Sam Says Some Things

Summary

Tech Brew Ride Home — “Sam Says Some Things”

Podcaster: Brian McCullough
Date: February 23, 2026
Theme:
A brisk, up-to-the-minute breakdown of the most provocative headlines in tech, focusing on Sam Altman’s recent AI commentary, changing SaaS paradigms, market risk in AI's advance, and notable AI provider moves.

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Main Theme

This episode centers on the implications of Sam Altman’s bold public statements about artificial intelligence, the economic and cultural friction around AI adoption, and the shifting landscape for vertical AI and SaaS businesses. The show also unpacks real-world impacts—workforce transformation, platform lock-in, and speculative outcomes if AI delivers a rapid, deep transformation of the global economy.

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Key Discussion Points and Insights

1. Sam Altman’s Latest (and Sometimes Controversial) AI Declarations

“Comms Needs to Have a Quiet Word with Him”

• Origin: Indian Express and CNBC TV18 interviews
• Altman’s take on Orbital Data Centers:
  • Calls idea of putting AI data centers in space “ridiculous,” notably diverging from Elon Musk’s vision.
  • “Orbital data centers are not going to matter at scale this decade due to the rough math of launch costs and how hard it is to fix a broken GPU in space.” (Altman, [01:39])
• Altman/Musk Relationship:
  • Altman: Becoming friends with Musk is “less likely” than TSMC losing chip monopoly, but “I feel like I have more control over that one.” ([02:12])
• On AI-driven layoffs:
  • Acknowledges “AI washing”—companies using AI as a scapegoat for layoffs (“some AI washing where people are blaming AI for layoffs that they would otherwise do” ([02:55]))
  • Still, expects “the real impact of AI doing jobs in the next few years will begin to be palpable.” ([03:28])
  • Suggests historical optimism: “We’ll find new kinds of jobs, as we do with every tech revolution.” ([03:22])

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2. AI Layoffs: Myth vs. Reality

• Stats from Challenger, Gray & Christmas:
  • 55,000 US layoffs in 2025 attributed to AI, less than 1% of all job losses ([03:44])
• National Bureau of Economic Research:
  • “90% of executives surveyed said AI has had no impact on workplace employment in the last three years.” ([03:54])
• Public Resistance:
  • Uptake “surprisingly slow” versus what’s possible, per Altman:
    • “There was more resistance to… the absorption of AI into the culture and economy than he expected.” ([04:06])
  • Altman: “I suspect that in a couple of years on almost any topic, the most interesting, maybe the most empathetic conversation that you could have will be with an AI.” ([04:36])

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3. Public and Industry Critique: Tech Bro Tone, Energy Analogies, and Humanity

• On AI’s Environmental Impact:
  • Altman’s comparison: training a human also takes “20 years of life and all of the food you eat… It took the very widespread evolution of the 100 billion people that have ever lived…” ([05:13]-[05:32])
• Pushback:
  • Critic David Besus: “Why does Sam insist on declaring war against his entire customer base?” ([05:53])
  • Kunal Kapoor: “You can see why people are becoming increasingly uncomfortable with the tech Bros… The genius who sees humanity as a system to optimize.” ([06:05]-[06:16])
  • “But people don’t want to be solved, they want to be understood.” ([06:25])

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4. Vertical AI: The SaaS Successor?

• Anthropic Data:
  • Software engineering makes up ~50% of AI agent tool usage, other 16 verticals (health, legal, etc.) all below 9% ([06:35]-[06:56])
• Gary Tan:
  • “That gap between what AI can do and what we let it do is a massive opportunity… The models are already more capable than users trust them to be.” ([06:56]-[07:26])
• Aaron Levy:
  • To unlock value: build “agentic” software for real people, proprietary data, change management, and vertical expertise ([07:51]-[08:14])
• Outlook:
  • “Every one of those [SaaS] unicorns has a vertical AI equivalent just waiting. And the AI versions could be 10x larger because they… replace the operators too.” ([08:35]-[08:43])
  • SaaS unicorn boom could repeat for “vertical AI unicorns” next decade ([09:01]-[09:11])
  • “Users only let them [AI agents] work for 42 minutes. That’s an indicator. We are so early…” ([09:12]-[09:21])

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5. User Lockdowns and Platform Risk: Google and Anthropic Crack Down

