18 October 2026
150 new episodes (145 hours listening) published by the 50 podcasts on the list. 40 highlight clips below (123 mins total).
Investment 18 October 2026 · 40 clips
The Compound and Friends
Steve Eisman
Steve Eisman bet against the subprime mortgage market ahead of the 2008 financial crisis while running FrontPoint Partners, a trade chronicled in Michael Lewis's The Big Short. He joined Neuberger Berman in 2014 as a managing director and portfolio manager, and launched the Real Eisman Playbook podcast in 2025.
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1 of 3 current issue
Steve Eisman, while stressing it is not a prediction, thinks an OpenAI bankruptcy would put the US into recession immediately, because the AI supply chain runs on two customers.
Nvidia's 10-Q shows 70% of its receivables coming from five customers; Eisman puts 70% of the hyperscalers' AI revenue, perhaps 25% to 30% of their cloud revenue, with OpenAI and Anthropic, and half of Oracle's backlog with OpenAI alone. He sets this apart from 2008: a failure here looks more like General Motors going under, with layoffs and failed suppliers, while the banks are fine.
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2 of 3 current issue
Steve Eisman counts about 65% of the S&P 500 as a single AI trade once tech, Alphabet, Amazon, the investment banks and suppliers such as GE Vernova, Quanta, Eaton and Rockwell are added up.
Tech alone is 40% by his count and Google and Amazon take it to 50%; one host adds that companies not yet public are now big enough to cause a recession, and that this week showed how much yields depend on AI's ability to sell debt. Eisman says the trade is fine so long as demand holds up and somebody is willing to finance the build.
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3 of 3 contrarian
Steve Eisman's bear case for AI is a price war, as cost-conscious buyers move staff onto cheaper models and the two leading labs come under pressure to cut prices.
Enterprise software has moved from per-seat contracts toward paying for usage, which Eisman says is a lot more expensive and makes buyers cost-conscious. In his hypothetical, Anthropic's growth turns negative, nobody funds it, commitments get cut, and Oracle, with half its backlog from OpenAI, goes down with them.
All-In
Ben HorowitzAndreessen Horowitz
Ben Horowitz of Andreessen Horowitz, which the hosts introduce as the largest venture firm by assets under management, went through the 1999 to 2001 bandwidth collapse at Loudcloud; his firm holds stakes in both OpenAI and Anthropic.
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1 of 5 framework
Ben Horowitz says Andreessen Horowitz has stayed out of neoclouds because at Loudcloud he saw bandwidth bought on three-year contracts at $1,500 a megabit in 1999 fall to $50 by 2001.
He still reads the AI build-out as the reverse of the internet bust, which died of too little demand: GPUs now earn for six to eight years instead of three to five, and Andy Jassy told him Amazon is out of capacity to the end of 2028, perhaps beyond. Data centre space is rising in price as well, with labour scarce and politics slowing builds, so the tailwind runs through the whole supply chain.
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2 of 5 current issue
Chamath Palihapitiya reads CoreWeave's credit default swaps, at about 953 basis points this week, as an implied annual chance of default of about 16% and roughly 55% over five years.
He treats the traders in those swaps as the smartest money on this risk. His chart then splits CoreWeave's borrowing cost from junk debt as a whole: both have been dragged up by a rising 10-year Treasury yield, and CoreWeave's has climbed faster.
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3 of 5 contrarian
David Sacks argues a yield of around 15% on CoreWeave's unsecured bonds does not raise what the company pays today, because the coupon stays at 9.6%, and he thinks new capacity is financed project by project.
He works through the alternatives in turn: demand is still rising, with H100s and A100s renting at premiums long after they were meant to be written down; supply is held back by power and permitting; and each project borrows on the credit of a five-year tenant such as Microsoft, with the GPUs as collateral. He concedes the repricing could lift the cost of future unsecured debt.
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4 of 5 framework
David Sacks names payback period as the metric to watch in AI data centres: CoreWeave says it recovers its outlay in 2.5 years of a five-year contract, and SpaceX does so in roughly one.
The gap comes from pricing, on his account: SpaceX sells close to spot on deals either side can cancel within 90 days, earning about $50 billion a gigawatt to CoreWeave's $20 billion on contracts signed years ahead. The panel then argues over whether CoreWeave should pay to exit contracts and sell spot; the counter is that investment-grade customers will not pay spot when they can build their own.
