Lumida Wealth : Non-Consensus Invest Beyond the Ordinary

Anthropic just filed for what could be the biggest tech IPO in history. We went through the S-1 so you don't have to.

Ram Ahluwalia sits down with returning guest Michael Parekh, former Goldman Sachs analyst and author of AI: Reset to Zero, to break down what the filing actually reveals:

→ 48% of revenue runs through Amazon, Google and Microsoft, which also compete with Anthropic
→ Broadcom, Google and Amazon are financing their own customer. Clean financing or circular?
→ For every $100 of revenue: $14 in cost, $60 in R&D, and a $4 operating loss
→ Only about 1,900 customers pay $1M+ a year. Still early?
→ Ken Griffin says AI models are the new airlines. Is he right?

Watch the full conversation on YouTube: https://youtu.be/vo_NOv2i8-A

Follow Michael Parekh: AI: Reset to Zero on Substack https://michaelparekh.substack.com · X @mparekh
Follow Ram: X @ramahluwalia

Chapters:
00:00 Intro
01:11 Inside the S-1: a $30T market
07:53 48% of revenue runs through rival clouds
12:11 Circular financing: Broadcom, Google, Amazon
20:17 $10T to fund AI through 2032
20:51 Clean vs. dirty financing
24:05 The unit economics
26:54 Pricing power: is Ken Griffin right?
32:50 Jevons paradox and open-weight models
38:49 Only 1,900 customers pay $1M+
43:48 Agents are the new form factor
47:40 DRAM, semis and the Cambrian explosion
51:58 The rise of the harness
58:17 Vertical AI: Harvey, Rogo, Lumida
59:44 Where to find Michael

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On one of the busiest days of earnings season, Ram works through the reports from the driver's seat with Grok: Amazon, Reddit, ServiceNow and Norwegian Cruise Line, then Intel and the talks between Marvell and Lumentum.

On Amazon, he sees the cloud as the crown jewel. Hyperscalers keep handing cash to the chipmakers, Google is closing the gap in cloud, and Trainium takes aim at NVIDIA, which he still sees in pole position. He finds consumer spending brisk, and calls Amazon an expensive stock with great businesses inside it.

Reddit sold off on its outlook as AI search pulls traffic away from Google results, and he asks who should buy it. He is bearish on ServiceNow, a ticketing system he expects AI to pressure, and sees cruise lines and airlines as cheap on energy fears while baby boomers keep traveling.

He closes on Intel spending as a CapEx payer rather than a receiver, Marvell's move for Lumentum, NVIDIA playing chess, and the rush of capital into AI assistants.

Chapters

(00:00) One of the busiest days of earnings season

(01:08) Amazon's Trainium push and NVIDIA's lead

(01:55) Grok on Amazon's quarter

(03:44) AWS CapEx and the backlog

(05:13) Hyperscalers hand cash to semiconductors

(05:56) Google closes the cloud gap

(06:24) Trainium, OpenAI and revenue visibility

(07:19) A services economy driven by cloud

(07:32) Consumer spend runs ahead of inflation

(08:06) Why Amazon trades at a premium

(08:36) Return on capital from Amazon's logistics

(10:01) What Amazon's report implies for Shopify

(10:44) Amazon's third-party seller business

(11:49) Tech sells off, Reddit included

(12:19) Reddit loses Google traffic to AI search

(13:05) AEO over SEO

(13:33) Grok on Reddit's quarter

(15:42) Why Reddit sold off

(17:49) AI changes traffic patterns on the web

(18:03) Is Reddit good value?

(18:24) Who should buy Reddit

(18:52) AI owning the customer relationship

(20:42) Bearish on ServiceNow

(21:11) Grok on ServiceNow's quarter

(24:31) ServiceNow's AI pivot

(25:12) Norwegian Cruise Line's quarter

(27:48) Higher energy costs create opportunities

(28:11) More days per year and the baby boomers

(28:43) The Costco hot dog strategy

(29:15) 252 episodes and counting

(29:55) Airlines, cruise lines and the aging demographic

(30:36) Intel, the CapEx payer

(32:02) Marvell and Lumentum

(33:29) Lumentum and the momentum back test

(34:10) NVIDIA is playing chess

(34:55) Big rounds for AI assistants

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Microsoft and Google both reported, and Ram works through the numbers from the driver's seat, starting with Anthropic: the market kept waiting for a shoe to drop, and he can't find one. His read is that semis are cheap and back, and that the hyperscalers' spending flows straight to the CapEx receivers.

On Microsoft, he calls the OpenAI deal incredible: a revenue share, the IP and an early stake, while OpenAI carries the CapEx. He sees Microsoft's hold on financial services and other regulated sectors as durable, even as GitHub and LinkedIn come under pressure, and he hears from venture investors that the big banks see AI coming.

On Google, he still sees a long-term winner that is spending on data centers now to earn the return later. He weighs the two companies' backlog against their CapEx, asks how much of it rests on the frontier labs and on venture-funded demand, and closes on why he thinks agents put us back in 1995, with adoption still early.

Chapters

(00:00) Anthropic, and the shoe that never dropped

(01:02) Semis are cheap and the midterm risk is priced in

(01:35) Microsoft's sales next to Anthropic's growth

(02:23) How semiconductors stopped being a commodity

(03:21) Microsoft's revenue capture from OpenAI

(04:19) CapEx receivers over the hyperscalers

(04:38) Grok on Microsoft's quarter

(05:49) What Microsoft earns from OpenAI

(07:08) Microsoft's stake in OpenAI

(08:27) Microsoft as one of the shrewdest investors in AI

(09:29) Private and public investors read revenue differently

(09:55) How the OpenAI deal came about

(10:59) Chipmakers financing their customers

(11:15) OpenAI broke the contract and Microsoft took the edge

(12:30) Why OpenAI's S-1 won't look like Anthropic's

(13:04) Microsoft's lock on financial services

(13:49) GitHub and LinkedIn under pressure

(14:17) The big banks see AI coming

(15:45) Grok on Microsoft's earnings call

(17:51) Free cash flow and credit to Satya Nadella

(18:37) Did ego cost Google the early deals?