• Google AI account bans:
  • Users of Gemini via OpenClaw third-party tool faced sudden bans, even risking Gmail and workspace lockout ([11:18]-[12:49])
  • “No terms of service violation was cited. No explanation for followed. Other users arrived with matching stories.” ([12:29]-[12:35])
  • One user: “I’d have to sue a trillion dollar company just to get a measly fee. I paid nearly $3,000 a year, and the best Google could offer was a community manager…” ([12:58])
• Anthropic mirrored Google, banned OAuth tokens in 3rd party tools ([13:13])
• Token arbitrage explained:
  • Third-party tools “broke those expectations by letting subscribers extract more value than the subscription model assumed.” ([14:24]-[14:32])

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6. Speculative Economics: AI-Driven “Ghost GDP” and Systemic Risk

• Citrini Research scenario, 2028:
  • “Imagine…a theoretical memo…June 30, 2028.” ([15:10]-[15:29])
  • Unemployment at 10.2%, S&P down 38% from 2026 highs ([15:43]-[15:52])
  • Productivity surges, “ghost GDP”: profits and output rise, but doesn’t reach households; “machines spend exactly $0 on discretionary goods” ([16:07]-[16:31])
  • Key quote: “Ghost gdp. Real output on the spreadsheets that doesn't trickle down to households…” ([16:19]-[16:31])
  • SaaS and intermediation cracks, agentic tools “good enough” replace whole market segments ([16:42]-[17:56])
  • Ripple effects: offshoring, service sector wage pressure, private credit and reinsurance at risk ([18:15]-[19:02])
  • “Intelligence premium unwind”: institutions built on scarcity of intelligence upended ([19:25])
  • Policy scramble: “transition economy act,” AI inference taxes, populist backlash
  • “You're not reading this in 2028. You're reading it now, today, in 2026, when the Canary in the coal mine is still alive, but the clock is ticking.” ([19:44]-[19:54])

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Notable Quotes & Memorable Moments

• Sam Altman (on orbital data centers):

  • “Orbital data centers are not going to matter at scale this decade due to the rough math of launch costs and how hard it is to fix a broken GPU in space.” ([01:39])

• On Musk relationship:

  • “I think Musk and I becoming friends again is less likely...I feel like I have more control over that one.” ([02:12])

• On AI layoffs:

  • “I don’t know what the exact percentage is, but there’s some AI washing where people are blaming AI for layoffs that they would otherwise do...” ([02:55])

• On energy consumption:

  • “It takes like 20 years of life and all of the food you eat … to train a human.” ([05:15])

• Bridget Far Laud:

  • “It's almost as if these tech leaders crowing about the end of jobs and humanity as we know it isn't sitting well with folks. Crazy.” ([04:43])

• Kunal Kapoor:

  • “Some of this language starts to echo the architecture type of the technocrat villain you see in movies…But people don’t want to be solved, they want to be understood, end quote. ([06:16]-[06:25])

• Ghost GDP scenario:

  • “Machines spend exactly $0 on discretionary goods, so the velocity of money stops.” ([16:31]-[16:42])

• Warning for the present:

  • “You're not reading this in 2028. You're reading it now, today, in 2026, when the Canary in the coal mine is still alive, but the clock is ticking.” ([19:44]-[19:54])

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Timestamps for Key Segments

• 00:27: Episode theme setup, Altman, SaaS, and a speculative future
• 01:11: Orbital AI data centers — Altman vs. Musk
• 02:12: Altman on Musk feud and TSMC
• 02:49: AI layoffs and “AI washing”
• 03:44: 2025 Layoff data
• 04:06: Altman on resistance to AI adoption
• 05:01: AI’s energy use — Altman’s controversial “training a human” analogy
• 06:05: Public discomfort with “tech bro” AI framing
• 06:35: Anthropic data: which sectors actually use AI agents?
• 07:51: Aaron Levy — The playbook for building vertical AI unicorns
• 11:18: Google bans users who access Gemini via OpenClaw
• 13:13: Anthropic follows suit; Token arbitrage and economics
• 15:10: Speculative “ghost GDP” crisis, 2028 scenario
• 19:44: Present-day warning — canary in the coal mine

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Overall Tone and Final Takeaway

This episode is a fast-paced, slightly irreverent but data-rich walk through tech’s hottest current debates—anchored by Altman’s candid (sometimes awkward) statements and the evolving reality of AI’s impacts. The tone is skeptical, at times wry, and always focused on puncturing hype with hard market data, broader context, and a splash of speculative “what if” to keep listeners both grounded and alert. For anyone watching the AI landscape, this is a primer on both where reality sits and why it may shift, fast.