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5 of 5 prediction
Chamath Palihapitiya argues Anthropic should use its IPO to raise $200 to $250 billion at a valuation nearer $1 trillion to $1.5 trillion, instead of about $80 billion at close to $2 trillion.
He would rather take the money now than file a mixed shelf for a later raise, which takes about six months in whatever market then exists; later in the clip the panel puts $200 billion as a path to five to 10 gigawatts financed through CoreWeave-style boxes. Ben Horowitz agrees, from a chief executive's experience of nearly running out of cash, that financing is the risk most likely to stop the company.
Capital Allocators
Charlie RoseInvesco
Charlie Rose is Global Head of Real Estate Credit at Invesco, part of an $85 billion global real estate platform. He spent eight years at Canyon Partners investing across the capital stack after the 2008 crisis.
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contrarian
Invesco Real Estate Credit is not lending on data centres, citing single hyperscale tenants, no alternative use and unknown obsolescence five to 20 years out.
Charlie Rose concedes the supply of deals and the yields are tempting. His second reason is portfolio-level: real estate credit has historically shown a correlation below 0.2 even to private equity, private credit and real estate equity, and with a lot of other segments now carrying meaningful AI exposure, Rose believes keeping it out helps the asset class hold that low correlation.
The Credit Edge
Bryan WhalenTCW
Bryan Whalen is chief investment officer of TCW's fixed income group, which oversees about $160 billion, and a generalist portfolio manager with 30 years in bond markets. His background includes MetWest, Credit Suisse and DLJ.
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1 of 4 current issue
TCW's fixed income group holds less investment-grade and high-yield credit against its benchmarks than at any point in 30 years, with investment-grade spreads still near all-time lows.
Most of TCW's public fixed income is run long-only, so the position is an underweight to the corporate share of each benchmark. Whalen would rather wait for a better opportunity than take so little pay for the concerns he has.
Audio streamed from the publisher.
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2 of 4 contrarian
Bryan Whalen of TCW argues rates of 5% or more feel suffocating for the US economy outside AI, while most of the big borrowers inside it keep borrowing at the same pace.
He puts neutral near the 3.5% to 4.5% range rates sat in at the turn of the year and expects a return there within one to two years. Housing activity, commercial property, auto loans and credit cards already show the strain, and businesses that AI threatens, his examples being software firms and insurance brokers, face it worst.
Audio streamed from the publisher.
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3 of 4 current issue
TCW's Bryan Whalen expects Meta, Microsoft, Amazon and Google to manage their AI debt load, and puts his real concern on AI companies with no business outside AI.
The big four have non-AI businesses that can carry the debt whether they turn free-cash-flow positive in 2028 or 2029, so their spreads may widen without principal coming under threat. The AI-only names carry more leverage, and their financing depends in large part on others inside the same ecosystem.
Audio streamed from the publisher.
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4 of 4 prediction
TCW expects hyperscaler bonds to keep trading wide for years even if AI goes well, because chip financing will follow this year's wave of data-centre issuance.
Whalen draws on the big six banks after the global financial crisis: TCW judged their cleaned-up balance sheets cheap and was right, but spreads took ten years to compress. What it may have missed, he says, was how much the banks would issue to get their balance sheets where regulators needed them.
Audio streamed from the publisher.
The Real Eisman Playbook
Market Cracks Under AI Debt Burden | The Weekly Wrap
A weekly solo wrap by the host, with no guest.
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1 of 3 framework
Steve Eisman says investors fear consumer AI agents will sweep idle cash out of bank and broker accounts into money market funds, and JPMorgan has announced it will not let outside agents into its customer accounts.
Checking and savings balances paying little or nothing are a typical bank's most important funding and the base of its net interest margin, and they stay put because customers do not bother to move them. Personal-lines insurers such as Progressive and Geico face the same threat, since an agent shopping for a policy weighs price and credit rating and ignores the brand.
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2 of 3 current issue
Steve Eisman reads CoreWeave's bonds, issued at a 9% coupon and now below 90 cents on the dollar for a yield near 15%, as the fixed income market quickly losing confidence in the company.
