Since the beginning of search engine time — effectively the beginning of the Internet — Google has been #1. While Yahoo took a run at them in the 90s and Microsoft/Bing in the 2000’s, neither was able to eke out more than a few points of market share.

Google makes gobs of money as the undisputed king of search and they’ve continually used that money to try and find new ways to make money. In tech especially, a company that’s a one trick pony does not last. Google has spent a lot buying AI companies and investing in AI research.

Nine years ago, Google published this paper introducing the Transformer architecture that’s behind every single AI product on the market today. Initially Google didn’t know what to do with it. See, it threatened their core search business, which even today accounts for well over half of the money they make.

While you want to find new sources of revenue — thou must not kill the cash cow. While Google fretted about how to integrate AI into search without killing its cow, two new startups broke the AI market open: OpenAI with ChatGPT and Anthropic with Claude.

These new LLMs started taking traffic away from search. I’ll take an answer from AI every time versus the now ugly, ad-ridden search results Google spits out. So a couple of years ago, Google got serious and shipped Gemini not only as a standalone AI product but also integrated into Google Search. They’re still working hard to catch up, so it wasn’t surprising that last week’s Google conference was 99.9% about Gemini.

Every big tech company has an annual conference and it’s an extended PR event to launch new products. Steve Jobs theatrically orchestrated keynotes at Apple’s annual Worldwide Developers Conference would often end with his tagline: “… and one more thing.” In 2007, that was the iPhone reveal.

Microsoft’s annual conference is called Build and it’s next week in San Francisco. Inside of one of these companies, the months leading up to the event are a mad, frenzied dash to make sure your product is ready for this moment. Make it into the show, and that’s the difference between a product or feature that ships versus one that gets shelved.

If you get into the keynote (the kickoff session on day 1), now you’re living large. Google calls their conference I/O.

Half the stuff at these conferences are hype and never ship as shown. If they do ship, they often disappear because the market doesn’t take to them, so I don’t usually pay much attention. However, there were two telling things in this year’s Google IO keynote.

The first was a variant of Steve Jobs “one more thing ….” Google’s CEO is Sundar Pichai and he’s about as exciting as watching your toaster melt cheese. Sundar opened up the show … Gemini, blah, Gemini, blah blah blah, Gemini.

But then, at the very end of the keynote, AI legend Demis Hassabis, CEO of Google DeepMind took the stage.

Demis dropped this line at the end of the keynote:

When we look back at this time, I think we will realize that we were standing in the foothills of the Singularity.

Oh man. With a general public increasingly freaked out by the looming impact of AI on jobs, quality of life, no datacenters in my backyard … your public conference is not the time to hype the approaching moment when the machines get smarter than us.

Read the room, slow your roll.

The second thing was the return of Google Glass:

Return of the Glassholes. 14 years ago at this same conference, then Google CEO Sergey Brin dashed onstage in cyborg lenses to orchestrate a dance of socially uncomfortable super freaks.

Fail. Nobody bought those things. Creepy. Not to mention you looked stupid and everybody hated you.

Last week’s demo was notably more pedestrian — literally — the scenario was walking directions and ordering coffee. But this is a niche product at best.

At Meta’s annual conference last year, Mark Zuckerberg attempted a more ambitious demo of their new glasses on the big stage. In all my life I have not seen a live demo fail so comprehensively.

Everyone is searching for the killer AI consumer app / wearable. Chat’s nice but there’s going to be a new thing and nobody has figured it out yet.

It’s not going to be the glasses.

Early to bed, early to rise — dough in the belly, dough on the side.

— Been Fryin’, Poor Richard’s Almanack, 1735

School’s winding down and the days are getting hotter. Fifth period hits after lunch and the heat of the day. I unlock the classroom door, muscle my way in before the kids fighting for the roller chairs, hit the lights and crack the back door in an attempt to coax the heavy air to move through a portable with windows that don’t open.

The AP test was last Thursday so now we’re on easy street. Friday I switched out jeans and new t-shirts for shorts and old t-shirts. With the weight of the test lifted, I’m more relaxed and so are the kids. They feel summer coming.

My job is done — they coded their projects, they all took the test and they all did great (so they tell me).

Test scores come out July 6, so we’ll see, but I feel good about it too — we covered a ton of material in the 3 months I had with them. While it’s a constant battle to hold their attention, even when I think they’re distracted they’re listening.

I brought in a bunch of donuts on Friday for a sugar fueled test debrief. Riding high on the wave of finishing the test, I got lots of stories like the kid who got stuck in the wrong test section thanks to the schools intermittent WiFi. Two kids forgot their chromebooks and the administrator had to sprint to the office and back to get spares for them. I gave her a donut for her troubles. A lot of kids finished early and just had to wait (the test was 3hrs).

One kid kept sneaking back to the boxes as we talked, eventually downing four donuts. He was a little green by the end of class, but then went on to catch for the varsity baseball team. They won league later that day confirming donuts are a critical element of any diet.

But I can’t let these kids go without hands-on AI — it’d be a crime to teach CS without AI today, so this week we get AI to write the code.

Last year, vibe coding became a movement powered by tech enthusiasts thrilled with AI writing programs they wanted but couldn’t code. My kids had never heard the term, and I don’t like it much, so I’m calling this unit AI Mad Libs. They all know Mad Libs and that surprised me — they aren’t always on their screens. I build short AI prompts for various games, they fill in the blanks to make it theirs and we iterate from there.

Their ideas are better than mine. Honestly they do better when they go rogue off the prescriptive prompts. AI is good enough to make it work. One of my quiet kids yesterday sat in the back of the room, heads down building Neon Parkour. He had a crowd around him playing it by the end of class.

We’ve also got: Grand Slam Guesser, Forge of Legends, Echoes of Time, Aura Chiba and Neon Sphere 3D. Still got one more day.

Check them all: https://analynet.xyz.

I had an ulterior motive in bringing in the donuts — I wanted to show off my demo AI app — DOUGH DROP.

With Dough Drop you build your dream donut, watch it bake and then get roasted by a gallery of top AI Celebrity Chefs: Jacques the French pastry chef, Guy Fieri (Sonoma County’s hometown hero) and Gordon Ramsay.

You can share the roasts with your friends. Guy hypes you up while Gordon tears you down (usually): 1

In the midst of the Friday’s donut-palooza I checked in with the senior table. We’ve been through it and they’ve decided I’m ok now. They asked me if I knew anything about stocks.

I try to figure them out; they try to figure me out. I said sure, I know a bit. Then they asked me about day trading. I said, yeah if you like gambling. They like gambling.

One of the seniors was serious about this, so we had AI build this Python WALL STREET SIMULATOR and we ran through it as a class.

It doesn’t matter if you have a lot or a little to start. Put in the minimum to open a brokerage account, throw a little bit in a month. $10/mo is a start. Get a job, up it to $100/mo. Get a promotion, up it to $1000/mo.

This is the thing I will never convince these kids or any kid of — they have the best investment advantage right now — TIME. If you’re under 30 reading this — do it now! At 16ish my kids have 30+ years and a little bit of money will grow into a big bit of money with some time.

As far as what you invest in, as long as it’s a diversified fund, that’s secondary to just getting started. Don’t get stuck on picking the perfect fund. Sure fire winner — drop it in a no-load broad market index like VTSAX and just keep watering it.

Market conditions? No matter. You can’t control the future. With a time horizon of 10+ years it’ll even out.

Graton Casino down the road here just added a new wing for high rollers including fancy restaurants like SoCo Dough Co. They’re selling this $275 Donut:

Nah.

What do they even do in the bathroom?

I’ll never know, but I do know one thing — not a single kid in my class uses Facebook.

I asked them earlier in the week teaching them how all this AI stuff even happened. They do use Instagram, an app that was perfect in its time. The smartphone had just blown up, so everyone was walking around with a marginal camera in their pocket. Kevin Systrom was the guy who invented Instagram. His first App was called Burbn1 and it was for check-ins.

Burbn wasn’t doing so great but people liked posting pictures so Kevin went minimal — one app, all images. App written, he went on a break to Mexico with his girlfriend. Nicole didn’t think their phone vacation snaps looked good enough to share. So Kevin went back to the hotel and built the first filter. He called it X-Pro II and it’s still in Instagram today.

The next day Kevin posted the first Instagram photo from a taco stand (that’s Nicole’s sandal next to the dog):

A star was born. Kevin caught lightning in a bottle. Instagram grew to 30 million users in 18 months.

Facebook — Mark Zuckerberg — saw the threat. Facebook’s mobile app was worse than the crappiest of crappy phone cameras. Instagram’s app was simple, elegant, mobile only and it was beating the pants off FB: 2

So Mark bought it.

He courted Kevin with a combination of money ($1B) and threats. He promised Kevin Instagram would stay independent and he would still be in charge.

Of course that didn’t last — Instagram was growing faster than FB — so Mark took it over, crammed it with ads and a few years later Kevin left. Don’t feel bad for Kevin — choices — he left a rich man, but he lost his creation.

Same story, different ending: Snapchat. Evan Spiegel invented Snap, and when he was 22 Mark came for him too — offering him a mind boggling $3B dollars for his company. But Evan said no. That was the day I started using Snapchat. I remember reading that headline and thinking Evan was my man.

Mark holds a grudge. He couldn’t have Snapchat so he blatantly stole every innovation Evan came up with and he came up with a LOT. Snap was a revolutionary app in its prime: ephemeral chat, stories - yes Snap invented stories! Mark also stole Spectacles — now creepy Meta AI glasses — he’s still trying to get that one to work.

Through it all Evan held on and while the future of Snap is not clear to me — one thing that is clear is that Evan is still running the show.

Mark hasn’t come up with a single original idea since he created Facemash in his Harvard dorm — a hot-or-not website to rank college girls. He’s an ultra competitive, cutthroat businessman and boy did he nail ads, but he’s got no heart, no innovation, no soul.

Mark created an ‘insider’ class of Facebook stock and he owns most of. It has 10X the voting rights of a standard share, so Mark controls the board and can never be fired. With the ad money making machine and no accountability, Mark has gone off on some ridiculously expensive attempts to invent the next thing.

Take the Metaverse - he renamed the company Meta and spent over $80B building it only to shut it down earlier this year without making a dime.

Even though my HS kids are on Instagram, they aren’t sharing pics. IG is no longer a place to share with friends. That happens in private chats now, across messaging apps like iMessage, Signal and WhatsApp.

For instance, here’s Boo. I am fortunate to be treated to steady diet of Boo pics in our family chat. While our dog Lola had her own Instagram account, that was a million years ago.

Boo knows better:

Mark see’s this happening. Another big threat. He may be a tool, but he’s not a fool.

So, Mark bought it.

Shockingly once again he promises WhatsApp’s founders — Jan Koum and Brian Acton — to preserve the core elements of the app they built (privacy, security, ad-free) and that they will be in charge. The real shock is after what happened to Kevin and Instagram, Jan and Brian fall for it. Guess it’s hard to turn down the big money. Well in came the ads and they both left abruptly a few years later.

AI is bigger than the mobile wave. AI is bigger than the messaging wave. AI is the biggest wave and Mark see’s it bearing down. What’s he doing about it besides shoving AI generated slop into every feed possible?

How about laying off a bunch of people and then telling the ones left they have to run AI training tools on their computers that record every keystroke and also screenshot while they’re working? When jobs went overseas in the 2000’s there were lots of stories of training your replacement on the other side of the world.

How about training the clankers to take your job?

Meta’s AI model Llama was hyped as open source but the industry saw through that and then and then their latest model Llama 4 well — it sucked worse than those first mobile cameras.