Transcript

[A]

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[B]

Welcome to the Tech Brew Ride home from Monday, February 23rd, 2026. I'm Brian McCullough. Sam Altman has a lot of stuff to say about AI and let's just say Comms needs to have a quiet word with him. SAS may or may not be dead, but is the replacement vertical AI and a big thought experiment. If the AI bulls are right and AI transforms the economy, what might that look like?

[C]

Here's what you missed today in the world of tech,

[B]

Sam Altman has been

[C]

saying some things and you can do some real tea leaf reading into some of the things he's first quoting the Indian Express in his recent outing With Express ADA OpenAI CEO Sam Altman spoke

[B]

about meeting the staggering future demands of artificial intelligence.

[C]

When Anat Gwenka, executive director of the Indian Express, asked about putting data centers in space, Altman quipped, saying the idea was ridiculous. This is in stark contrast to Altman's

[B]

chief rival, billionaire Elon Musk, who has

[C]

been speaking profusely about moving AI computation

[B]

off Earth into space, specifically into orbit,

[C]

with the help of satellites and solar power. Putting data centers in space the current landscape is ridiculous. Orbital data centers are not going to

[B]

matter at scale this decade due to

[C]

the rough math of launch costs and how hard it is to fix a broken GPU in space, altman told Gunka.

[B]

Other than the massive physical infrastructure of

[C]

AI, the landscape seems to be also shaped by intense personal dynamics and rivalries. Altman's relationship with Musk has been famously fraught. During the interview, Glenn asked Altman to

[B]

weigh the probabilities of two highly unlikely

[C]

scenarios whether Taiwan Semiconductor Manufacturing would lose its global monopoly on chip manufacturing, or

[B]

if he and Musk would ever become friends again.

[C]

Altman was unambiguous in his response. I think Musk and I becoming friends again is less likely, he admitted, adding with a touch of humor, I feel like I have more control over that one. End quote now from Gizmodo.

[B]

Quote Sam Altman is starting to get the sneaking suspicion that companies might be using the technology he's dedicated his life

[C]

to once it turned out to be

[B]

extremely profitable as cover for their own interests. In an interview with CNBC TV18 at the India AI Impasse Impact Summit the founder and CEO of OpenAI suggested that AI has become a scapegoat that is wrongly being blamed for the mass layoffs

[C]

that continue to hit basically every sector of the economy.

[B]

I don't know what the exact percentage is, but there's some AI washing where people are blaming AI for layoffs that

[C]

they would otherwise do, and then there's

[B]

some real displacement by AI of different

[C]

kinds of jobs, altman said. Of course, Altman's gotta thread the needle here.

[B]

He does, in fact need people to believe his company's technology can replace people.

[C]

That has kind of become the whole

[B]

pitch to corporations looking to pour money

[C]

into AI despite little real return on those investments thus far.

[B]

But he also would rather not position his product as a job killer, lest

[C]

he rile the masses who are on edge that their jobs might get axed.

[B]

We'll find new kinds of jobs, as we do with every tech revolution, he added.

[C]

But I would expect that the real

[B]

impact of AI doing jobs in the

[C]

next few years will begin to be palpable.

[B]

End quote that said, Altman is probably onto something here. According to data from consulting firm Challenger Gray and Christmas, about 55,000 layoffs in

[C]

2025 were attributed directly to AI. While that is significant number of people

[B]

out of work, it also accounted for less than 1% of all job losses for the year.

[C]

A recent paper published by the National Bureau of Economic research found that 90%

[B]

of executives surveyed said AI has had

[C]

no impact on workplace employment in the last three years. End quote and then here are the quotes that lend themselves to real tea leaf reading. Quoting the Times, the chief Salesman of

[B]

the AI Boom, Sam Altman of OpenAI, said there was more resistance to, quote the diffusion, the absorption of AI into the culture and economy than he expected. Looking at what's possible, it does feel sort of surprisingly slow, Mr. Altman said

[C]

at an AI conference this month.

