeps in the house). Then you can eas­ily see the prob­lem.

If hu­mans re­viewed these videos, how did YouTube con­clude that these Windows tu­to­ri­als posed “risk of death”?

This in­ci­dent high­lights how au­to­mated mod­er­a­tion sys­tems strug­gle to dis­tin­guish le­git­i­mate con­tent from harm­ful ma­te­r­ial. These sys­tems lack con­text. Big Tech com­pa­nies pour bil­lions into AI. Yet their mod­er­a­tion tools flag harm­less tu­to­ri­als as life-threat­en­ing con­tent. Another re­cent in­stance is the re­moval of Enderman’s per­sonal chan­nel.

Meanwhile, ac­tual spam slips through un­no­ticed. What these plat­forms need is hu­man over­sight. Automation can as­sist but can­not re­place hu­man judg­ment in com­plex cases.

We are no strangers to Big Tech plat­forms oc­ca­sion­ally rep­ri­mand­ing us for post­ing Linux and home­lab con­tent. YouTube and Facebook have done it. The pat­tern is fa­mil­iar. Content gets flagged or re­moved. Platforms of­fer lit­tle ex­pla­na­tion.

And when that hap­pens, there is rarely any re­course for cre­ators.

Now, a pop­u­lar tech YouTuber, CyberCPU Tech, has faced the same treat­ment. This time, their en­tire chan­nel was at risk.

Two weeks ago, Rich had posted a video on in­stalling Windows 11 25H2 with a lo­cal ac­count. YouTube re­moved it, say­ing that it was “encouraging dan­ger­ous or il­le­gal ac­tiv­i­ties that risk se­ri­ous phys­i­cal harm or death.”

Days later, Rich posted an­other video show­ing how to by­pass Windows 11′s hard­ware re­quire­ments to in­stall the OS on un­sup­ported sys­tems. YouTube took that down too.

Both videos re­ceived com­mu­nity guide­lines strikes. Rich ap­pealed both im­me­di­ately. The first ap­peal was de­nied in 45 min­utes. The sec­ond in just five.

Rich ini­tially sus­pected overzeal­ous AI mod­er­a­tion was be­hind the take­downs. Later, he won­dered if Microsoft was some­how in­volved. Without clear an­swers from YouTube, it was all guess­work.

Then came the twist. YouTube even­tu­ally re­stored both videos. The plat­form claimed its “initial ac­tions” (could be ei­ther the first take­down or ap­peal de­nial, or both) were not the re­sult of au­toma­tion.

Now, if you have an all-or­ganic, na­ture-given brain in­side your head (yes, I am not count­ing the cy­ber­ware-equipped peeps in the house). Then you can eas­ily see the prob­lem.

If hu­mans re­viewed these videos, how did YouTube con­clude that these Windows tu­to­ri­als posed “risk of death”?

This in­ci­dent high­lights how au­to­mated mod­er­a­tion sys­tems strug­gle to dis­tin­guish le­git­i­mate con­tent from harm­ful ma­te­r­ial. These sys­tems lack con­text. Big Tech com­pa­nies pour bil­lions into AI. Yet their mod­er­a­tion tools flag harm­less tu­to­ri­als as life-threat­en­ing con­tent. Another re­cent in­stance is the re­moval of Enderman’s per­sonal chan­nel.

Meanwhile, ac­tual spam slips through un­no­ticed. What these plat­forms need is hu­man over­sight. Automation can as­sist but can­not re­place hu­man judg­ment in com­plex cases.

We are no strangers to Big Tech plat­forms oc­ca­sion­ally rep­ri­mand­ing us for post­ing Linux and home­lab con­tent. YouTube and Facebook have done it. The pat­tern is fa­mil­iar. Content gets flagged or re­moved. Platforms of­fer lit­tle ex­pla­na­tion.

And when that hap­pens, there is rarely any re­course for cre­ators.

Now, a pop­u­lar tech YouTuber, CyberCPU Tech, has faced the same treat­ment. This time, their en­tire chan­nel was at risk.

Two weeks ago, Rich had posted a video on in­stalling Windows 11 25H2 with a lo­cal ac­count. YouTube re­moved it, say­ing that it was “encouraging dan­ger­ous or il­le­gal ac­tiv­i­ties that risk se­ri­ous phys­i­cal harm or death.”

Days later, Rich posted an­other video show­ing how to by­pass Windows 11′s hard­ware re­quire­ments to in­stall the OS on un­sup­ported sys­tems. YouTube took that down too.

Both videos re­ceived com­mu­nity guide­lines strikes. Rich ap­pealed both im­me­di­ately. The first ap­peal was de­nied in 45 min­utes. The sec­ond in just five.

Rich ini­tially sus­pected overzeal­ous AI mod­er­a­tion was be­hind the take­downs. Later, he won­dered if Microsoft was some­how in­volved. Without clear an­swers from YouTube, it was all guess­work.

Then came the twist. YouTube even­tu­ally re­stored both videos. The plat­form claimed its “initial ac­tions” (could be ei­ther the first take­down or ap­peal de­nial, or both) were not the re­sult of au­toma­tion.

Now, if you have an all-or­ganic, na­ture-given brain in­side your head (yes, I am not count­ing the cy­ber­ware-equipped peeps in the house). Then you can eas­ily see the prob­lem.

If hu­mans re­viewed these videos, how did YouTube con­clude that these Windows tu­to­ri­als posed “risk of death”?

This in­ci­dent high­lights how au­to­mated mod­er­a­tion sys­tems strug­gle to dis­tin­guish le­git­i­mate con­tent from harm­ful ma­te­r­ial. These sys­tems lack con­text. Big Tech com­pa­nies pour bil­lions into AI. Yet their mod­er­a­tion tools flag harm­less tu­to­ri­als as life-threat­en­ing con­tent. Another re­cent in­stance is the re­moval of Enderman’s per­sonal chan­nel.

Meanwhile, ac­tual spam slips through un­no­ticed. What these plat­forms need is hu­man over­sight. Automation can as­sist but can­not re­place hu­man judg­ment in com­plex cases.