CoreWeave carries more than $35 billion of debt and $10 billion of capital lease obligations against a $43 billion market cap, while competing with hyperscalers on far larger balance sheets. Its shares fell 15% on Wednesday and Nebius 10%, and OpenAI's reported annualised revenue has slipped from a claimed $70 billion to $50 billion.
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3 of 3 contrarian
Steve Eisman finds no sign of a credit cycle in the non-accrual data of JPMorgan, Wells Fargo, Citi and Bank of America, and concludes the banks are not the leading indicator this time.
JPMorgan's non-accruing loans stood at $9.4 billion, down 7% on a year earlier, and Bank of America's at $5.7 billion, up 3%, with none of the consumer surge that preceded the financial crisis. On his account the next trouble could emerge instead in private credit's exposure to software or in AI-related debt such as CoreWeave's.
Top Traders Unplugged
Christian Mueller-GlissmannGoldman Sachs
Christian Mueller-Glissmann is head of asset allocation research at Goldman Sachs.
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1 of 3 contrarian
Christian Mueller-Glissmann of Goldman Sachs reads the AI boom as an earnings bubble in parts of the market, not a valuation bubble, and thinks the S&P 500's forward multiple has fallen from 23 to 19 times this year.
Most investors he speaks to are already discounting the cyclical semiconductor and hyperscaler earnings, and long-dated data centre and compute contracts give more visibility than usual. Because an earnings bubble can take a long time to deflate where a valuation bubble can burst quickly, he makes the third-quarter season the test: AI revenue has to start offsetting negative free cash flow and the depreciation to come.
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2 of 3 framework
Goldman Sachs' Christian Mueller-Glissmann judges a bond sell-off by its level, speed and source, and with the US 10-year at 5.3% to 5.4% he puts all three at or near the point where equities struggle.
He puts the 300-year average US 10-year yield at 4.7%, or 4.5% without the 1970s, and says equities have historically struggled once yields rise more than two standard deviations in three months, a line crossed around 5.1% to 5.2%. The rise has come through real yields and policy, and the damage already shows in small and mid caps, real estate, home builders and some financials.
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3 of 3 current issue
Goldman Sachs' Christian Mueller-Glissmann reports global asset owners moving a little closer to home because currency risk now matters more, already in bonds and increasingly in equities.
On his account, policy-driven volatility tends to bring inflation, which gives real assets the potential to cushion it over the medium term even if property and infrastructure do not protect at the moment inflation arrives. With fiscal and political risk widespread, government bonds become a less reliable offset to equities, and gold tends to gain when trust breaks: in central banks in the 1970s, the financial system in the global financial crisis and governments since COVID.
MacroVoices
Yasir ArafatAalo Atomics
Co-founder and chief technology officer of Aalo Atomics, which is building a factory in Texas to produce 100 reactors of 10 MW each a year, first for AI data centres.
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current issue
MacroVoices' market desk reads CoreWeave's shares falling about 16%, with its bonds yielding up to 15%, as a possible first sign that the credit funding AI growth is tightening.
In the desk's account AI has absorbed so much credit to grow that growth may stall once access to it slows, so the market is trying to work out when that financing cycle comes under stress. Commitment of Traders data had Nasdaq positioning at the 100th percentile and Russell small caps near zero beforehand, and on the day defensives and Treasuries rallied while AI names fell.
The Pomp Podcast
Jordi VisserVisserLabs
Jordi Visser is a macro investor with more than 30 years' experience and writes the VisserLabs Substack.
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1 of 2 current issue
Lone Pine Capital, on The Pomp Podcast's account, rose more than 40% in the first half and gave all of it back by the end of September, in a quarter when the S&P 500 rose 2% and the VIX never spiked.
Visser reads it through LTCM: a levered spread trade is a bet on how long investors stay and how long prime brokers keep lending. With the AI winners so few and the losers so many, he expects that squeeze to run for the five years he gives the build-out and to take leverage out of the hedge fund industry.
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2 of 2 contrarian
The Pomp Podcast puts money market fund assets up 70% since 2022 against 5% to 6% growth in bank deposits, and expects AI agents to pull more cash out of the zero-yield accounts that fund JP Morgan's spread.