[B]

From the point of view of the AI promoters, an inability to relate to human beings is not a defect, but a virtue. Quote I suspect that in a couple of years on almost any topic, the most interesting, maybe the most empathetic conversation that you could have will be with

[C]

an AI, Mr. Altman said, end quote

[B]

quoting Bridget Far laud on LinkedIn.

[C]

It's almost as if these tech leaders

[B]

crowing about the end of jobs and humanity as we know it isn't sitting well with folks. Crazy.

[C]

End quote yeah, and it doesn't help, I guess, to say things like this. Quoting TechCrunch OpenAI CEO Sam Altman addressed

[B]

concerns about AI's environmental impact. This week, while speaking at an event

[C]

hosted by the Indian Express, Altman complained

[B]

that many discussions about ChatGPT's energy usage are, quote, unfair, especially when they focus on, quote, how much energy it takes to train an AI model relative to how much it costs AI human to

[C]

do one inference query but it also

[B]

takes a lot of energy to train a human, Altman said. It takes like 20 years of life and all of the food you eat during that time before you get smart. And not only that, it took the very widespread evolution of the 100 billion people that have ever lived and learned

[C]

not to get eaten by predators and

[B]

learned how to figure out science and

[C]

whatever to produce you, end quote.

[B]

So in his view, the fair comparison is if you ask ChatGPT a question, how much energy does it take once its model is trained to answer that question versus a human? And probably AI has already caught up on an energy efficiency basis measured that

[C]

way, end quote Quoting David Besus why

[B]

does Sam insist on declaring war against his entire customer base?

[C]

That's a truly bizarre positioning for a mainstream business. End quote and quoting Kunal Kapoor, quote I'm very pro tech and his intent

[B]

here is to talk about energy. But you can see why people are becoming increasingly uncomfortable with the tech Bros. It reflects a broader discomfort in how they frame humanity culturally.

[C]

Some of this language starts to echo

[B]

the architecture type of the technocrat villain you see in movies. The genius who sees humanity as a system to optimize. It's turning the human experience into energy and mathematics.

[C]

But people don't want to be solved, they want to be understood, end quote.

[B]

Anthropic's own data now shows that software engineering accounts for around 50% of its

[C]

AI agent tool calls, which is interesting on its own.

[B]

But Gary Tan points out the remaining verticals that compromise that other are what

[C]

is interesting to him and that most founders are overlooking this quote Software engineering

[B]

owns half of all AI agent activity. The other half is scattered across 16 verticals, none above 9%. Healthcare is only at 1%. Legal is 0.9%. Education is 1.8%. These aren't saturated markets, they're markets that barely exist. Here's what should make founders salivate. The models are already more capable than users trust them to be. Metter's capability assessments show Claude can solve tasks that would take a human nearly five hours. But in practice, the 99.9 percentile session

[C]

runs only about 42 minutes.

[B]

That gap between what AI can do and what we let it do is a massive opportunity. Between October 2025 and January 2026, the 99.9 percentile turn duration nearly doubled from

[C]

under 25 minutes to over 45 minutes. The growth is smooth across model releases.

[B]

This isn't just better models, it's users extending trust session by session as they

[C]

learn to work alongside agents.

[B]

Aaron Levy points to the untold wealth and value ready to be unlocked. Build agentic software that taps into proprietary data. Make the software actually work for real people and problems. Stuff that context to maximize intelligence coming out and the part most founders miss Drive Change management for customers. That last piece is why vertical AI is so defensible. Anyone can build a wrapper.

[C]

Few can navigate the specific workflows, regulatory

[B]

constraints and organizational friction to healthcare billing or legal discovery or construction permitting SaaS has grown 10x per decade for a few decades now. Over 40% of VC dollars in the past 20 years went to SaaS companies.

[C]

The industry produced more than 170 SaaS unicorns.

[B]

And so the thesis is simple. Every one of those unicorns has a vertical AI equivalent just waiting.

[C]

And the AI versions could be 10x

[B]

larger because they don't just replace software, they replace the operators too.

[C]

The map is drawn.

[B]

Software engineering is spoken for. Healthcare, legal, finance, education, customer service, logistics 16 vert with single digit market share each are waiting for someone to build

[C]

the domain expertise into the agent.

[B]

300 SaaS unicorns came before 300 vertical AI unicorns are coming next. The founders who pick a vertical build domain expertise into their agents and figure out change management will own the next

[C]

decade of enterprise software.