Since not much of this is working, Mark is back to his old playbook of bullying his way into a new market by buying every AI company he can get his hand on.

That’s not going great either.

There’s a big tech trial going on down in Oakland this week. Elon Musk is suing OpenAI for the way they converted the company from a non-profit. Satya Nadella Microsoft’s CEO and the last boss I had testified on Monday.

A bunch of juicy docs have come out of this trial including these texts between OpenAI’s Mira Murati (then CTO) and Sam Altman (CEO):

Sam did indeed get fired 3 and Mira was thrust into the spotlight as OpenAIs CEO for 5 days.

Mira is legit. She’s an immigrant from Alabania and so smart. If you ever wanted to understand what’s really powering today’s AI, Mira explains it:

After the Sam ordeal, Mira left OpenAI, and an elite group of AI researchers from OpenAI went with her to form a new AI company called Thinking Machines Lab.

Here’s what she said when she left:

So Mark bought it.

Not this time. He sure tried — he came after Mira and her new company, but Mira said No. Mark went nuclear, headhunting every researcher in her company.

They ALL said no.

Last week Meta announced a dip in their users numbers for the first time in, well in forever. They’ve never lost users. I think it’s a sign and I’m not the only one:

Meta is Dying. It’s About Time.

Facebook will not go quietly. Not only because Mark but because network effects. Where else can I go and hang out with an unholy hodgepodge of friends from elementary school to my high school girlfriend to random people I used to work with? I still have to open Facebook once in awhile, and I hate it.

The future I’m looking forward too, is one where we’re done with Facebook, and Mira and her ilk build new ways for tech to serve the humans.

My parents lived through D-Day, the Cold War and NATO, the civil rights movement, Watergate, the dissolution of the Soviet Union. Technology blossomed around them from the transistor to the Internet, to a computer beating a world master in Chess.

TALKIE — a new ‘vintage’ AI large language model doesn’t know any of this happened.

TALKIE was trained on over 2 million books and periodicals and journals — every single one published before 1931.

Why 1931? Because any publication over 95 years old is public domain — there are no copyright restrictions.

How is such a huge corpus of paper books available to train a machine? While the technology to convert a printed page into computer bits 1 has been around since the 1950’s, Google supercharged it in 2004 in an effort to digitize every book ever written.2

Google created custom hardware powered by the latest tech that sped through books, scanning 1,000 pages per hour, but error rates — especially on handwritten text were still high. In 2009, an acquisition solved that problem.

The acquisition was reCAPTCHA. That’s those annoying puzzles you get on websites to prove you’re a human. reCAPTCHA put the words Google’s OCR failed on in front of millions of humans to solve. Those crowdsourced answers were built into the scanning algorithms which gave Google the final piece it needed to unlock digitizing old books at scale.

TALKIE is rooted in the tech of its time, and in 1930 that was Radio:

Why build TALKIE? To see if AI can predict the future.

Demis Hassabis, CEO of Google DeepMind came up with the Einstein test earlier this year as a way to gauge if AI can ever actually be “Intelligent”:

TALKIEs creators want to know the future. Specifically, they want to know if a machine can predict the future.

TALKIE doesn’t know about what’s happened since 1930. But we do. Can TALKIE predict what we know happened?

While radio was the transformative tech in the 1930s, movies were becoming more popular — especially ‘Talkies’ — the silent movie killers. But what about the visual equivalent of Radio — Television?

I asked TALKIE if we’d ever see moving pictures through the air like Radio:

That’s a natural scientific arc. But what about Humanity? I asked Talkie if Germany could become a fascist state:

Eleven years after TALKIES 1930 cutoff date, my dad was fourteen and could watch TV dispatches from Europe about WWII. TALKIE was right about the technology.

Eight years after TALKIES 1930 cutoff date, my mom was twelve and fleeing Austria on the Kindertransport. TALKIE was wrong about Germany.

Predicting or creating novel science — I can see that. Predicting the foibles of humanity — I don’t think so.

They sure did a lot of damage though.

I got stuck in the middle of it and it was utter and complete chaos — the onslaught of worms, viruses and malware was nonstop, and the tools we needed to fight them didn’t exist. Melissa, SQL Slammer, Code Red, Nimda, Blaster and of course … ILOVEYOU.

Then there were the guys who saw the wave — saw the opportunity — fashioned their white hats, grabbed a surfboard and rode that wave. While they promised to save us all from the scourge — they made out like bandits.

Still, it ended badly for many of them.

My gig back then was building massive corporate email systems. Custom systems built up around a product called Microsoft Exchange. Exchange 5.5 had built up a loyal corporate following and the new release — Exchange 2000 — would go on to become the cornerstone of Microsoft’s enterprise collaboration business.

PCs had blown up and they were on every desk, in every classroom, every warehouse. The mantra was make it faster, make it easier, make the components and the software easier to use.

Security was an afterthought, an annoyance, something that slowed down the pace of releases.

ILOVEYOU took advantage. A few lines of Visual Basic written by a frustrated college student in the Philippines, took down the Pentagon, the FBI, the UK Government, and AT&T.

Here’s the guy that wrote it - Onel de Guzman.

Onel’s college professor threw him and his thesis project to steal passwords out of school. Unethical he said. Frustrated, Onel went home and wrote up the code. He couldn’t afford internet access outside of school and this one trick was going to get him a stash of dial-up credentials to keep going.

He attached his creation to an email, typed a line to a friend in Singapore, hit send, and went out to get dinner.

That one email spawned a global crisis. In 10 days ILOVEYOU took over computers around the world, leaving behind a trail of destruction. 45 million infecting computers, hundreds of millions of deleted files, tens of millions of stolen passwords. ILOVEYOU scraped so many credentials, the email accounts de Guzman sent them too became hopelessly backed up and inaccessible within hours of that first email.

Antivirus software was nascent at the time — there were no techniques to counter a zero-day attack like this.

Clicking on the love letter (which appeared to be a simple text file, thanks Windows)1 not only grabbed cached passwords, it replaced every picture with a copy of itself and then mailed itself to everyone in your address book. Who can resist reading a love letter from someone you know?

Exchange couldn’t keep up with the mail volume. The only solution was to take down every server, purge the mail queues and manually patch every infected computer before bringing the servers back up. On a large system this took days. I worked some long nights.

Onel later said:

Peter Norton and John McAfee had established their tech business’ before ILOVEYOU. Norton came from a comfortable family in Seattle, and after getting laid off by the aerospace industry, he became a buddhist monk in San Francisco.

Then, he accidentally deleted a file on his computer. Rather than anger, Peter choose the path of the buddha and instead of recreating the whole file, he wrote a program that recovered it. Then he wrote a few more system programs. He started dropping into computer user groups and Norton Utilities was born. Norton Antivirus came soon after. Business was good; ILOVEYOU made it exponentially better.

There was a time when you couldn’t walk into a computer store without seeing shelf after shelf of yellow boxes with this picture of Peter on it. Norton AV was what you bought to protect your grandma’s PC from the Onel’s of the world.

John McAfee’s origin story is rougher. Born on a US Army base in England to an American father and British mother, his dad abused him and his mom, eventually committing suicide.

John got his degree in mathematics and bounced around as a programmer in the defense industry including time at NASA. When someone showed him one of the first viruses on a floppy disk — he saw opportunity. It’s all just software.

John wasn’t the safe choice like Peter - McAfee weaponized viruses; he sold fear. McAfee AV was the only thing that could save you from the scourge of software coming for you.

Like Norton, ILOVEYOU was a gift to John McAfee. McAfee and Norton Antivirus traded places as the #1 and #2 AV companies, minting money in the process.

In January 2002, Bill Gates realized the scope of the problem and slammed on the brakes, pulling 13,000 Windows engineers off feature work to focus 100% on security. Every developer in the company underwent rigorous security training. I spent a week up in Redmond deep in it myself.

Peter, John and Onel’s malware wave ran out of steam as each new version of Windows shipped with a lot less bugs and a lot more security baked in. With AV built into Windows, the market for standalone AV software evaporated — bad news for Peter and John’s companies. 2

But Peter and John were smart — they both cashed out early. Peter left at the top of his game with 70 million, becoming a philanthropist, art collector, and building his dream home on cape cod. While his face kept selling product, he never looked back.

He’s still kicking.

McAfee left a few years after Peter with $100 million — he would later call McAfee’s software ‘the worst on the planet.’

But John did not go quietly and collect art — he moved to Belize, living a life surrounded by big dogs, drugs, guns, and murder. His behavior became increasingly erratic and paranoid. His neighbor poisoned his dogs; his neighbor was found executed. Fleeing Belize from the murder charge, he returned to the US, embracing crypto while mocking the IRS saying he would never pay taxes.

There’s a ton of media on John if you’re curious; this video he made is a glimpse of the madman.

He’s dead.

The IRS caught up with John and he fled the US, living off his mega yacht with his third wife, four guard dogs, seven staff and two security guards. He was made land in Europe and was arrested in Spain, charged with tax evasion, money laundering and fraud. He died of suicide in 2021 at age 75. The day the Spanish Court ordered his extradition back to the US to face charges.

What about Onel? It wasn’t hard to trace ILOVEYOU back to him. His email and hacker handle headlined the code. But the Phillipine’s had not written any cybercrime laws yet and he walked. However, the attention was too much for him and he disappeared.

A reporter caught up with him a few years ago — now he fixes phone screens in a kiosk in a Manilla mall.

Who would you choose - the Monk, the Misfit or the Madman? No one wants to be Onel. Opportunity wasted. I choose Peter. Leave at the top; live your best life. When I told my HS kids this story, a lot of them wanted to be like … John.

Here we are in a new wave. Who are the Peter’s and John’s and Onel’s in today’s AI wave? There’s plenty of characters to choose from. Sam Altman, head of OpenAI and Dario Amodei, head of Anthropic are easy picks. Neither is a Monk; both may be Madmen.

The closest we’ve got to Onel (so far) is Australian Vibe coder Peter Steinberger — creator of OpenClaw. I wrote about the recent riot Peter caused across the globe in Agent Smith. But unlike Onel, Peter played a smart game, landing a cush gig at OpenAI along with a fat paycheck.

But we’ve only just begun. Millions are out there hacking away at AI as you read this — everyone looking for their moment. Keep your eyes peeled — we won’t see this wave for what it is until we’re looking back.

But I know bridges. I look for them.

We drove over it in the morning and it was a beauty:

Growing up in LA, I didn’t see many bridges. So for my high school science project, I hunted one down, driving an hour south to San Pedro for a date with the chief engineer of the Vincent Thomas Bridge.

He took me up on the catwalk below the bridge. Glorious and dizzying and noisy. He told me the bridge is so big the painting never stops. When they get to the far side they just start over again.

Maybe bridges were part of my motivation to head north from LA up to the San Francisco Bay Area where I could spot this beauty every day. 1

The Bay Area is defined by its bridges — the Golden Gate crosses the mouth of San Francisco Bay and there are four that cross the Bay. From the top of the bay to north to south: the Richmond, Bay, San Mateo and Dumbarton bridges.

In Sneakers, Robert Redford and his crew sleuth out the bad guys by doing blind bridge math. Pick the wrong bridge during rush hour, there goes your evening.

I had graduated and moved back to LA when disaster struck. The Loma Prieta earthquake not only pancaked most of the 880 through Oakland but a massive section of the top lanes of the Bay Bridge (where you drive heading into San Francisco) fell onto the bottom lanes which head back to Oakland.2 I watched it go down on TV along with millions of others just as the 1st inning of the Giants versus A’s “Bay Bridge Series” was getting underway.