The conversation puts the bank's net interest income at $107 billion and sees its only defence in cutting headcount by automating workflows while the margin narrows. Stripe, which bought OpenRouter, is put at $160 billion to $200 billion with about 10,000 staff, against Citigroup's 200,000 at a similar market cap.
BG2 Pod
Jensen HuangNVIDIA
Jensen Huang leads NVIDIA, which he puts at about 80% of AI infrastructure revenue. This is his third BG2 conversation, recorded days after he received the National Medal of Science.
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1 of 3 contrarian
Jensen Huang puts the frontier labs at roughly a quarter to 30% of NVIDIA's compute, and argues the trillions in AI capex do not depend on their revenues doubling every year.
The hosts set the test: lab revenue of about $200 billion this year would need to reach $400 billion and then $800 billion to come near paying back the build. Huang answers by splitting NVIDIA's business into rough thirds: classical computing such as fraud detection and simulation, growing perhaps 30% to 40% a year with no AI in it, the labs, and thousands of startups renting compute.
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2 of 3 current issue
Jensen Huang says NVIDIA is setting up two revenue lines independent of the next chip sale: enterprise software licences at roughly a couple of thousand dollars per GPU a year, and, very likely, revenue shares in regional clouds it helps finance.
Many enterprises moving from training to deployment lack the staff to run the stack and want NVIDIA on the service agreement for years; at, say, 20 million GPUs a year, half into enterprises, he says the licence income adds up. A revenue share would apply where NVIDIA supplies offtake, software support and investment to a cloud that has already secured land, power and buildings.
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3 of 3 current issue
Jensen Huang says NVIDIA's offering now comes to more than $40 billion for each gigawatt of data centre, up from about $18 billion, and that a shortage of power is shifting buyers toward it.
With land, power and buildings scarcer than chips, Huang argues a fixed power budget goes to whatever earns the most revenue per watt, and that scarcity therefore works in NVIDIA's favour. He estimates NVIDIA's share at about 40% of the big cloud providers' capex and about 80% of spending outside them, against single digits six years ago.
The Meb Faber Show
Dirk WillerCiti
Dirk Willer is head of global macro, asset allocation and emerging market strategy at Citi, where his team includes a large quant group that backtests the rules he trades by. His book, Trading Global Macro Markets, came out last spring.
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1 of 2 prediction
Dirk Willer puts the US equity market at 240% of GDP against just over 100% at the 2000 peak, and expects a burst to bring a deeper recession, with rates back at zero not implausible.
A real yield of about 3.3% on the 30-year may be hard for the S&P to beat if the bubble bursts within the next five years or so, Willer argues. The market has swung from treating every shock as deflationary to treating every shock as inflationary; a burst bubble, or AI pushing unemployment past 10%, could be the deflationary shock that makes Treasuries work again.
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2 of 2 framework
Citi built a Warsh shadow rate from every indicator Warsh has said he cares about, and with it at its highs, Dirk Willer's team reads him as hawkish.
Summed as z-scores, those indicators tracked Fed funds in the 1990s almost exactly under Greenspan, Warsh's favourite central banker, and later led it. For bonds Willer uses the rule of thumb of selling about six months before the first hike and buying back only when one hike is left, because the market keeps pricing more hikes until the Fed sounds close to done.
Masters in Business (Ritholtz)
Bob MicheleJ.P. Morgan Asset Management
Chief investment officer and head of global fixed income, currency and commodities at J.P. Morgan Asset Management, which he joined in 2008 after running fixed income in London for Schroders. He started in the industry at Bankers Trust in 1981.
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current issue
Bob Michele says private credit is repeating the mortgage market, where Rocket Mortgage, a non-bank, became the largest lender and the banks learned to live alongside it.
Large borrowers now weigh a public bond against a direct loan, and Michele's firm has paired its commercial bank, which sources and originates the loans, with his asset management team, which takes a fiduciary look and buys those that fit its clients. He says the convergence of public and private is happening everywhere.
Audio streamed from the publisher.
Excess Returns
Colin McQueenT. Rowe Price
Colin McQueen is a portfolio manager in T. Rowe Price's global equity division, billed by the show as a $17 billion international manager. He started in 1989 at Phillips & Drew, the UK value house later absorbed into UBS, and spent time on Morgan Stanley's global value team before joining T. Rowe Price.
