24 August 2026
16 new episodes (14 hours listening) published by the 50 podcasts on the list. 17 highlight clips below (54 mins total).
Investment 24 August 2026 · 17 clips
20VC
Jason Lemkin and Rory O'Driscoll
Jason Lemkin is a SaaS investor whose portfolio includes Algolia, Talkdesk, Owner, RevenueCat and Salesloft, and he says he is an investor in Mercor, Poolside and Perplexity. Rory O'Driscoll is a general partner at Scale, where he led investments in Bill.com, Box, DocuSign and WalkMe.
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1 of 2 framework
NVIDIA's vendor financing changes what it has to be right about: selling chips only requires being right in the end, while lending against them requires being right every year along the way.
Aschenbrenner's fund is the same structure seen from the other side: the thesis may well have been right over five years, and four-to-one gearing meant it had to survive each quarter in between. Citadel is set against both, never trying to be right over five years and selling anything up 10%.
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2 of 2 framework
Stripe tells its investors to treat intelligence as capital rather than as seat-based software, because uncapped consumption has to be allocated and rationed the way money is.
A chief financial officer cannot introduce automation and then report that earnings per share fell 10%, so a rising token bill has to come out of another line, usually people. Their figure for the two labs' revenue is an appreciable share of total US corporate profits, which is the arithmetic that forces the trade-off rather than any preference for cutting.
The Compound and Friends
Ed Zitron
Zitron founded the PR firm EZPR in 2013 and has written the newsletter Where's Your Ed At since 2020, where his 2023 essay on the rot economy circulated widely. He hosts the Better Offline podcast and says he holds no position in any of the companies he writes about and gives no financial advice.
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1 of 2 contrarian
Ed Zitron puts $24.1 billion of Microsoft's $34.33 billion in fiscal 2026 AI revenue down to a single customer, OpenAI, which leaves everything else Microsoft sells into AI a single-digit-billion business.
Microsoft is being paid out of money OpenAI raises, and the last round drew only $12 billion of its $122 billion from venture capital, the rest from Nvidia, SoftBank and Amazon. Zitron sets his own break point: at 30% concentration he would drop the argument, at 70% he calls it existential.
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2 of 2 prediction
Ed Zitron names four events that would break the AI spending cycle, and all four are financing events: a hyperscaler quitting the race, a hyperscaler downgraded, a widely held AI startup running out of money, and an IPO that fails.
He watches bond books for the first sign: Amazon's data centre issue cleared at 1.6 times oversubscribed against four to five times for Google's, and a fall towards 1.1 or 1.2 would be the tell. Ratings agencies meanwhile put CoreWeave's debt at investment grade on the strength of its hyperscaler customers.
Monetary Matters
Jim Wiederhold
Commodity indices product manager at Bloomberg, responsible for the Bloomberg Commodity Index and the enhanced roll yield benchmark built alongside it. He called industrial metals to outperform gold and silver at the start of 2026; industrial metals are up 27% on the year against a roughly flat gold price.
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1 of 2 current issue
Jim Wiederhold says the Hormuz closure now removes half the supply it did in February, with Chinese inventory draws, North American output and a Saudi pipeline running west covering the gap.
China's move to electric vehicles meant it needed less imported crude than the same conflict would have demanded a few years earlier, and it drew down stored barrels on top of that. The remaining support is talk: the US administration has been pricing a deal that has not arrived.
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2 of 2 explainer
Jim Wiederhold puts flows through Hormuz at about 9 million barrels a day, more than half of it shadow fleet, and says the anchorage off Oman now holds 150 tankers or more against a historical 30 to 40.
Transponders go off for the transit and come back on outside the strait, so the ship-tracking series most desks quote cannot see the larger half of the traffic. Wiederhold's read leaves the disruption at roughly 10% of world supply against the 20% lost in February.
The Meb Faber Show
Paul Kedrosky
A fellow at the MIT Institute for the Digital Economy, a partner at SK Ventures and a former sell-side analyst. He works on the scale and financing of the AI build-out, and says he modelled the IPO funding drain in March and April of this year.
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1 of 3 current issue
Paul Kedrosky dates the crossover to the first half of 2026: most hyperscaler data centre financing now comes from ABS, private credit and sovereigns instead of internal cash flow.
Lenders he talks to look straight through the building to the hyperscaler covenant behind a twelve-year renewable lease, which prices better than holding a ten-year Treasury, so what happens inside the shed stops mattering to the credit decision. That bid now competes with sovereign issuance, which he ties to the pressure at the long end.
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2 of 3 framework
Paul Kedrosky puts token prices on a 70% to 80% annual decline, which leaves a frontier model company needing 400% unit growth a year just to hold revenue flat.
Technology was bought for years partly on a pristine balance sheet, and he counts data-centre paper at 15% to 18% of the investment grade market against that memory, on a JP Morgan report. Continuous maintenance capex leaves these companies with a utility's fixed commitments and none of a utility's multiple, and he expects the technology side to re-rate first.
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3 of 3 explainer
Paul Kedrosky argues that funds facing up to $5.5 trillion of coming IPO supply had to sell their most liquid winners months ahead, which is what pressured the best-performing AI names.
Cash is a drag on a long-only fund, so nothing waits in an account for an allocation and the money comes from selling. What gets sold is liquid, overlaps the exposure being bought and has performed, because a manager avoids doubling a factor and prefers to book the gain, and the selling starts weeks or months before the deal prices.