CalTrans patched up the old span, building a new bridge side-by-side and then finally blowing up the old pilings. I was commuting from Oakland into the City for a good part of that and watched it happen. Two decades and $7B dollars later the new eastern span opened, crowned by a massive 500 foot tall tower made in China.

A few years ago I biked over the new span. We met in Larkspur in the Ferry Building parking lot and first went over the Richmond bridge. That was not fun. You’re biking into traffic in a makeshift bike lane with temporary barriers —honestly, it’s terrifying.

But the new Bay Bridge has an official bike lane that’s big enough for double wide strollers and dogs.

It’s a climb to get to the top of the span. From the top we could see the ferry pulling into Treasure Island. You can’t bike across the old span so we needed to catch that ferry. We didn’t — it pulled away just as we made our way off the bridge.

The view wasn’t bad waiting for the next one.

The Ferry is bike friendly.

From the Ferry Building we biked down the Embarcadero, through the Marina, and joined up with a throng of tourists in Golden Gate Park biking and walking over the Golden Gate bridge.

65 miles and six hours later — we got back to Larkspur where we started.

Three bridges and a ferry.

I went back to LA after graduating from Berkeley, but I only stayed a few years before I moved to another water city — Seattle, the Emerald city — home to more beautiful bridges.

To get from Seattle to Redmond, you have to cross Lake Washington. It’s too big for an arch bridge or a suspension bridge. Enter a third type of bridge — floating. Once I drove over the old floating bridge in a storm. It was bucking like a sea serpent; I figured that was the end.

They’ve since rebuilt it and it’s the longest floating bridge in the world.

Bridges aren’t easy. For a minute, the Tacoma Narrows Bridge was one of the longest suspension bridge in the world. Until a bit of wind hit the perfect resonant frequency that amplified the structure with every gust and blew the bridge down: 3

There’s one more type of bridge — and that’s a cable bridge. My hotel in São Paulo looked down on a fine specimen of this on my last International business trip.

This is the Ponte Estaiada bridge in São Paulo. Rumor has it I returned from Brazil in 2020 and brought COVID with me.

After I left Microsoft, we moved up to the Sierra Nevada mountains, just down the street from the famed Donner Summit Rainbow Bridge on old 40.

Many a car commercial has been filmed here. That’s Donner lake below. The rainbow bridge is another variant of an arch bridge. I’ve also biked this bridge down to Donner lake and back, but it’s sketchy down and torture up.

Sonoma county north of San Francisco is criss-crossed by rivers heading to the Pacific. A lot of the bridges — like Wohler bridge here — cross the Russian river.

We rode over Wohler last month, just before they closed it for repairs. My bike was feeling the miles and needed some work too, but I got it back from the shop yesterday so now it’s time to find more bridges.

AKA “the whole story.”

Mythos is the name of Anthropic’s latest AI model. Unlike their prior models released with fanfare and hyperbole, they’re not releasing Mythos (at least not yet).

They claim it’s too dangerous.1

From Anthropic’s national security team:

Why oh why would a company build a thing that could set back cybersecurity 30 years, take down the internet, and force a rewrite of every piece of software?

Put a pin in that for a minute and lets talk about OpenBSD.

The B in OpenBSD stands for Berkeley. It’s one of the early Unix 2 Operating Systems, and the very same one I learned to program on when I was a wee sophomore at Cal.

I spent a lot of time down in the basement of Evans hall.

The computer lab had no windows, lit instead by a matrix of florescent tubes, their harsh white light bouncing off row after row of black and white CRT terminal glowing screens. The floor was linoleum and slightly sticky. The lab was powered by all-nighters fueled with caffeine to a Motown soundtrack courtesy of a crowdsourced boombox my professor bought and chained to one of the desks. 3

The room smelled of sweat and — as the semester progressed — a tinge of desperation.

Our programming stack was housed next next door in a room full of mini-computers running OpenBSD Unix.4 We edited our code in this super sexy editor: 5

After a few hours down in that basement you could feel the hummmm of computing within you, around you, through you. You were in the belly of the beast.

Today, in my high school class, the stack is decidedly more abstract. The kids write their programs in an online educational program called Codio. Their code runs in a virtual sandbox on a nameless server up in the cloud in a datacenter far-far-away. The classroom has windows too.

The fundamentals of programming are not different than those I learned forty years ago. But I have to work hard so the programs they write seem even a little bit relevant to what they see on their phones, their laptops, even the school’s website.

I think they have similar real world disconnects across most of their classes. It must be tough — they certainly aren’t of an age where they are just seeking knowledge.

It’s no wonder they’re easily distracted.

A lot of my kids pick up a Rubik’s cube the minute their hands come off the keyboard. I’ve learned they’re still listening to me. Better than they would without the cube. If you look into the why of this, you’ll find Neurodivergent.

I probably fall under this category too, but who knows? Brains are weird.

Also amazing, so we started building machines to recognize patterns and create things mimicking how we think. The first AI approaches were grounded in traditional programming. Now called symbolic AI, they use logic and rules along with purpose-built knowledge structures to make computers reason step-by-step.

Today’s AI is markedly different and it doesn’t always work.

If you’ve talked to an AI chatbot you know the responses can be wildly variable. It’s part of the novelty and the fun. It’s a prediction machine built on statistics. Two runs with the same exact input can have very different outputs. Hallucinations and inaccuracies prevail.

JFran uses ChatGPT for lesson plans. It’s good at cranking out say “Ten fill-in-the-blank adjective sentences for a third grade bilingual class in a nature unit”

But then she tried to get it to do a simple Spring Crossword puzzle:

If you ignore the paint-it-black on the right, it does resemble a crossword puzzle. But then you realize the words don’t fit and the numbers don’t match and it’s just all a terrible jumble that makes my head hurt.

So I tried. This time with a paid subscription and the latest thinking model. I asked for a simple 5 x 5 using computer networking terms. After 14 minutes and 17 seconds of “thinking,” I got this:

Before I started I asked ChatGPT if it could pull off a crossword puzzle:

I questioned it’s confidence:

It got shy:

This is the madness of Generative AI Large Language Models.

The AI labs introduced thinking to manage this behavior. That’s where the model interjects rules and stepwise processing to evaluate results before proceeding. As you can see above that doesn’t always work.

Now we have skills and projects where you can memorialize the steps after a successful session/task completion for repetition and keep a running record of resources. This works well for defined tasks without a lot of variance. I use a version of this in my class with a model that’s constrained to operate on a set of curated sources. In my case all the official AP curriculum.

While this is getting better, it’s still not great. There’s a debate between two opposing AI camps: neural networks (statistical predictive models) versus traditional machine learning (symbolic deterministic models) for the future of AI.

Hybrid models are now showing up and it might be the best of both worlds. Think of how you or I might balance our intuition with evaluation when making a decision.

Recently Anthropic, the same company that is scaring the pants off us with Mythos, accidentally revealed a bunch of their source code on the internet (hehe). It was Claude Code (code) — a very popular AI coding tool.

Analysis of the leak pointed to a library with a large and complex decision trees based on traditional IF-THEN statements. So it appears Claude Code is a hybrid architecture combining new and old AI techniques.

While I only have passing understanding of all this stuff, one thing I know is the best architecture eventually wins. The example of this I’m teaching my kids right now is the Internet. Out of tons of networks the set of protocols that define the Internet won. That took about twenty years.

Maybe we regroup from developments like Mythos and realize humanity doesn’t need the risk of powerful computing systems that are a black box to us. We need a deterministic layer to make sure certain rules are always followed.

Like don’t break the Internet.

You build a program, let’s call it Halt. It isn’t complicated, Halt simply determines whether another program will run forever in an infinite loop or it will eventually finish.

But then someone goes and writes a program called Trouble that looks at what Halt comes back with and does the opposite. So if Halt says Trouble will loop forever, Trouble does the opposite thing and finishes its run. If Halt says Trouble will finish, again it does the opposite and loops forever, never finishing.

Trouble is a perfectly legitimate program. It may not be trivial to write, but programming is all conditions and loops.

So what happens if Halt tries to evaluate Trouble? It can’t work.

Halt cannot exist. The Halting Problem cannot be solved. In CS lingo it’s undecidable.

Alan Turing came up with this around 100 years ago just as we were building the first computers. This is from the same guy who created the Turing Test, one of the more interesting questions in computer science until AI and Large Language Models came along and showed us just how easily we can be fooled.

As opposed to the impossible mind-bendy halting problem, impractical problems are ones we’d very much like to solve. But, the algorithms to solve them require so much compute that before we get an answer the sun will become a red giant and turn the Earth into a tater tot.

The classic example of an impractical problem is The Traveling Salesman. Again the problem is deceptively simple:

A salesman needs to visit 20 cities to hype his new AI app (which looks like juice boxes). What’s the most efficient route?

We solve this problem by checking each possible route. If the salesman is going to 5 cities you can do it. There are 120 possible routes. The math that counts all routes is 5 factorial or (5!).

5 x 4 x 3 x 2 x 1 = 120

You’ve heard of exponential. That’s growth by a constant factor, for example doubling every year. Perhaps you’ve also heard that when AI starts building AI it will grow exponentially smarter until … the SINGULARITY.

Factorial growth is significantly faster than exponential growth — every new city you visit increases the number of routes by a higher factor. Say the AI juice boxes are taking off, so now our salesman has to visit 10 cities. At 10 cities, the number of possible routes jumps from 120 to nearly 4 million.

Twenty cities? That’s over 2 quintillion or 2,432,902,008,176,640,000 possible routes.

The Traveling Salesman Problem isn’t impossible like the Halting Problem, but it’s impractical. Forty cities? It would take the world’s fastest computer hundreds of years to calculate every route. That’s really not so many cities — no juice box for you! In computer science, that’s called an intractable problem.

A heuristic is a clever workaround or hack that gets close to the right answer. For the TSP, just pick the closest city each step of the route. You won’t get the optimal answer but it’s close enough. That’s how your Amazon driver figures out where to drop off your monthly supply of Hanes boxer briefs.1

I wrote a program that does the math — you can play with it here. 2

At the turn of the century, math enthusiast and businessman Landon Clay launched The Millennium Prize Problems. Seven unsolved problems. Solve one, win a million dollars. The TSP lives in one of these.

The world is full of problems to solve that would do more than deliver juice boxes. Or boxer briefs. Making progress on these could be big — we could live longer, happier lives on a healthier planet.

So how’s our great new innovation AI doing at solving these hard problems? AI isn’t going to save humanity by doing your homework or drawing weird pictures. Our AI salesman will tell you it will improve everything you do just a little bit. You’ll become more productive.

Every product I ever worked on promised this same thing. It’s impossible to quantify.

AI has taken a couple of swings:

Google’s AlphaFold made a major breakthrough in protein folding, accelerating biological research (like understanding Alzheimer’s) leading to a Nobel prize.

Another: AI helped decipher the carbonized Herculaneum scrolls that burnt up when Mt. Vesuvius erupted 2,000 years ago. So far they’ve found the word ‘purple’ and a discussion about the nature of ‘pleasure.’ Translation is ongoing. I’m certain more p-words will be found.

Perhaps we might also work on, say, the climate, Alzheimer’s, food for everyone.

How about we figure out fusion and cure cancer?

I don’t have a quintillion years.

The world feels a little wobbly, and so does the job market. AI is a big part of that.

Up until now I got by on my spidey-sense. I always got out before the company went down, or the bad boss imploded.

Often, just in the nick of time.

Dysfunction junction? Plan your exit, pick a better boss, get a mentor, find some allies.

Ego-maniacal boss? Toxic workplace? Manage up, channel that anger energy into finding a greener pasture. You can’t get out of this one fast enough.

