E54: Spread trading big tech, capital allocation, Zillow's misfire, Progressives suffer losses
David Friedberg (host), Chamath Palihapitiya (host), David Sacks (host), Narrator, Jason Calacanis (host), Jason Calacanis (host), Chamath Palihapitiya (host), Jason Calacanis (host), David Friedberg (host), Chamath Palihapitiya (host), Narrator
In this episode of All-In Podcast, featuring David Friedberg and Chamath Palihapitiya, E54: Spread trading big tech, capital allocation, Zillow's misfire, Progressives suffer losses explores big Tech Spread Trades, Zillow’s Collapse, and Voters Reject Wokeism The episode opens with banter before diving into markets, where Chamath outlines a spread-trade strategy: go long Microsoft and Google while shorting the rest of big tech to manage market risk and exploit relative outperformance.
Big Tech Spread Trades, Zillow’s Collapse, and Voters Reject Wokeism
The episode opens with banter before diving into markets, where Chamath outlines a spread-trade strategy: go long Microsoft and Google while shorting the rest of big tech to manage market risk and exploit relative outperformance.
They discuss capital allocation and fund structures, contrasting traditional VC distributions with permanent capital models like Sequoia’s evergreen fund and Friedberg’s Production Board, and touch on whether DAOs can realistically manage early-stage investing.
In real estate, they dissect Zillow’s failed iBuyer program, arguing it conflated speculative price-taking with true market making, and contrast its operational and data weaknesses with Opendoor’s more focused, software-driven model.
The back half is dominated by politics and policy: a ‘woke lash’ in recent U.S. elections, backlash to progressive education reforms (CRT and detracking math), and optimism about scientific solutions to climate change, including a breakthrough CO₂-to-starch process that could massively accelerate carbon removal and biomanufacturing.
Key Takeaways
Use spread trades in big tech to reduce market risk and bet on relative winners.
Chamath argues the most compelling internet trade is to go long Microsoft and Google while shorting other mega-cap tech (Apple, Amazon, Facebook, Netflix), capturing outperformance without taking full directional market risk.
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Distribution decisions in VC should distinguish between venture skill and public-equity skill.
They note that even top firms like Sequoia must confront whether they can compound capital as effectively in public markets as in private ones, suggesting LPs may often be better off receiving shares and deciding for themselves.
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Copying a focused upstart is far harder than it looks for incumbents.
Zillow’s attempt to replicate Opendoor exposed how entrenched legacy products (like Zestimate) and thin operational expertise can lead to mispricing, low margins, and huge losses in complex, low-margin, capital-intensive businesses.
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Political extremes in behavior and policy are being punished; moderation is winning.
They interpret recent elections (e. ...
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Education fights hinge on equality of opportunity versus equality of outcomes.
Debates over CRT, detracking math, and removing advanced courses reflect a deeper conflict: whether to level results (‘equity’) by capping exceptionalism, or expand opportunity so more students can reach high performance without dragging top performers down.
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Technological innovation may solve climate change faster than global political agreements.
Friedberg highlights a Chinese CO₂-to-starch process that could, at scale, both remove vast amounts of carbon and produce food or feedstocks, arguing that investing in such science and infrastructure is more practical than massive foreign transfer payments or symbolic summits.
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Public pressure can expose gaps between grand humanitarian claims and real plans.
Elon Musk’s public challenge to the UN World Food Programme—offering to sell Tesla stock if they publish a concrete plan to end hunger—illustrates how demanding transparency and specificity can reveal whether large institutions are prepared to deliver on their rhetoric.
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Notable Quotes
“The best trade on the internet is long Microsoft, Google, short the rest of big tech.”
— Chamath Palihapitiya
“Catching a wave of disruption is very difficult when you have an old-line business that is fundamentally competitive with a new line of business.”
— Chamath Palihapitiya
“Trump was behaviorally extreme… Now what we’re realizing is a different form of extremism, which is policy extremism, will also be met with the same response.”
— Chamath Palihapitiya
“This is a very old debate. It’s the debate between equality of opportunity and equality of results.”