In Good Company (Norges Bank)
Sir Paul Marshall, co-founder of Marshall Wace
Marshall co-founded Marshall Wace in 1997 with $50 million, half of it from Soros, and the firm now runs around $90 billion with roughly 750 staff, over 200 of them in technology. Assets fell from $14 billion to $3.5 billion through 2008 because the firm chose not to gate while competitors did. He wrote "10½ Lessons from Experience" and sold a minority stake to KKR in 2015-16.
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1 of 3 explainer
Paul Marshall sets out why a short book fights its own risk management: the position grows as it moves against you, and the borrow rate has already priced what every other hedge fund thinks.
Brokers and the press sit on the long side of every company they cover, so the argument a manager hears runs one way before the trade is on. Marshall's comparison is the losing long, which shrinks as it falls and can be averaged down at a better price, a discipline that has no counterpart when the position runs the other way.
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2 of 3 contrarian
Paul Marshall expects markets to get more competitive without getting more efficient, because AI pushes retail's share of trading up and retail does not arrive with institutional risk management.
Good firms now receive and process the same data in the same moment, which is how he explains an information edge disappearing while an analytical one survives. He points at China, Taiwan and Korea, where a high retail share has historically left alpha on the table.
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3 of 3 prediction
Paul Marshall says the US semiconductor index sits at a five or ten year low on valuation, so the AI bubble he expects has not started, and twice-levered GPU securitisations would be his signal that it has.
He wants three conditions before calling one: rates low enough to encourage speculation, valuations extended, and leverage at unsustainable levels. Korea gives him the second reading, at an all-time low on the same measure, and its leveraged ETF market falling from $60 billion to $20 billion in five weeks is a leverage episode he treats as already formed and cleared.
AI 24 August 2026 · 17 clips
Invest Like the Best
Neil Movva
Neil Movva co-founded Sail Research, which sells inference on open-source models through an API and hosts long-running agent virtual machines for tasks measured in hours or days. Nvidia was his first job, while he was in college, and he worked on the software team squeezing performance out of the first generation of tensor cores from around 2016; he says he has spent his whole professional life on GPUs and kernels.
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1 of 2 explainer
Nvidia's Blackwell stacks 298 gigabytes of DRAM around a logic die carrying roughly 500 megabytes of SRAM, and that gap of three orders of magnitude is the whole reason Cerebras and Groq exist.
Static cells sit beside the arithmetic units and read at petabyte-a-second rates, but a six-transistor cell eats die area, so even a full wafer of them holds only tens of gigabytes. Weights fit that budget and the conversation cache does not, because the cache grows with how many users arrive and how long they talk, which is why the wafer-scale parts get paired with a conventional GPU rather than replacing one.
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2 of 2 framework
Neil Movva puts the practical ceiling on new United States data centre capacity at about 10 megawatts a site, with one megawatt plentiful and a gigawatt effectively unbuildable.
Training needs one concentrated site because nobody wants to train across data centres, which is why developers still hunt for the hundred-megawatt parcels. Inference does not, so he buys the scattered one-megawatt pools instead and accepts what comes with them: no backup generators, a single fibre trench, no redundancy, and uptime he expects to fall to 95% at some sites.
In Good Company (Norges Bank)
Sir Paul Marshall, co-founder of Marshall Wace
Marshall co-founded Marshall Wace in 1997 with $50 million, half of it from Soros, and the firm now runs around $90 billion with roughly 750 staff, over 200 of them in technology. Assets fell from $14 billion to $3.5 billion through 2008 because the firm chose not to gate while competitors did. He wrote "10½ Lessons from Experience" and sold a minority stake to KKR in 2015-16.
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contrarian
Marshall Wace runs 750 staff with over 200 in technology, and Paul Marshall says AI has reduced headcount on one of fifteen fundamental teams and nowhere else in the firm.
Payroll climbed toward that level over three years and has not moved for two, while Marshall reports large gains in productivity and in the quality of decisions. Nobody inside the firm expects to need fewer people; what he expects to change is the kind of person they hire.
20VC
Jason Lemkin and Rory O'Driscoll
Jason Lemkin is a SaaS investor whose portfolio includes Algolia, Talkdesk, Owner, RevenueCat and Salesloft, and he says he is an investor in Mercor, Poolside and Perplexity. Rory O'Driscoll is a general partner at Scale, where he led investments in Bill.com, Box, DocuSign and WalkMe.
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explainer
The 20VC panel reads OpenAI's IPO announcement as forced: an 18% quarterly step from roughly $5 billion to $6 billion could not be left standing next to Anthropic.
Broadcom and NVIDIA are the audience that matters, since they are planning to sell something like $200 billion of chips into a growth rate a flat quarter would call into question. The panel puts Anthropic near $60 billion mid-year and reads the reacceleration story as the defence of a ranking rather than a disclosure.
The Meb Faber Show
Paul Kedrosky
A fellow at the MIT Institute for the Digital Economy, a partner at SK Ventures and a former sell-side analyst. He works on the scale and financing of the AI build-out, and says he modelled the IPO funding drain in March and April of this year.
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contrarian
Paul Kedrosky puts year-on-year gains on composite AI benchmarks at 1% or 2%, down from 10% or 12%, and says the spread between the leading models has collapsed below what a user can detect.
He throws out the published scores because the systems ingest them, the way a candidate who has already sat the test does well on it, and works from blended indices instead. Harnesses such as coding agents surround the weights and make progress look quicker than training justifies, which is why he thinks the first lab to stop paying for new training runs collects a gift.