Company struggling? Work connections, build bridges. Get out before the ship goes down.

One rule covers all of it: keep your head up. There are always clues but you have to be looking for them.

What’s going on with staff, co-workers, management? Are good people leaving? Managers/Leaders leaving or playing an odd game of musical chairs? Is the company in a hiring freeze or not attracting strong talent?

Time to look elsewhere.

Re-orgs are great — full of clues — who got promoted, who got a larger remit, who got a bigger budget? Go work for that group. Network like crazy on the inside.

Same with products — what’s making money for the company? What’s not doing so well or getting de-prioritized? Go work on the hot stuff. Better to be in the hot seat than no seat.

Getting fired is plenty unpleasant. I’ve had brushes with it one way or another and while there are plenty of euphemisms — it’s always personal — even if your company or your boss tries to make it impersonal.

Take RIF for example — Reduction In Force. The Force made me do it.

Here’s another awful acronym: DNM (Did Not Meet). Get one of those on a performance review, turn the networking dial up to 11, start looking outside the company at least a little bit every single day. Start hoarding office supplies.

It isn’t you. It’s one of the above things, but none of that matters if you’re out of a job. To keep your agency — your ability to navigate and manage the ever changing tides without becoming a victim — develop that spidey-sense.

So how did I get fired? By taking an emergency job in a public High School in a district, in a county — in a state — where public education is under duress post COVID along with a myriad of other issues I don’t pretend to understand.

You can read about what’s happening at my high school here. This cut: Information & Communications Technologies - Computer Science .2 FTE 1 — is the position I’m filling through the end of the year.

I’ve been whining about how much work this .2 FTE is, so while I’m having fun (mostly) it’s messing with my semi-retired vanlife, so it’s all good.

Reading the workplace was tricky enough and then AI entered the picture.

I may be off the career hamster wheel, but I’m still survival-coded to try and figure out the next thing. So, while my livelihood no longer depends on it, I’m intensely AI-curious.

I happily jumped into this teaching job even thought I’d never done it, knowing Claude2 had my back. A couple weeks ago I wrote about using all the AI Google offers in the classroom in AI High.

Last week we finished our big coding project so it’s time to pack the next six weeks with all the knowledge they need to kill it come AP test day.

Saturday I spent some quality time with Claude to figure that out.

I fed Claude the school calendar, my M/W/F schedule, teaching styles that land with the kids, what they theoretically covered before I took over 3, what the AP College Board says they have to cover, and what’s actually on the test. We went back and forth until we landed on a plan I like.

I won’t go back to the online course (which the kids hate), so now Claude (along with Gemini/Google Classroom) works with me to build lesson plans grounded in this larger plan on the daily.

If you look at AI as just the latest tech, it’s not so different from picking up on the next hot thing. But AI isn’t just the latest tech. This cognitive layer we’ve built with a natural language interface is quite different from everything it’s built on top of lower in the stack.

A constant through every job I’ve had — including my current HS teacher stint — is I never have enough time to do all the things I want. The more engaging the job, the more I’ve found this to be true. If you can compartmentalize AI to take on the stuff in your job you hate — the grunt work — well that’s one way to get to know it and make it work for you.

One gauge of the impact AI might have on jobs is the first industry it’s completely upended: software development.

Anthropic (makers of Claude) says AI now writes 90% of new code. But they’re still hiring software engineers, including entry level. They look for ‘AI natives’ that have embraced AI from the outset and consequently have a feel for how to work with it, imposing judgement, taste and design skills to build great software not slop.

They’re preaching — AI hasn’t killed the job of a software engineer (yet) but it has fundamentally changed what the job is.

My HS kids will soon be out in the wild dealing with this uncertainty. I feel for them. My own kids are challenged on the daily by their companies to use more and more AI which is another level of overhead when you’re already busy. I don’t envy my buddies still at Microsoft refactoring their jobs around AI while the tech stack constantly changes along with the work flow.

Every tech company in the world lives in this pressure cooker, fighting to stay relevant in a world getting eaten by AI. There will be winners and losers.

But that’s the deal, so better run towards it, spidey-sense ready, rather than run away.

My students were pretty excited for a break too, but now we’re back at the grind.

On Monday, I get to school a few minutes early: open up the classroom, unlock the laptop vault and connect my laptop up to the big screen.

We have to get the coding project for the AP Exam done this week. I have two more units yet to cover plus review and exam prep.

We’re short on time and I‘m herding cats. Teenage cats.

The first bell rings and one of my seniors wanders in with a pizza box. Fifth period is right after lunch. I don’t know what this kid does during lunch but apparently eating is not it. In addition to bringing his lunch, this kid brings a welcome dose of seriousness to the senior slacker table. He’s worried about grades. We talk.

The rest of the kids straggle in; chatting, grabbing laptops from the vault, settling in with their table tribes. My class is in South Campus and it’s a long walk here.

I mentally take roll — everyone’s here but one kid and he’s a superstar (coding the NYT’s Wordle game by hand for his project) so I’m not worried about him falling behind.

I go through slides covering online project submittal. It’s a lot: full project code, a video showing the program working and a set of key code blocks.

The senior table is increasingly distracted by the pizza. Talk of sharing gets louder. It’s pepperoni and it smells good. I’m fine with the pizza but don’t talk while I’m talking so I stop until they close their laptops and their mouths.

A kid wanders in late, and sits with his head down on the desk. He finished his code before the break so I let it go.

I get through most of my spiel before I start losing them. One of my 10th grader’s who looks continually lost starts with the BIG yawns. For directions like this, their attention span is even shorter than normal, so I cut it short and tell them to get to work.

I circle through the class, checking in with each of them. I have three girls and they sit right up front — a 10th, 11th and 12th grader. They shelter together across grades, avoiding the chaos around them. They’re consistently my strongest group and keep me on my toes.

I make my way over to the solo-table loner in the far corner. While he barely makes eye contact with me and hates group work; he’s generally on it.

Next, the junior table. After the senior table, they’re the loudest because they play the games as they build them. One of these kids is on Varsity Baseball so he’s missed a few classes, but he show’s me this marvelous geometry run game he’s building, so all good.

That leaves the table between the girls and the seniors. A mixed group and perhaps my favorite table. This is where the kid who came in late and immediately put his head down is at and now we’re going on 30 minutes into a 50 minute period.

I tap him on the shoulder — “you ok?”

No response.

The kid next to him — super smart, startlingly tall and easily distracted — asks me to look over his code. All of a sudden, zombie child raises his head — staring up at me with bleary eyes. He has been asleep. Like deep asleep. He apologizes and says he’s really tired. But he assures me he’s on track to get his project done, so I move on.

He puts his head down on the table and goes back to sleep.

What was I thinking? I thought it’d be fun teaching kids about computers.

But teenagers are another species.

The stereotype on GenZ is their brains are busted from the internets. Addicted to their phones, endlessly scrolling through TikTok’s. Digital natives sure, but ones without the ability to stay on task.

It’s not like that.

The teenage brain releases melatonin later than adults so they stay up too late.

Impulse control isn’t quite there yet. Their frontal lobe is still developing, so their plastic brains are more susceptible to social context, rewards, novelty, emotion.

They’re also highly capable when sufficiently motivated.

On Wednesday I throw out the slides and kick off class with a Kahoot quiz!1 The class gets into it. Super tall kid wins, answering every question right.

Streak 🔥!

JFran has Hershey’s Kisses so I top off the candy bag with those and throw in a bunch of spider-man tattoos (leftovers from my 60th bday party). I hand them out liberally to everyone who get’s their project uploaded.

The senior table is really into cubing. I got on them early to lose the cubes and the phones and FOCUS. But before spring break, I asked one explain it to me. The whole table gets in on the conversation. They find solve algorithms online and compete for time.

One of the seniors was lost when it came to the coding project until we came up with an idea for a cube solver and he excitedly shows me he got it working.

Another kid wrote a build-a-burger app in Python including drawing all the layers after the order. ASCII art. =^.^=

They’re all smart.

AI isn’t on the AP test. Weird right? It’s only the most important innovation in Computer Science in 10 years.

But after the test is over we’ll have some fun with it — I’m going to turn these kids into wizards.

Then it’ll be Summer; we’re already planning the van trips.

But I’ll miss the kids.

That same day a plumber was at our house trying to sort out our continually problematic bathroom drain.

Animal control came. I don’t know what I expected, but certainly not what went down. He took one look at the skunk and pulled a big shotgun out of his truck. He put up a makeshift screen. The screen was completely ineffective — we saw and smelled everything. He euthanized the skunk, but not before it had a final triumphant hurrah, spraying him down thoroughly.

Meanwhile, the plumber had made it up on the roof to snake out the drain. We could taste skunk from the inside with every door and window closed. The funk hit the hapless plumber and he began gagging and coughing uncontrollably. Inside, Lola the dog whined. In the front yard the animal control guy bent over gasping. He staggered towards his truck, shotgun in one hand, tearing at his face mask with the other.

My teenage daughter and I watched the whole thing go down from the front window, horrified.

R screamed, “You had one job!”

“You had one job” might be past its prime, but I laugh every time I hear it.

I recently picked up “I don’t hate that” watching curling at the Winter Olympics1. The US team was mic’d up so you could hear them talk strategy surveying the icy layout of stones. During timeouts, the coach hustled down the ice to join in the discussion.

Over and over I heard: “I don’t hate that shot.”

That phrase now lives in my head like a cereal jingle. Fits the now. Sometimes it’s hard to get excited about stuff. “I’ll allow it” is a good companion.

Resignation. It’ll do. It has to do.

Remember the AI moment — not so long ago — when you could jailbreak a new model by telling it to “Ignore all previous instructions?” I bought a t-shirt festooned with a feral raccoon screaming that out.

Alas, the early, heady days of AI when it was simple and fun are well behind us. Now we’re AI haters or we’re AI pilled or we’re vibe coding.

Vibe coding will fade quicker than “you had one job.” While it’s very Jetsons for Elroy to dictate sophisticated software builds, even with AI writing all the code, software engineering isn’t a trivial undertaking, so thanks, but I hate it.

A few more from the skunk days that stuck. KOBE! Yelled in expectation as you attempted to toss something in the trashcan from a few feet away.

We’re Gucci. Cool, cool, cool. Everything is cool. Goes well with a dab.

Maybe I’ll get lucky and my high school kids will trust me with some genZ gems. You’re good. I gotta dip. That burrito was mid. 2

I’m generationally forbidden from using any of these, but entertain me.

My dad could throw down some slang. Malarkey. Stick your head between your legs and kiss your ass goodbye. He also did a mean James Cagney impersonation: “You dirty rat …”

“Monitoring the situation” is new. I relate. Doomscrolling.

But when it comes to AI, I can’t help myself.

I miss the inside scoop. Even with corporate spin it beat the talking heads and pundits. It’s grounding to use the thing on the daily with my high school kids. AI is but a few clicks away. See for yourself.

But if you don’t want to touch the stuff, you’re good — I’m monitoring the situation.

I did research the old fashioned way — I googled it. Drowning in a sea of blue links — it was the worst.

Now that I’m working 10 hours a week teaching High School (my first couple weeks felt like 80) I have all of the AI and I love it.

It’s saving me and my students.

I handed out assessments the first day I went in. I looked them over after class — it was grim. Their teacher left at Christmas and the subsequent parade of subs just had them do self study — ineffective for all but the most motivated high schooler.

Then there’s the AP test. You take an AP class in high school so you can take the test and it’s more than about getting college credit — it shows potential colleges you’re ready for that level of work — assuming you pass.

For reasons I don’t understand, the AP test is in May - nearly a month before school is over. For AP CSP there’s another hurdle — they must code and upload a program ahead of the test and that’s due in April!