[B]

The models can already work for five hours. Users only let them work for 42 minutes. That's an indicator.

[C]

We are so early and there is

[B]

a lot more to build. And in so many places that haven't

[C]

even seen a single minute of intelligence in action. End quote.

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[E]

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[B]

users say their paid Google AI accounts were banned after they linked Gemini models via OpenClaw.

[C]

Peter Steinberger says he may remove support for this soon, quoting Duplicator AI Google

[B]

has restricted accounts of AI Ultra subscribers who access Gemini models through OpenClaw, a

[C]

third party OAuth client, according to a growing thread on the Google AI Developer Forum.

[B]

The restrictions arrived without warning or explanation, cutting off users paying $249.99 per month from Gemini 2.5 Pro and in some cases threatening access to Gmail, Workspace and other linked services. The enforcement comes two days after Anthropic updated its legal terms to explicitly ban OAuth token usage in third party tools, including OpenClaw. Two of the three largest AI model providers locked down third party access in the same week.

[C]

Same calculation, same week the forum thread

[B]

that started this carries a title worth reading in full Account Restricted without warning Google AI Ultra OAuth via OpenClaw the original poster described losing access to Gemini 2.5 Pro after connecting through OpenClaw, an open source AI agent framework that routes

[C]

existing subscriptions through alternative interfaces.

[B]

No terms of service violation was cited.

[C]

No explanation for followed. Other users arrived with matching stories.

[B]

Some submitted appeals and received only automated replies. Others couldn't find a human representative at all. One user wrote that they tried creating a fresh Google account, only to discover that one restricted too. No warnings, no nothing. Just a ban after being a customer

[C]

for decades, the user wrote, threatening to

[B]

cancel YouTube, Google Ultra and every other Google product.

[C]

Another described the situation in terms of what it felt like from the inside.

[B]

I'd have to sue a trillion dollar company just to get a measly fee. I paid nearly $3,000 a year, and the best Google could offer was a community manager promising to share this with our internal teams. No timeline, no specifics, and the thread has kept growing. And here is where Google's architecture turns an annoyance into something worse. Google's AI products sit on top of the broader Google account infrastructure, a restriction triggered by Gemini usage can cascade into Gmail, workspace, and cloud storage, all tied to the same credentials. Several forum users flag this exact concern.

[C]

For a developer whose entire business runs

[B]

on Google, getting your AI subscription flagged doesn't just cut off one product, it puts everything at risk. Google's crackdown didn't arrive in a vacuum. Anthropic, two days earlier on February 20, had revised its consumer Terms of Service to spell out what had been loosely Implied since February OAuth tokens from Claude, Free Pro, and Max accounts are only permitted in Claud code, and Claude AI

[C]

using them anywhere else, including openclaw, violates the terms.

[B]

What makes the timing notable is that Anthropic's contractual language in section 3.7 has already forbidden unauthorized third party access since

[C]

at least February of 2024.

[B]

For two years that clause sat in

[C]

the terms, While tools like OpenClaw and OpenCode quietly let users supply CLAUDE subscription keys anyway. Anthropic had tolerated the practice, or at

[B]

least failed to enforce it, until the

[C]

economics forced their hand.

[B]

The Register's Thomas Claiborne framed the economics bluntly. Anthropic sells subscription tokens at a discount

[C]

compared to API pricing, an all you

[B]

can eat buffet priced with certain usage expectations. Third party harnesses broke those expectations by let letting subscribers extract more value than the subscription model assumed.

[C]

Token arbitrage pay the flat rate route tokens through a tool that burns through them faster than anyone planned for.

[B]

OpenAI, emboldened by this, has leaned into the gap. Tiebalt Sotio from OpenAI pointedly endorsed using

[C]

codec subscriptions with third party harnesses. Competitive positioning dressed up as developer friendliness. End quote.

[B]

Finally today, I found this very interesting over the weekend. It's from an investment analyst firm called Citrini Research. Think of this as a thought experiment imagining an AI driven 2028 global intelligence crisis. Basically, imagine this piece as a theoretical memo dropped on a training desk in

[C]

the future, say June 30, 2028.

[B]

The theoretical story the authors tell what happens if the AI optimists are right

[C]

and AI has transformed the economy like some expect it to.

[B]

The scene the piece sets is a bit concerning Unemployment numbers just hit 10.2%.