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current issue
Samsung Electronics traded at one times book 18 months ago and now sits just under three, and T. Rowe Price's Colin McQueen puts about 14% to 15% of international stocks as tied into the AI supply chain.
Memory chips and passive components were commoditised suppliers to PCs and phones, carrying excess capacity, until AI demand pushed them into undersupply and gave them pricing power. On the user side McQueen says the market is still working out which companies AI helps and which it disrupts, and he takes from the dot-com era that proving a business is not being disrupted can take a long while.
Forward Guidance
The Bond Market Is Pricing In Something Worse Than Inflation | Weekly Roundup
A weekly roundup between the two hosts, with no guest.
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current issue
Forward Guidance's hosts argue the US is already tightening with little help from the Fed: the 10-year has held above 5% for what one host thinks is more than a month, while high-yield and hyperscaler credit spreads widen.
Diesel prices, mortgage rates and wider spreads all raise the cost of building, and one host puts the lag before it reaches the data at anywhere from one to four months. They read the recent sell-off as de-grossing ahead of the midterms and the next Fed meeting, with nothing yet in place to bring yields, spreads or oil back down.
Excess Returns
Jim PaulsenPaulsen Perspectives
Jim Paulsen writes the Paulsen Perspectives Substack and joins Excess Returns each month to walk through his charts. He has managed money for clients himself.
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prediction
Jim Paulsen's most likely path is Fed cuts that arrive with falling stocks, a 15% S&P 500 correction with 20% or more in tech, then another three years of bull market.
Paulsen argues that oil oscillating around $100 a barrel adds nothing month on month, so inflation comes down unless crude escalates to about $150, and he says non-energy prices have already rolled over. Easing would then bring bond yields lower, which he expects to surprise most of the market.
Rational Reminder
Alex EdmansLondon Business School
Professor of finance at London Business School and author of Grow the Pie, May Contain Lies and The Madness of Markets. Previously a tenured professor at Wharton and an investment banker at Morgan Stanley.
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1 of 3 explainer
Alex Edmans found the 100 Best Companies to Work For in America beat their peers by 2.3% to 3.8% a year over 28 years, even though the list is public.
His explanation is that employee satisfaction never arrives as an announcement the way earnings do, some investors dismiss it as soft, and those who rate it may still not know how to turn it into a figure in a valuation model. Compounded, the gap comes to 89% to 184% over the period.
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2 of 3 framework
Alex Edmans argues, after Berk and Green, that a lack of persistence in fund returns is no evidence of a lack of skill: money floods to a skilled manager until the edge is diluted or charged away.
Inflows push a larger book out of its ten best ideas into weaker ones, or the manager raises fees, and either way the investor keeps little of the talent. Edmans cites ARK growing from $4 billion to $60 billion after one strong year, and says his own emerging and frontier market holding is little known and that he invests on preferential terms.
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3 of 3 explainer
Alex Edmans says momentum's worst losses can be seen coming: they typically arrive after a big fall in the S&P 500 or when the VIX is high.
After a sell-off the rebound is led by cyclical companies, and those are the stocks a momentum book has just sold because they fell hardest, so the strategy is short the recovery. Edmans points to Daniel and Moskowitz's Momentum Crashes paper, which suggests tilting out of the factor when the market is in decline.
AI 18 October 2026 · 40 clips
The Compound and Friends
Steve Eisman
Steve Eisman bet against the subprime mortgage market ahead of the 2008 financial crisis while running FrontPoint Partners, a trade chronicled in Michael Lewis's The Big Short. He joined Neuberger Berman in 2014 as a managing director and portfolio manager, and launched the Real Eisman Playbook podcast in 2025.
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contrarian
Steve Eisman's thesis is that Sam Altman and Dario Amodei are asking for regulation because token-maxing is done and open-weight models at a tenth of the price leave no AI lab with a moat.
Uber ran through its AI budget in three months this spring, and Eisman expects cost-conscious companies to move work to open-weight models; he hears Anthropic is already cutting prices. On his reading, the two labs could use regulation to keep Chinese open-weight models out and hold a duopoly.