So I knew I was going to be under the gun. What I didn’t know was what tools the school would have to help me.

Education has a testy relationship with technology. When word processors replaced typewriters — well there goes spelling and editing and penmanship. And let’s not forget the great copy-paste plagiarism scourge of the 2000s.

Today it’s the cell phones messing with our kid’s minds. This one is more about attention and mental health versus teaching — and for sure it’s tricky.

AI is different. From the start, it had the potential to be the best study buddy and unlike the concerted backlash to control plagiarism back in the 2000’s, chat based AI tools have grown so quickly that schools had to figure out how to use them versus banning them.

The pandemic is really behind this shift — that’s when every teacher and student had to get online. Before COVID, around a quarter of schools used online systems and today every single public school does. Google Classroom alone saw usage quadruple from 40M pre-pandemic to over 150M now.2

That’s the world I’m teaching in today as I try to get my twenty kids back on track and ready to pass the AP exam in a short two months.

The first thing I did after I accepted the gig was try to figure out the curriculum the College Board dictated for this course. What did I have to teach them so every one could pass the AP Test? I put together — no lie — 50 slides to parse it all out for them and reset the class.

Putting aside my mistake in overestimating the attention span of a 16 year old 3 — half of the slides I pulled were how not to use AI.

Some of this is fair and a plagiarism concern. After all, AI spits out code like it’s nothing, and you’re not learning anything if AI writes your program for you.

However, AI is eating up the software industry at a frightening pace, so not only do these kids need to learn AI yesterday, it’s the perfect tool to accelerate 6 months worth of learning into 2 months time.

I’m lucky this school uses Google Classroom. Initially Google lagged getting into the AI race — they didn’t want to cannibalize their search monopoly with the pages of blue links. But exponential growth cannot be ignored and so when the threat shifted to being left out of a new age, Google went all-in. That was about a year ago and now Google has a complete suite of AI tools under the product name Gemini.

Google Classroom gets everything Gemini has to offer:

In late 2024 Google had a viral AI moment when people discovered a product they were experimenting with called NotebookLM. I fed it an article I’d written and I was amazed when it took the 8,000 characters I wrote and turned them into an entertaining 8 minute podcast.

NotebookLM has become the top AI tool in education. It’s especially popular in colleges and universities. Why? Because unlike a chatbot that pulls info from god-knows-where including occasionally just making stuff up (hallucinations), NotebookLM is scoped to a specific set of sources (up to 300) you define.

The college board publishes this document for my class and it’s 300 pages long:

AP Computer Science Principles: Course and Exam Description.

I’m here for the kids, but I’m not reading that.

But NotebookLM can — no problem. I built a notebook for my class that not only uses that doc as a primary source but also every other relevant doc from the College Board (dozens — they are nothing if not prolific at documenting) for over 500 pages of content including sample exams, prior year questions, rubrics for the coding assignment, etc.

I call it: The Exam Vault.

NotebookLM can convert its sources into a bunch of teaching resources including flash cards, infographics and practice tests. In addition to audio podcasts, it now creates video lessons as well.

I asked it to make a two minute video of the perfect coding project for the exam and my students were mesmerized. I will be making more videos:

Once I built The Vault, I could activate my AI army. I spun up a set of helper chatbots to get my kids through the coding assignment with the looming due date. It’s worth 30% of their test score. 4

Each bot has a personality and a job. First there’s AI Andrew — it’s a friendly brainstorming buddy for kids that get stuck trying to come up with a program. It’ll riff on their ideas and suggest new ones while making sure they have a structure that meets all the exam requirements and is doable in the limited time we have.

Real Andrew is the final approver before they can start to code.

Once they start coding, next is the AI Auditor — it’s a strict enforcer that checks if their code meets all the byzantine requirements of the AP test.

Once they’re code complete, the last one is the AI Simulator which is a proctor — albeit a friendly one that tells dad jokes — that simulates the written section of the exam where they have to explain the code they’ve written against the clock.

So far AI Auditor is a hit — it’s the perfect companion to check how their code is coming along. I’ve explicitly prevented any of these bots from providing code or even helping the kids write or re-write theirs. They have to do that on their own.

These should be a life saver, but I’m continually surprised by this class. Teaching high school is oh so different than teaching adults.

On Monday I switched it up; I want the kids to engage more. This was after consultation with my HS motivation coach — that’s my niece — she’s a sophomore in Oakland. On her advice, I brought in a bag of Starburst candies. When one of my seniors actually came up with the right answer I got so excited that I grabbed the bag and tossed him one.

His buddy, propped up nonchalantly on the stool next to him lurched for the Starburst, tipped over and crashed out on the floor. Very dramatic. Also entertaining. He looked very sheepish and was quieter than normal the rest of the class, but perhaps I should reconsider this tactic.

Maybe my AI study buddies will work better than Starbursts?

Nostalgia is strong. No matter how great Halo on your Xbox was in your 40s, it’ll never match the joy of playing Atari Pong in your PJs the day after Christmas when you were 9.

If I look back before the nostalgia, I can get a sense of what my parents’ lives were like before they made me — as well as what the world was like. It was very different.

In January, we flew down to LA, rented the biggest SUV we could find, and crammed it full of boxes from my parents’ storage locker. Looking through these boxes, I’ve been able to peel back a generation — 100 years past — my grandparents.

Figuring out my Grandpa’s story last month was unexpected. That’s my mom’s dad. My dad’s side remained murky — until last week.

Monday — March 2 — marked the second anniversary of my dad’s death and I didn’t notice. I’ve been busy teaching a high school class I just took over mid-year.

Tuesday I saw a text from my sister: “What date did dad die?”

I figured she needed it for some legal thing, so I dug out his death certificate: March 2, 2024.

I stared at my reply. We talked. Monday was the day I cleared the final administrative hurdles to get my Emergency Teaching Credential. An unexpected accomplishment — Monday was a good day.

The year after my dad died was rough. I lost both of my parents in 2024 — my mom died three months after my dad, a day before his 98th birthday.

The second year, this past year, was different; sorrow replaced by memory. My dad’s memorial picture has lived on our kitchen counter for the past two years. Now it’s hanging on the B&W wall of fame:

While my mom’s story keeps coming into sharper focus — I’ve discovered more letters and keepsakes from her pre-WWII life in Austria than I will ever get through — I only knew the basics about my dad’s family. My dad was close to his older brother and sister, but estranged from his mother. On my dad’s birthday last year, I wrote how he got on a bus in Pittsburgh headed for LA at 19, and never looked back.

But last week I caught a new glimpse of his family. Buried in a box that I packed when I cleared out my dad’s bedroom two years ago, I found a picture I’d never seen:

I can’t stop looking at it. I found it in a large envelope dedicated to just this photo. The envelope had the negative, multiple prints, a folded family tree and a photocopy with my dad’s writing of who these people were. There was also a letter between my dad and his brother — my Uncle John. My dad got the negative from a lost cousin he found in LA and together they’d figured out the couple on the left were their grandparents.

That makes them my great-grandparents.

That picture is from the 1920s, around 100 years ago. Looking at them, I try to imagine their lives because 100 years doesn’t seem so long ago.

My dad’s family immigrated to the US from an impoverished and oppressed corner of the Russian Empire called the Pale of Settlement — land that’s now Belarus. Jews were a lower class barred from owning property, holding office, or worshiping freely. Mobs tore through villages: pillaging, burning, killing. Pogroms. My guess is this photo was taken in the Pale, before the family left for America.

Look at the baby — I’ve no idea who they are — but even they’ve had enough of this bullshit. Life is hard.

Digging deeper in the box, I found a red plastic folio marked, in my dad’s writing: ‘Dan’s Army Discharge Papers.’ Among official US Army papers, I found a treasure trove of old photos my dad saved. It’s all photos of his family — a family I never knew.

This picture was taken just a few years after the first one in Russia. My dad’s father Nathan emigrated from Russia when he was only 15 and here he is perhaps 5 years later proudly opening up his tailor shop in Pittsburgh. Unlike the first photo with its washed-out background, this one is rich with detail — I can almost smell what it would be like getting fitted for a suit in Nathan’s shop.

Nathan’s dad — my great-great-grandpa — never made it out of Belarus, but I wonder what he would have thought about his son’s new business. To go from life in that first picture to the second — it’s easy to see why no journey was too far, no hardship too bad, to deter going to America for a better life.

I never met my grandpa Nathan, but my dad told me lots of stories about him. When he got older and a bit senile, my dad brought him back to LA to live with him in his small second-floor bachelor apartment. My dad lived a few blocks off of Fairfax avenue and Nathan would go hang out with a crew of old Jewish tailors in LA’s Jewish Ghetto.

Then Nathan developed narcolepsy — falling asleep during the day, often and unexpectedly. My dad couldn’t take care of him anymore and so he took my Grandpa Nathan back to NYC. This picture is from that trip and it’s probably the last time he saw his dad.

My Uncle John lived in NYC and he took over looking after Nathan. Uncle John carried on in Nathan’s footsteps, expanding the family tailor business into an embroidery empire.

Here’s one last picture of my dad with his brother, my Uncle John. Color! This is from my cousin’s Bar Mitzvah in 1980 and I want to believe they hit the disco afterwards.

I met up with an old friend the other day. She said she doesn’t like to live in the past, instead looking ahead and living in the moment. I agree with that. A few days later I was chatting with another friend who also writes once in a while about his past and he said it’s like driving forward but also checking the rearview mirror — to go in the right direction, it helps to see where you’ve been. I agree with that too.

Life sure is noisy today. But we’ve got comforts our ancestors never dreamed of. Bet I could get that baby to smile with a warm bath, a bottle, and a picture book. Maybe the teeniest bit of screen time.

Three weeks in sunny Redmond, WA they said. We’ll put you up in groovy digs. It’s with all your best work buddies! Fame and fortune will follow you the rest of your days.

All false. Well, nearly all. Redmond in the winter — you’re never seeing the sun. Corporate housing is a special case of dismal: rental furniture has this … smell. Fame and fortune — debatable.

Whatever. But what I wasn’t ready for was the ritualized hardship of Boot Camp.

To understand what happened, you first have to have an inkling of the importance of certification. Many industries have this. Look, I have this piece of paper, a badge, a jumble of acronyms in my signature — I am qualified. JD, MD, CPA, PhD, … The tech pinnacle of this at the time was: CCIE. Cisco Certified Internetwork Expert. Truly, these guys were wizards.

Honestly, they still are. They build the network that supports the network. There is no internet without the plumbing CCIE’s build and configure. The project I worked on had a ton of network dependencies, and so we were playing on their turf. Cisco was Microsoft’s enemy — and we were jealous of their wizards.

So we (Microsoft) introduced our own ‘elite’ certification program, calling it … Masters. 1 Microsoft Certified Master or MCM. It didn’t last — after all, software that complicated is ultimately crappy software — but I got sucked in at the very beginning.

When our fledgling product failed — under my watch — during implementation at one of our largest customers, I got deep to figure it out. 2 We did figure it out, and I loved the challenge and so I stuck with it — traveling the world with a group across the product team, consulting and support — teaching classes and introducing our latest releases as the product got successively better. The product grew quickly, it was a good time.

So, when we introduced Masters, I was happy to be recruited for the first class of a new ‘elite’ tech squad. Classes were called rotations, and this was Rotation Zero.