[C]

The S& P is selling off again and the index is now down 38%

[B]

from the October 2026 highs again. In this scenario, AI has won. Productivity rips. Output per hour rises like it's the 1950s again. Companies dump, labor margins widen, earnings beat and a huge chunk of those profits

[C]

go straight back into more compute.

[B]

The markets in this little future history are euphoric, while the lived economy quietly

[C]

stops looking like the one we recognize today.

[B]

They even coin a phrase for it. Ghost gdp. Real output on the spreadsheets that doesn't trickle down to households because the workers

[C]

in those households producing that output don't

[B]

buy groceries, take vacations or remodel kitchens. Machines spend exactly $0 on discretionary goods, so the veloc of money stops.

[C]

According to the piece, this scenario starts in late 2025 when agentic coding tools take a step change jump. Suddenly a competent developer with tools like

[B]

Claude Code or Codex can recreate the core of a mid market SaaS product in weeks.

[C]

Good enough that a CIO staring at

[B]

a $500,000 renewal starts asking why are we paying for this? Procurement discovers a new superpower even threatening to rebuild becomes a negotiating weapon. SaaS pricing cracks first and then the broader intermediation layer starts to wobble. Travel booking, insurance renewals, tax prep, routine legal work, even some real estate commissions as agents with MLS access grind fees down. The theory here is we've always overestimated relationships. A lot of what we called relationships in the economy was just friction with a friendly face. Once agents control the transaction, they behave like little heat seeking missiles for fees. Delivery apps fragment. A machine doesn't have home screen loyalty or brand loyalty. It checks every option every time and picks the cheapest or the fastest. Then payments come next. If agents are transacting on your behalf, why pay card interchange fees at all? So agents route around it stablecoins on solana or Ethereum L2s Instant settlement fractions of a penny. Meanwhile, the shock isn't just American. The piece imagines India's IT outsourcing giants tcs, Infosys, Wipro getting hit as contract cancellations accelerate, the rupee slid hard and even preliminary discussions with the IMF for

[C]

a bailout by early 2028.

[B]

Then the macro crisis becomes obvious. In the US displaced white collar workers downshift into lower paid service and gig

[C]

jobs, pushing wages down there too. One anecdote has a salesforce product Manager

[B]

Going from $180,000 a year to $45,000 driving Uber by Q2 2027, the US is in recession and then comes the daisy chain private credit has ballooned over

[C]

$2.5 trillion by 2026 in the scenario,

[B]

stuffed with PE backed software deals priced for perpetual recurring revenue. Right as AI disruption makes that premise laughable marks to market on portfolios like reality downgrades hit, insurers get forced to reassess capital treatment and the whole offshore reinsurance rating structured debt industrial complex turns

[C]

out to be opaque at the exact wrong time.

[B]

Mortgages start to wobble not because rates are too high, but because the income engine underpin pinning mortgages is suddenly suspect. When intelligence is cheap by the end, the authors call it an intelligence premium unwind because for most of human modern history, human intelligence was the scarce input

[C]

and our institutions were built around that assumption.

[B]

In this scenario, the policy world scrambles talk of a transition economy act with direct transfers funded by deficits and a tax on AI inference or even a more radical public claim on the returns of intelligence infrastructure. Its while Wall street gets populist Occupy

[C]

Silicon Valley blockades at major labs. The final part of the piece is a warning. You're not reading this in 2028. You're reading it now, today, in 2026,

[B]

when the Canary in the coal mine is still alive, but the clock is ticking.

[C]

Provocative stuff.

[B]

Worth reading.

[C]

The whole thing if.

[B]

You this has officially been the wintriest winter I've ever had since I've lived

[C]

in New York City. If you've heard people shoveling snow in the background of today's show, there was no way for me to avoid it, really.

[B]

I've had winters like this when I

[C]

lived in Michigan, where you get a big snowstorm and then it doesn't go above freezing for like a month or so, so the snow never really goes away. And it's gross. And everything is going gross.

[B]

The snow had almost gone away here,

[C]

but now we've gotten another snowstorm, which

[B]

is maybe the biggest I've seen since the 2004 blizzard.

[C]

So yeah, for the 26 years I've lived north of the Mason Dixon Line,

[B]

I've always still gotten a thrill when snow is in the offing. But this winter has broken this Florida

[C]

boy is all I can tell you. Talk to you tomorrow.