— David Sacks
“If we have a great gain… we can take the gain and we can reinvest that capital in building new things. There’s no shortage of opportunities to pursue for the rest of my life.”
— David Friedberg
Questions Answered in This Episode
How feasible is it, in practice, for individual investors to execute and risk-manage the kind of big tech spread trades discussed in the episode?
The episode opens with banter before diving into markets, where Chamath outlines a spread-trade strategy: go long Microsoft and Google while shorting the rest of big tech to manage market risk and exploit relative outperformance.
Get the full analysis with uListen AI
What governance and talent structures would a firm like Sequoia need to consistently outperform in public markets as well as they have in private ones?
They discuss capital allocation and fund structures, contrasting traditional VC distributions with permanent capital models like Sequoia’s evergreen fund and Friedberg’s Production Board, and touch on whether DAOs can realistically manage early-stage investing.
Get the full analysis with uListen AI
Could Zillow have designed its iBuyer strategy to coexist with, rather than cannibalize and distort, its Zestimate-driven media business?
In real estate, they dissect Zillow’s failed iBuyer program, arguing it conflated speculative price-taking with true market making, and contrast its operational and data weaknesses with Opendoor’s more focused, software-driven model.
Get the full analysis with uListen AI
What concrete steps could Democrats and Republicans each take to realign with the political center without alienating their activist bases?
The back half is dominated by politics and policy: a ‘woke lash’ in recent U. ...
Get the full analysis with uListen AI
How might education systems practically expand advanced opportunities for underrepresented students without flattening or eliminating spaces for exceptional performance?
Get the full analysis with uListen AI
Transcript Preview
My body is a wonderland.
If that wonderland is white, soft and mushy, sure.
And hairy too.
(laughs) You know, the worst thing about skin on skin sleeping with a newborn is that, you know, sometimes she roots and she goes after the ma- the male nip.
I know.
The problem is, my nipple's covered in hair. (laughs) It's really awkward for everybody. (laughs)
Just start gagging.
I'll tell Tally that story when she's 18. Or at her wedding, it'll be even better.
(instrumental music plays) We're going all in. Don't let your winners ride. Rainman, David Sacks. We're going all in. And I said- We open sourced it to the fans and they have just gone crazy with it. Love you, Vespa. Queen of Quinoa. Going all in.
Hey, everybody, welcome to another episode of the All In podcast. I am wearing a blue shirt. I am a pasty white old Greek-
(laughs)
... man, uh, who's balding and obnoxious, and, uh, with me today is, uh-
No, no, no, no, you have to, you have to say your pronoun, bro.
... M- oh, and my pronouns are, uh... Oh wait, what are my pronouns? My pronouns are beep, beep. And most people just call me a jerk. With me today, of course, is my Sri Lankan Urkel looking-
Hello, hello, hello.
... wearing a furry sweater-
Hello, everybody. My name is Chamath. I have, uh, salt and pepper black hair, brown eyes. Uh, I am tall, uh, six foot two. I go by the pronouns we, king, and studmuffin.
(laughs)
And, uh, uh, I'm here to talk to you about, uh, internet security protocols. Wah, wah, wah, wah.
(laughs) I look like Urkel. I think people should just come up and say which celebrity they look-
Whoa, I don't look like Urkel?
... the closest like.
I don't, I don't look like Urkel.
You look like a Bollywood movie star.
When you put your gla- Oh, bam. It's a...
(laughs)
You're kind of like the Sri Lankan Urkel to us.
Welcome to the All In podcast. Two out of the four of us are canceled. Next up for cancellation, Sacks.
Yes, I am coming to you here from the floor of the New York Stock Exchange, which was once land that belonged to the Mohegan, the Montauk-
(laughs)
... the Oneida, the Erie, and the Iroquois tribes.
Oh, we're all canceled.
Since time immemorial.
Oh my god. (laughs)
You forgot the Irish. We own the seven points.
Oh my god. You really did it. You went for it, Sacks. I love you.
I-
Uh.
Isn't it important that we-
(laughs)
(laughs)
... at any moment that we're successful, we have to flagellate ourselves or remind ourselves-
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