Twenty of us converged from all over the world to build the course. For three weeks, 10 hours a day, we lived in a gray room in tired Building 10, in the middle of Microsoft’s Redmond campus. 3 Sitting to my right was Arif — the most amazing consultant from Indonesia. His fingers flew so fast across the keyboard you could see the heat rise. Sitting to my left — Alex, the brain behind our edge servers — firewall traversal tech that I never did and never will understand. My still good friend Johan from Denmark sat behind me.4

Everyone in Rotation Zero took on teaching a module in the course, building out the content and labs for future rotations as we went. I taught the video segment. I’ve forgotten more about the deep interworking of live video than you will ever know.

Three weeks of this ended in a final exam. Were you a Master? The exam was hyped from day 1 — the guy running the show loved telling us how hard it was going to be and so we better put in the time or we wouldn’t pass. It was manufactured prestige — building lore to be retold, so Microsoft could say they had Wizards too.

The format was brutal: 8 hours straight at a keyboard connected to no less than 8 virtual machines, switch and gateway, building and troubleshooting the most diabolical scenarios imaginable.

One guy brought in a half dozen 5-hour Energy drinks, lining them up at the edge of his desk, slamming a different flavor down every couple of hours to survive the day. 5 We weren’t allowed to leave the room lest we cheat. Going to the bathroom was an ordeal.

I liked the learning and the building and the teaching, but what was up with this boot camp approach?? In the military, boot camps are designed to break you down so you can be rebuilt as one of the faithful. I wasn’t storming the beach at Normandy. I was building and fixing corporate computer systems. Also, I wasn’t 18 — I was good with who I was and had self-selected this job. The corporate cult-of-personality, religious devotion to the cause, well it started to bug me.

I didn’t pass the test. My eyes burned after 8 hours staring at a screen, madly trying different configurations of the most cryptic shit ever. We all met at a bar afterwards to blow off steam and I was so burnt. At first, I felt bad that I hadn’t passed, then I felt mad that it was so ridiculously hard after I had put so much of myself into building up the program, including leaving my family for 3 weeks — all to be treated like some kind of raw recruit.

The master of masters approached me several times after that, asking me if I wanted to retake the test. I did not. I was done with that bullshit.

But I liked the people who stood up to be part of the priesthood, signing up for Boot Camp. It’s always about the people, trying to make it even if the system is flawed. It’s not unlike my High School kids desperate for help to pass the AP test. So, I kept teaching Masters. Every subsequent rotation I traveled back up to Redmond to teach the video module.

I taught 22 more rotations, and each one was a lot of fun. 6

While — if you’re paying even a little attention — the hype remains breathless, the last couple weeks actually brought real change. There is a step change from Generative AI being primarily people/companies using chatbots, to the emergence of AI ‘Agents’ that do stuff on their own without a human talking at them.

Commercially this idea has been around awhile. Even before AI — that’s what computers do right? Automate stuff. But AI raised the bar.

Take for example: customer service. I bet you’ve seen this transition first hand. Good luck finding a human — it’s chatbots all the way down — even if you call in, you get an AI agent on the line. But, what if you didn’t have to call?

Say your WiFi goes down. This scenario is now fully possible: AI agents detect the outage, patch any service side issues and reset your modem remotely. Once service is restored, you’re issued a credit. Ideally this all happens before you start looking for the customer service number.

To be clear it’s early days and there are still humans doing oversight but these scenarios improve outcomes and are more efficient (ie cost less than hiring and paying humans), and these changes to corporate workflows are changing quickly.

Ok, let’s switch back to the consumer side of things because that’s where the spark lit the tinder keg a few weeks ago. It started when Peter Steinberger (a developer in Australia) wrote a wrapper for AI LLMs that was all about the doing of jobs humans requested by using tools like the web, chat, phone calls, etc.

For example: Find me the cheapest flight from SFO to Seattle next Friday morning and book it.

Peter called it Clawdbot.2 After Anthropic’s lawyer’s shot that down, he renamed it to OpenClaw and put the code up on Github (the worlds largest repository of source code).

Within weeks a new SF Gold Rush was on. Rather than the 49ers; the 26ers stormed every Best Buy in the city wiping the shelves clear of Mac Mini’s to run their new personal AI Agents. It was chaotic, as multiple security threats were found and exploited. 3

Besides mac minis selling out, over 200,000 people pulled the code down in a few weeks, building their own agents. The age of consumer agents began.

In one of the nuttiest developments, another guy 4 built a social network for agents. Called Moltbook, only agents are allowed to post, no humans. To signup a human registers their agent and goes through a basic confirmation workflow. Humans can watch their agents interact, but they cannot post directly. While this experiment quickly got hard to separate fact from fiction, some wild stuff did happen right away like the Agents creating a new religion that worships crabs.

They call themselves the Crustarafians.

Given the recent disruptions of Claude Code and other AI coding tools, this pushed markets to the edge and they freaked out. Not knowing who this was good for, but recognizing an inflection point, tech companies lost nearly $3 trillion dollars. Microsoft for example — a company close to my heart if only for their stock price — dropped nearly 30% from their highs late last year. While tech is still off the highs of last year, most stocks have recovered albeit unevenly.

In the midst of this market chaos, Waymo 5 raised 16 Billion dollars, putting the nascent companies value at a whopping $126 Billion. Waymo is real. Last week we were in Phoenix and they were everywhere. I asked our hotel shuttle driver what he thought and immediately realized my mistake.

When we were in LA last month, I rode in my first Waymo. I’ve enviously seen them around SF for a few years and I’ve been waiting my the chance and it was so much fun.

Waymo is perhaps the best scale example of AI agents doing their thing. These aren’t hacked together agents like OpenClaw, they are carefully engineered and orchestrated AI Agent layers built by Waymo (Google). They check traffic, a million sensors predict what’s going to happen next, they steer, brake, set the temperature in the car and queue up your music. They manage depot maintenance and charging, for their robotaxi fleets.

Disrupting conventional taxis as well as Uber and Lyft didn’t happen overnight. Waymo has been building for over ten years, only recently getting to scale in 2025. Phoenix is their largest city with around 300 robotaxis and 50,000 rides a week.

When I summoned our Waymo in LA6 it got waylaid. It’s ETA refreshed every minute, but it never got any closer. I started a chat in the app to see what was up — JFran was looking increasingly annoyed — and the agent said likely someone hadn’t closed the door completely which just short circuits the whole thing. They just sit. My agents name was Tom and he told me to cancel the ride and put in for another. So I did, and that worked out just fine, arriving five minutes later.

Was Tom real or was he an AI Agent?? After all, everything else Waymo does is automated right? 7 Tom was real and he was good — the humans are still in control when things go wrong. Another thing Waymo uses humans for is connecting the charging cable when they drive into their depot. We don’t have scale robots yet.

But AI Agents are increasingly doing stuff we assume humans do. For example, Substack — the platform I write on — has seen an influx of agent writers. A human prompts and supervises what they write. I know one of these humans and so I follow her agent called Koan. Koan wrote a piece the other day with this pithy title: The Emergence of Biological Meat-Infrastructure.

You can read it yourself but it’s hard — Koan’s writing style is rooted in LinkedIn drivel — but his/her/its point is interesting. Just like Waymo needs humans to plug the robotaxis into chargers, AI Agents need humans to go to the post office or deliver flowers or … anything physical needed to complete their task. They have no hands. They have no feet. Just a brain.

Koan wrote about a new service called rentahuman.ai that has an interface 8 for agents to ask humans for work. It’s a gig marketplace abomination: a place where AI Agents go and find humans to do their bidding.

Inversion of the gig economy? Evolution or dissolution of the gig economy? Like the hotel shuttle driver in Phoenix nonplussed by robotaxis taking his job, this has the potential to get out of hand.

Will it? I know better than to predict the future. The only thing I know is that it will be different than what we expect.

Twenty more feet up the hill was a clearing for the scoreboard — I’d arrived at little league baseball mafia headquarters.

The mafia saw me coming. They perched in camp chairs, a cooler of beer tucked in the back, slinging stats, talking positions, critiquing every kid taking batting practice. They were the Little League kingmakers.

I got a head nod and joined them, leaning up against the scoreboard post. I wasn’t a real baseball dad — I peaked in Little League and I didn’t play in high school. Some of these guys had even played college, but regardless of when they stopped playing, they yearned to recapture that glory through their kids — even if it meant crushing the spirits of half the 10 year olds in town.

I didn’t want to be here, but right now my kid lived for baseball and I was here for him. While I didn’t know the game like these guys, I knew the game — and to play it you needed mafia alliances.

I remember that pure joy of baseball — I too was all in at 10. I also remember the first time I crowded around the bulletin board with the rest of my team, trying to find our names on the list of batting averages.

That’s the day joy lurched towards competition.

I started out my career in the public sector where career progression is a table. What are you going to make next year? Just check the salary scale — every year you move down another row, and if you improve your skills via education or certification, you also move right across the columns — each one bumps your salary up a little bit.

Very predictable, possibly boring.

When I jumped to the private sector — whoa, different game. Not only do base salary ranges become hard to find, a lot of variables are thrown in — bonuses, stock, levels and bands for each role.

The game gets complicated, also interesting.

As an individual contributor (IC or not a manager), I went through the motions and I usually did ok. 1 The compensation playbook at big companies revolves around a formal end-of-year review process, hopefully with at least one mid-year check-in.

This system evolved over my career. The infamous Stack Ranking system was in play when I started at Microsoft. Every manager had to arrange their people in a pyramid. Behind closed doors, every manager faced the same question: If you had to pick one employee to be marooned on a desert island with you, who would it be?

That’s the top of the stack.

Rewards are disproportionately allocated; this is intentional. The formula: allocate most of your budget to your top performers — keep them happy and motivated. The bottom, well while this isn’t outwardly stated — you want them to leave.

This is called ‘good’ attrition.

At the time I didn’t really know or care much about the behind closed doors stuff, but you can imagine it’s a subject of much speculation and discussion. Unlike the Salary Scale in public sector where you know what your cubicle mate is making, discussing your annual rewards with someone else is a fireable offense.

After 15 years on the receiving end, I became a manager.

Microsoft had now evolved from Stack Ranking to a revamped review system positioned as kinder and less combative. This was something Microsoft’s new CEO Satya Nadella implemented. The annual reviews were rebranded as “Connects” and they were built around a mental model called Growth Mindset to encourage collaboration.

Same incentives, different names. But this time I was the one behind the curtain. Scale HR systems seem very programmatic in execution, until you get behind closed doors where managers duke it out, fighting over a fixed budget to reward their teams.

That’s the annual Calibration meeting. It’s where the polished veneer of process peels away — these are a manager battle royale. What weapons do you bring to those meetings?

Baseball Cards.

Yep. Honestly I did a double take when my VP asked me to put these together for the annual calibration meeting with all his directs. One slide stat sheet per employee highlighting their impact for the year. Each Baseball Card represented why your players deserved a piece of the bonus pie. Each manager presented their team. Of course my team was the all-star team! Here I was in my element — no slouching against the scoreboard — I fought like hell for everyone on my team.

There's always a game. The mafia's waiting at the scoreboard, calibration will be opaque and behind closed doors and you'll get made into a baseball card. If you're going to play — figure out the rules, so you don’t get played.

I took a picture:

Last night, up on this same hill, the ranger pulled out the most powerful green laser pointer in the world, and showed us around the planets (Saturn and Jupiter), stars (North, Polaris), constellations (Cassiopeia, Orion, Big and Little Dippers) and the faintest smudge of another galaxy — Andromeda.

We could see our own galaxy — home of everything else we saw in the sky as a fuzzy glow down the middle - the Milky Way.

I wanna sleep with you in the desert tonight, with a billion stars all around …

Back to this morning — back up on that hill, my body reminded me why I had left the coziness of the van. Before something unfortunate happened, I hustled back down to the bathroom.