Big Technology Podcast
Kevin Roose
Kevin Roose is the author of The AGI Chronicles, a history of the last decade at OpenAI, Anthropic and Google DeepMind built on interviews with more than 150 people. He co-hosts Hard Fork and is launching a new show, Machine Gods, with Casey Newton.
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prediction
Kevin Roose cites Anthropic's figure that Claude now leads 26% of the company's AI research and development projects, and sees no reason it could not reach 50% or 75%.
OpenAI has said its goal is an automated AI researcher, and if the labs close the loop Roose suggests new models could arrive every couple of weeks or faster instead of every six months, though he does not know how fast the cycle would run. He thinks the labs are racing toward recursive self-improvement and should stop.
20VC
Harrison ChaseLangChain
Harrison Chase is co-founder and CEO of LangChain, which builds developer tools for AI agents and has announced about $160 million in funding, the last round at a $1.25 billion valuation. LangChain works with 35% of the Fortune 500 and has passed one billion open-source downloads.
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contrarian
Harrison Chase calls the fear that Chinese open-weight models send enterprise data back to their labs ridiculous when the model runs on Fireworks or on the enterprise's own hardware.
The second fear, that training leaves the model answering against an enterprise's values, he thinks largely unfounded and testable with evals, with some nuance by domain. He expects comparable US open models within 12 months, pointing to Nvidia and a recent Reflection launch, and finds open models in wider use than he expected, though mainly on narrow tasks.
a16z
Jad NaousGrepr
Jad Naous is chief executive of Grepr, a 10-person company whose telemetry pipeline cuts observability data costs. He spent a couple of years in venture at a16z, was chief product officer at a startup whose product and engineering team grew from about 15 to over 90, and spent about three and a half years at AppDynamics as it grew from about 200 to 2,000 people ahead of its sale to Cisco.
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1 of 2 contrarian
Grepr's Jad Naous finds AI coding tools widened the gap between good and average engineers on his small team by about 10 times, with no weak engineer becoming a strong one.
His explanation is that someone still has to hold the whole system in their head and break the work into pieces a model can take. For the distributed algorithms Grepr builds, none of the models can reason through the problem, so the engineer explains what the system must do and the model builds to it.
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2 of 2 framework
Martin Casado expects AI to spread fastest where outputs look like the training data, and points to self-driving: about 20 years and $170 billion to reach unit economics worse than Uber's.
Casado names code and generated images as the domains where AI keeps spreading fast, and puts anything whose solution lives in the natural world on the slow side, with harder economics. He starts the self-driving clock at Sebastian Thrun's DARPA Grand Challenge win, when Casado was at Stanford.
Y Combinator
Clark Barrett and Mykel KochenderferStanford Center for AI Safety
Barrett and Kochenderfer are Stanford professors and co-directors of the Stanford Center for AI Safety. Barrett directs the Center for Automated Reasoning; Kochenderfer directs the Stanford Intelligent Systems Laboratory, whose ACAS X collision avoidance work was held to one catastrophic failure per billion flight hours.
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framework
Y Combinator's Paper Club panel floats an NTSB for AI, pointing to independent accident investigation and non-punitive reporting as how commercial flying became 80 times safer than in the 1970s.
The host asks whether that would mean opt-in guidelines or FDA-style approval, and the answer goes back to 1967, when the US accident board was set up as its own agency, and to ASRS and a later scheme that gave reporters some immunity. The panel concedes a new body may take too long to set up.
Worth listening to in full 18 October 2026
Most clips above stand alone. These are the episodes that justify the whole hour.
It's a Bubble. So Why Is Citi's Dirk Willer Buying?
Willer carries one argument for 48 minutes, that the US equity market is in a bubble that runs until liquidity is withdrawn, and tests it against bonds, the dollar, emerging markets, gold, copper and hedges, with a quantified rule at almost every turn. Two short sponsor reads and a book plug are the only dead air.
TCW Chops Credit Risk to Lowest in 30 Years as CCCs ‘Cry Uncle’
Bryan Whalen holds one argument for 50 minutes, that credit is not paying for its risks, and tests it from rates, the consumer, CCC contagion and the financing of AI, with a number at most turns. The securitised-credit stretch and the closing exchange on younger investors are the only parts a senior reader could skip.