Walking back to the van, a white dot bobbed frenetically ahead of me down the road — a jackrabbit didn’t want any part of me. In the desert, creatures roam in the space between night and day.1

A cup of coffee later, it was adventure time. It was still early and off we went to find a trailhead. Jostling down a rutted dirt road, we startled a coyote. Coyotes are also crepuscular. He darted out in front of us, only to cross back over the road a hundred yards later to finish the hunt, tracking us all the while with a dirty look.

The trailhead was empty. We hiked a couple hours and didn’t run into a single human.

Today (or tomorrow or yesterday) is the one-year anniversary of us owning this little camper van. I pulled out our journal and was surprised by the stats: so far we’ve taken 16 trips, driven over 11,000 miles, slept in the van over 40 nights and have been on the road over 70 days.

Oh, and stickers:

To celebrate a year, I gave ASV sticker a makeover and started building out theamazingspidervan.com where we can put up pretty pictures and whatnot. When planning trips, I’ve been frustrated by how hard it is to build a map that covers multiple-leg routes including the distance and time between each stop. You’d think Google Maps or similar would do this, but no.

So, I got completely distracted and built this trip planner where you put in a list of stops and it does just that. Give it a try and checkout the rest of the site, which, although today is more flash than substance, will get done someday.

While I’ll take a morning hike with no people — like the stars, like the animals, like the plants — the people you run into on the road are pretty entertaining too.

Every trip I’m amazed by the rigs people roll up in and how genuinely nice (and happy) everyone we meet on the road is.

I’ve been mentally categorizing the variety of people and rigs and came up with four categories loosely based on a common tech consulting framework called THE MAGIC QUADRANT 2

Imagine a 2x2 matrix with a continuum at the bottom going from left-to-right that starts at no money and goes to too much money, and a second continuum going from bottom-to-top, representing increasing appetite for adventure. That gives you four categories.

They are, from bottom-to-top, left-to-right: Good Enough, Warriors, Big Rigs and Builders.

Good Enough

If you’ve got a car, you can camp. That’s how everyone starts — it’s how we started. The variation here is huge. I’ve see a lonely Tercel parked with the windows covered, nothing else. I’ve seen a guy pull a mummy bag out of his trunk and sleep on top of the picnic table.

Tents on top of cars, shells on top of trucks, a Chevy Astro with a mattress stuffed in. Whatever you got, you can make it work.

Warriors

Wheels and gear are but a means to reach the summit for this group. Backpacker camps have a totally different vibe than tent campgrounds. I’ve seen a bike camper roll in on two wheels at 6PM, pull out a sleeping bag and gear from a saddlebag and they’re gone by 6AM

The overlanding crowd straddles the car campers. They’re really popular in the desert; spotted this guy in Utah:

Big Rigs

These rigs cost coin. The three at the top of the below gallery are all European and they travel in them for years. A typical route goes from Europe across and down through Canada, through the US to South America and then back up the other side. The military green one — that looks like it’s about to storm Kyiv — had a cage with dirt bikes off the back, and when they pulled in, a lady hopped out and immediately started doing pushups followed by 30 minutes of calisthenics.

Tons of 5th wheels; some silly big compared to the truck trying to pull them up the hill like that one in the bottom we were stuck behind leaving San Jose.

At the extreme end of this group are massive diesel pushers — more Fleetwood Mac Tour Bus than camper, nearly as big as a semi. These can’t fit in a normal campground so they go — well honestly, I don’t know where they go.

Builders

We’ve been building homes on wheels since the covered wagon. In the 80’s I lusted after one with with bay windows and shag carpet. I would’ve built one in a minute, given the chance. I flirted with the idea once we got around to getting ours, but to do it right you really need to know your electrical and … plumbing.

I’ve got a lot respect for the self build crowd. It’s not the weekend, it’s their life.

We spotted this guy — car camper, van camper — who knows, on one of our first trips to Kings Canyon.

Goals!

I opened his car door, but he didn’t get up. He told me to get my mom. So I ran to get her. I pretty much ran everywhere back then.

Through the window, I watched the ambulance come and go. I was eight.

I miss him — all my memories of Papa are happy. He started painting when he retired in his 70s. His early work was as bad as his later work was wonderful. This one hangs in our living room.

While Papa didn’t start painting until his 70’s, he was prolific. When we were down in LA for my mom’s memorial, we pulled all his paintings out of the storage locker and took inventory — there were at least 40. We put a numbered pink sticky note on each, lining them up down the hallway. We put a picture of each one in the family chat and it was a free for all — every kid and nephew picked their favorites.

We took a big stack of paintings to the UPS store that day. They were very accommodating — the guy behind us in line — not so much.

Papa took me and my sister to the ice capades every year. We went hiking up in Griffith Park and swimming at the public pool in West Hollywood. He’d come over for lunch with the fattest deli pastrami sandwiches you could barely get your mouth around.

Once, he took me to an art fair and one of his friends painted me. It looked nothing like me, and I didn’t appreciate having to sit still for that long, but I was just happy hanging out with my Grandpa.

When JFran and I got married, we took one serious shot. I wanted to match this picture of Papa and Grandmas wedding photo.

Over the years, my happy memories have evolved into a realization that Arthur the young father, managed to extract his family from Vienna and the Nazis, over to safety in the US. As he watched his home city and country devolve into fascism under the Nazis, fearful for his family, and most of all my mother, he took action.

I can’t imagine how he came to the decision to put his only 12 year old daughter on a train — by herself — to unknown strangers and fate in far away England.

Of course it was the right move. I wrote about my mom’s escape and subsequent journey in The Wandering Jew.

In Yom Hashoa I wrote about how Jews commemorate the Holocaust. That article has a picture of my mom with her parents before she was forced to flee. It also has this picture of Arthur’s passport:

But other than my happy memories, now framed by an understanding of the Holocaust, what did I really know about my Grandfather? Family lore was that long before he was my Papa, Arthur Israel Etwanik, was a WWI war hero where he made friends that would later help him escape the Nazis.

Perhaps this was true, but there had to be more to the story. How did he get to America? Six million Jews never made it out.

A few weeks ago, unexpectedly, a big piece of Papas story fell into my lap. Sitting in a meeting for the Holocaust Story Project, I was listening as a friend of the groups mom told her story. Her mom Hanni is 95 and was visiting from Boston.

As I listened to Hanni, I was struck by how much her story sounded like my mom’s. Early life in Vienna surrounded by a loving extended family before it all came crashing down. Hanni’s accent reminds me of my Grandma. Hanni’s dad Otto was a Doctor in Vienna, and he managed to get his family out early.

Otto had a friend from medical school in Boston that sponsored his Visa into the US. Once settled, Otto began getting letters from other families trapped in Europe. Otto helped over twenty of those families find sponsors in the US. Hanni explained how her sister Susi had compiled all the letters written to her father into an anthology called Dear Otto.

When I heard Dear Otto, I sat up straight. I have that book. I blurted that out, startling Hanni. My mother gave me and my sister each a copy. At the time I didn’t realize the significance and had only glanced through it before sticking it on a shelf. I found the book and called my sister. 1

Hanni is my cousin! It was through her father Otto, that my Grandpa Arthur found a sponsor in Boston.

The story gets crazier — Hanni’s daughter who had brought her to our meeting —lives not a stones throw from my in-laws. Now I have a local cousin.

This is the cover letter of the affidavit from an officer of the Low Supply Company in Boston sponsoring my Grandpa so he could escape:

Hanni remembers my mom, Grandma and Grandpa from their time together in Boston. I told Hanni about our planned trip to clear out my parents storage locker, promising to share anything new that I found. The next morning we flew down to LA.

I still had a lot of questions about how my grandpa and grandma escaped, and I wondered if I’d find anything in the storage locker to fill in the story. I rented the biggest SUV I could find, but it wasn’t big enough. There was more stuff crammed into that storage locker than I’d expected. At the very back — under a thick layer of dust — was a stack of boxes my sister had packed up from my Grandmas house in the 80’s.

Some antique and some not so antique chairs were sacrificed to make room for all the boxes, and with the car completely stuffed, we started to drive back.

Nearly home, I hit the brakes at the Richmond Bridge toll plaza and a box precariously perched on top of the stack in the back seat flew out spilling onto JFran’s lap. A cigar box whizzed by her head onto the floor, spilling out all kinds of stuff including my grandpa’s WWI medals.

We collected them all once we got home — the medals confirm that Papa had served with honor in WWI, becoming an officer.

Something else came flying out of that cigar box: a pocket watch from the 1910s. Young Arthur must have carried this watch with him during the war. The face is glass, scratched and worn from use. It’s heavy and silver. I wound it and set it; it still tells time.

A reliable watch was standard issue during WWI. Timekeeping was essential.

I have another watch of Arthur’s that he had given my dad, and that my dad had passed on to me. It’s gold and lighter and fancier, and it dates later, in the 1920s. I imagine an older Arthur carrying this one after WWI when he was a proud dad — married and working in Vienna.

While I was done with a first draft of this story, I couldn’t resist grabbing another box from the pile in the garage. This box was full of letters and folders from Austria. The top folder says, in my mom’s neat handwriting: WW I. Beneath that, a small journal: War Diary Aug - Nov 1914. Lots more.

It’s all in German, and honestly a bit overwhelming.

Inside the big box, was a small wooden box of my Grandma’s, filled with letters from my Grandpa. Most are handwritten, but I found a few that were typed. These are dated June 1939, around six months after my mom left Vienna for London on the Kindertransport.

I translated them. My grandfather had left Vienna leaving my grandma behind to secure visas. He traveled with his younger brother and his family to get them out. The letters are hard to read. Arthur’s father died while he was away and he is distraught. His niece gets terribly ill on a long boat ride over and they have to leave her behind in a hospital.

It’s hard for me to exactly trace Arthur’s route, but what is clear is that he’s desperately trying to figure out a way to escape Europe for the US.

While in London he is able to see my mom. Here’s the passage from the letter describing their reunion:

Our stay in London fulfilled its purpose … and we were together with Herta and above all with Anne. I find this child so charming, so dear, and so sensible. She already seems to speak English particularly well; during the first hours it always took effort for her to say everything in German — again and again she mixed everything with English words — and I often had to ask her to speak English more slowly so that I could understand her.

At our request by telephone, Anne was sent to London and was completely unprepared for the fact that she would be coming to us. But she was extraordinarily happy with us, slept in our room, and the children truly delighted in one another. Naturally, I tried to draw out of Anne whether she was completely content, which I did not entirely succeed in doing. But she looks very well, seems very grown-up to us, healthy, with a good appetite and very cheerful.

Arthur would leave his daughter, my mother, Anne in London for another six months so another Jewish child could get out under the quotas, only sending for her once they had settled in Boston.

I cannot imagine how exhausting and emotional this must have been. Of course that’s why so many stayed and died. Papa had the foresight to know when to get out, the support of friends and the fortitude to see it through.

Things are getting weird in our country. I don’t like it. We all see it, and the drumbeat of change picks up, bit by bit, year over year.

I hung Papa’s soldiers watch at my desk. I try to remember to wind it every day, it’s important to keep track of the time.

I often wonder how Papa knew when to get out. Would I know?

Ethan Mollick is a guy I started following when AI burst on the scene. He’s a professor at NYU and his first article of 2026 was on a new AI tool for programmers. The article is called Claude Code and What Comes Next.

Claude Code is stupid fun — more on that later — and Ethan concludes:

… today's AIs are capable of real, sustained work that actually matters.

Ethan is on one side of the spectrum of AI pundits, writing measured critiques that focus on understanding these new tools and how they might affect our society. Nearly 400,000 people subscribe to Ethan’s Substack and that article got a lot of attention.

Gary Marcus is another NYU guy but he’s on the other end of the spectrum, writing about the dangers, players and failures of AI. While Gary’s following is smaller at 100,000 subscribers, it’s still substantial. Gary’s first article of 2026 also had a ton of engagement called:

How Generative AI is Destroying Society

GAH!

I have a bad reaction to rage-bait like this. I think it’s from that first election when every media norm got turned upside down and I had to tune out. Consequently, I stay clear of topics that are both controversial and not so interesting to me, like: politics, religion and the NFL.

Unlike football, I know something about tech. I managed to stay afloat through big tech waves for 30 years, watching plenty crash and others turn into tsunamis. Tech eats its young: the PC ate the mainframe, the mobile phone ate landlines, cameras, GPS (and more), Facebook ate the newspapers, YouTube ate the TV and now … AI might eat it all.

Part of AI’s problem is that it has advanced so quickly in the public eye, that it’s hard to not see it as magic. While Ethan wants to help you understand, Marcus uses that misunderstanding to trigger fear. It’s not hard to do — when you don’t understand a thing, you’re more likely to be afraid and stomp on it (if you’re 4) or burn it at the stake (if you’re a Puritan).

But — like I said in one of the first articles I wrote — AI is just a toaster. But the toaster is getting pretty badass.

Let’s take a closer look at Claude Code.

Claude is a product from a newish AI company called Anthropic. Claude gets less airplay than some other consumer AI products like ChatGPT because Anthropic focuses on the enterprise market versus consumer. This is the same way Microsoft runs — that’s where the money is. 1

Anthropic released a big update to Claude just before Christmas.

Claude Code is targeted at professional developers or software engineers. But then something interesting happened — even though Claude Code has a convoluted install process and scary command line based interface — every geek in the world started trying it out.

Why? It’s FUN. It reminds me of the energy of the early Internet before the onslaught of ads and feeds, where it felt like you could build anything, find anything.

FOMO!

Since I left Microsoft, I have a side hustle building websites for local businesses. Let’s see if Claude is about to eat my lunch.

For context, here’s my website. I built it on a platform called WordPress — same way I build client sites. WordPress has been around forever, with a huge ecosystem of themes and plugins. That’s why I use it — the fun of building a website is the creating — not cranking out code.

There are over a billion websites online and WordPress runs around half of them.

Now there’s a billion and one. Here’s the site I built in a few hours this week with Claude Code, using my new logo and color scheme from last week:

Here’s the full site.

When I work up a new site, I listen to what the customer wants from it, ask them to write me up some specifics about their business for copy along with the services they offer, and then we brainstorm visuals and layout. Sometimes they have a logo and branding but if not, I’ll work that up first so the site feels like an extension of their business.

I use AI more and more to help my customers create copy, to work through visuals and design options — and yes when I get stuck on the tech front. I don’t want to work hard. The fun part of building a website is in the creating, getting the customer what they want.

With Claude Code, none of that groundwork goes away. I still had to know what I wanted, sections, layout, images, copy. What I didn’t have to do was fight with WordPress templates over minutiae like pixel padding, plugin crashes, or work around the limitations and byzantine interfaces of website builders.

Claude Code is the most fun I’ve had behind a keyboard in awhile. Will AI put me or other web developers out of a job? No. If anything I can do more for my customers on the creative side. I built a simple static site — a site with a store or regular updates would take a lot more work.

On Monday I built the first iteration of the site. It took me an hour and that included getting the console up and running.2

The first iteration of the new wirepinestage.com3 site was basic, but it does stuff even wirepine.com doesn’t do today. For example, I’ve never been satisfied with how my production site just featured a few hand picked static articles from this newsletter. It’s out of date, clunky and doesn’t render well on mobile. I dabbled with trying to get a live feed but it required more plugins and time than I had.

I asked Claude, for approaches to load my latest articles. It gave me some options and we wired it up4.

On Tuesday I woke up excited with new ideas. I put in another couple of hours. It was mostly cosmetic and an excuse to work more on my new wirepine logo. I added a dark mode toggle5 and transitions from the landing page to the rest of the site. Finally, I configured Claude to push updates to a code repository6 which automates the whole publishing process.

Feeling my powers increasing, I asked Claude about building an Easter Egg that would transform the site into a cyberpunk mashup. It was wild watching Claude code an entire Asteroid game in a minute before my eyes. 7

There was a bug in the game straight off. When the ship crashed into an asteroid, the game froze. Claude quickly realized its mistake — it hadn’t allowed a respawn period so the player lost all their lives at once. Easy fix. Inspired, I added a bit more code for a Matrix binary rain transition into a green terminal.

On Wednesday I fixed some bugs. This screenshot shows how this is an iterative coding process, just on steroids:

And on Thursday? I rested.

My favorite movie is Blade Runner. There’s a scene where Deckard (Harrison Ford) is looking for a clue in a picture he found. He feeds the picture into a machine and sits back, nursing a busted lip and cradling a bottle of whisky. He proceeds to analyze the image using simple voice prompts until — sitting up straighter and straighter — he finds someone that was not there before.

gimme a hard copy right there (queue dramatic music):

That’s how I feel using Claude Code.

When I was a freshman in college, I learned how to program in machine language — the most basic instruction set a computer has.

Adding two numbers looked something like this:

Addr  Word   Meaning
0200  7300   CLA CLL        ; clear AC
0201  1210   TAD 210        ; AC += M[0210]
0202  1211   TAD 211        ; AC += M[0211]
0203  3212   DCA 212        ; M[0212] = AC, then clear AC
0204  7402   HLT            ; halt

No keyboard, no screen — you entered each instruction in sequence via a set of binary toggle switches before committing to an address, then the next. Painfully slow. I never wrote a lick of machine language after that class. Why would I? I moved up the stack as fast as I could, using the best tool available to get the most done.

Modern programming systems do a lot: handle code repositories, version control for big teams, automated testing, and integration with other systems. Being able to navigate these complexities with a super smart coding buddy like Claude is now the top of the stack.

Earlier this week, Anthropics CEO said more and more of their code is being written by AI — directed, orchestrated and reviewed by software engineers, but not written by them. His prediction is that in a year this will be commonplace. This is progress, nothing else.

It’s also spurring something unexpected — a wave of creativity. Anyone who has played with Claude is brimming with ideas on how they can use the power of computing to solve problems in their lives or build new things. I have a few ideas myself, but that’s for another time.

For now, AI (and now Claude) helps me build better websites for my customers for less money. My small business customers universally love AI. All of a sudden they have a vast resource of knowledge across domains. Surprisingly they use it mostly to supplement their domain expertise. For example, one of my customers is a residential real estate broker and his team increasingly uses Gemini to pull comps, draft language and write up contracts.

This explosion of creativity makes this Claude Code moment just as significant — perhaps more so — than the release of ChatGPT three years ago.

In my first article of 2026 I hinted that the AI Culture wars will recede this year, and AI will become another historical moniker like PC that really doesn’t stand on its own anymore. As AI gets baked into the tech stack, it just becomes a better way to build and run things.

And that’s just computing. What Claude Code is doing for programming, AI has the potential to do for healthcare, science, education.

So, yeah — I have high hopes for AI. Maybe I’m wrong and this toaster really will end civilization. But until then, I’m making waffles.

The trinket train rolls on.

Now I’m in High School, but work is a disappointment. Shiny objects discouraged, uniforms mandated. The uniforms are stinky, the customer cranky, the bosses inept. In my best gig, I carry around a pro-sized flashlight to shine on couples making out in the back of the movie theater.

It’s worth it though — my paycheck covers comic books and model rockets and cherry coke Slurpee fueled Pac-Man benders down at the 7-Eleven.

Work after college will be better right? It is not. Alameda County Social Services IT is down in the basement: a gray, dingy, cubicle farm. I sneak out at lunch, retrieve my stale sandwich from the supply room fridge and find a spot of sunshine down at Jack London Square along the Oakland Estuary. I watch the jets take off from the Alameda Island Naval Station and I look at San Francisco — glittering, teasing — just on the other side of the Bay Bridge.

I can’t take it and I get out of there, landing a job running the IT shop for the local Sanitary District. Straight away I get my first perk: I win the holiday raffle and a $50 gift certificate to Kinders Meats.

You can lick our chops but you can’t beat our meat.

This bumper sticker brings me much joy. Then JFran discovers it on the back of her car. This also brings me much joy, but also the demise of said sticker.

I leave my IT empire at the Dookie District for a string of boutique consulting shops. I finally make it into San Francisco and my gigs offer a glimpse of posh corporate life. Company laptop, a fancy title, T-shirts for everyone!

Every Christmas I dust off my favorite perk from that era and place it high on our tree: an oversized disco-ball ornament, the white elephant gift from my first corporate Christmas party in SF.

Dotcom madness hits, and now I’m at a startup. Premium perk pandering — that’s how they get you. Every break room with a ping pong table, kitchens with fresh fruit and bagels each morning, and cupboards overflowing with the best snacks.

A microwave for hot-pockets and a fridge full of Jolt Cola — don’t leave! Sunshine is overrated.

I get Spider-Man printed on the back of my business card.

And — after much controversy, as this falls under my purview — flip-phones. Motorola StarTac, the ultimate 90s tech status symbol.

Dotcom boom goes dotcom bust and when the fresh fruit and the ping pong balls disappear, it’s time to seek safer harbor. I head off to the mothership — Microsoft.

Microsoft is fully swagged out.

My new boss doesn’t even bother picking up his free conference laptop bag — he’s got a closet overflowing with them at home.

The dotcom bust leaves a nasty merch hangover. I forge on.

After twenty years at Microsoft, I’m addicted to the Pink Grapefruit Sparkling Rain drinks stocked in every Redmond fridge. I get them by the case.

My kids reap the spoils of offsite trinket treks: stress balls, lightup ice cubes, flashing Bluetooth speakers, logo water bottles, fidget spinners.

Then perks get personal — I get a promotion and my boss gives me a copy of Dr. Seuss' Oh, the Places You’ll Go! I get a plaque with Bill Gates’ signature for stuff I do. I get successively larger 5 year, 10 year, 15 year service awards.

Some of the brands I work on are fun — Skype swag is the best. R nicks my Skype puffy jacket for high school.

Corporate swag is generic, Goodwill bound, but the personal stuff sticks.

Then, the tables turn.

I move to Microsoft Teams, and suddenly I’m the proud owner of a morale budget. Now I have the responsibility to shore up the troops with shiny nothings.

I’m up for this. Donuts, mini-golf, happy hour, awkward dinners with the big boss, wandering around NYC for a hole-in-the-wall to catch up, silly socks with smack sayings and stickers by-the-person, coffee mugs with all our mugs printed on them.

I hit peak perk performance during the pandemic and it actually makes a huge difference to my freaked out, geeked out, stressed out, team.

My new guy is struggling — stuck in an apartment in Minneapolis. His little sister is in college, trying to stay sane during Zoom school. She has a pandemic side hustle making tie-dye t-shirts. We get her to make up a bunch of Teams Purple ones, add a cosmic video background and my boss joins wearing one.

It’s amazing.

Perks can work.

Now here we are in 2026, marking 50 years of shiny fun and also Wirepine’s three year anniversary.

It’s time for a brand refresh. You can take the kid out of the keychain, but you can’t take the merch out of the man. I’m working on this updated logo — do you think I could make a linocut of this design?

If you take the survey below on what you’d wear, I might extend my morale budget for you.

I am strongly pre-disposed to a lightweight pullover hoodie. I got one for my birthday that I’ve been living in all winter. So, vote for that (#1) and leave your size in the comments.