(19:01) Google is still a long-term winner

(19:48) Grok on Alphabet's quarter

(22:07) Backlog against CapEx

(23:03) How much of the backlog is the frontier labs

(23:59) Most of the growth comes from real businesses

(24:30) Still early in AI adoption

(25:08) The CapEx dilemma for CEOs and boards

(25:53) Venture-funded demand is less durable

(26:19) A venture round that has heads exploding

(28:06) All of venture is AI now

(28:45) If Google gets cheap, it's a time-horizon call

(29:15) Meta has no cloud business to monetize

(30:04) Google and Microsoft can afford to be slow

(30:54) Don't underestimate Google

(31:12) Why agents put us back in 1995

(31:35) A processed-foods CEO meets AI

(32:36) Change management is extremely hard

(33:11) Now is the time to build

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A second, deeper look at Anthropic's numbers. Ram calls the release solid to strong: cash levels are up, in large part from operations, the company has financing from several suppliers including Broadcom, and he sees no sign that it is subsidizing tokens. Its CapEx commitments also leave room to walk away from some of them.

On revenue, he finds the number of large-spending customers smaller than most would guess, which leaves room to grow, while power users bring in close to half of revenue. That concentration sits with hyperscalers that could build their own coding tools, though for now Google, Amazon and Microsoft do well renting out the models.

He expects Anthropic to be a volatile stock, since its growth depends on having the best models at the best price, and closes on token demand that keeps expanding, lenders like Blackstone and Apollo, and a market he sees as healing after midterm anxiety.

Chapters

(00:00) Anthropic, a second take

(00:53) Preview of an interview with Michael Parekh

(01:25) A solid to strong release

(01:42) Cash, financing and no token subsidy

(02:38) CapEx obligations and levers on risk

(03:04) Revenue growth and the big-spending customers

(04:20) Customer concentration on the hyperscalers

(05:25) Why Google and Amazon don't need to fight Anthropic

(06:03) Blackstone, Apollo and the bank lenders

(06:19) Will Microsoft and Google close the gap on coding tools?

(07:05) Why Anthropic will be a volatile stock

(07:38) Token demand keeps expanding

(08:27) A market that is healing

(08:49) Post-midterm seasonality

Lumida Wealth Management LLC is a registered investment adviser. SEC registration does not constitute endorsement by the U.S. Securities and Exchange Commission and does not indicate a particular level of skill or ability.

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On the drive after Anthropic filed its S-1, Ram walks through what stood out to him: the gross margin line is gone, replaced by an expense allocation, customer concentration is lower than he expected, and the CapEx obligations look manageable against the revenue coming in. He contrasts that with OpenAI's position and calls the frontier lab race a power-law game, while dismissing the filing's market-size estimate.

Then the engineer's view. Top engineers now work in a harness that orchestrates agents across models, with OpenRouter routing each token, and Ram shares how Lumida's own agents went from talking in Slack to dedicated orchestration tools. He covers Anthropic's pricing tests, who owns the customer's desktop, a zero-margin rival to Higgsfield, and why the labs look more like 90s search engines than imperialists.

He asks Grok for the least-reported S-1 details, adds his own read on depreciation and the revenue tied to Amazon, and closes on chipmakers financing their customers, value in U.S. grid infrastructure, and the sell-off in Brazil.

Chapters

(00:00) AI agents are a bigger deal than we think

(00:30) Anthropic's S-1 drops the gross margin

(01:18) Customer concentration is lower than expected

(01:43) CapEx obligations and pole position over OpenAI

(02:51) A 40 trillion dollar TAM is nonsense

(03:26) Why Ram would be a net seller of frontier labs

(04:16) Top engineers now work in a harness

(05:26) Anthropic's pricing tests and why Claude won't go bankrupt

(06:20) Will engineers keep trusting Anthropic?

(06:43) Agent orchestration tools are moving fast

(08:04) Why Ram tunes in on left-hand turns

(08:31) Who owns the customer desktop?

(09:15) A zero-margin rival takes on Higgsfield

(09:40) AI labs are like 90s search engines, not imperialists

(10:46) Grok on the least-reported S-1 details

(13:43) Depreciation and the revenue tied to Amazon

(14:19) Chipmakers are financing their customers

(15:38) Bargains in U.S. grid infrastructure

(16:34) Brazil sold off, and that could be an opportunity

Lumida Wealth Management LLC is a registered investment adviser. SEC registration does not constitute endorsement by the U.S. Securities and Exchange Commission and does not indicate a particular level of skill or ability.

References to companies, industry themes, market statistics, prior investment activity, or case studies are included for context and should not be construed as a recommendation or endorsement.

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Heading home from Money 2020, Ram shares what a string of conversations in San Francisco taught him: AI adoption is still under-penetrated, even in Silicon Valley, and the frontier labs now look like airlines, with falling token prices and consolidation ahead.

He turns to OpenAI's latest raise and the capex obligations behind it, asks whether Coatue is the Tiger Global of this vintage, and passes on a venture investor's read on the midterms, along with why owning stocks after midterms has historically worked.

Then the venture picture: talent hoarding at big tech, experience as a service, back-to-back markups in hot rounds, why it's hard being a VC, the next real breakthrough in LLMs, and why code review is not the next theme. He closes on the momentum factor and why building an agentic firm beats buying one and bolting on AI.

Chapters

(00:00) Money 2020 and AI adoption in Silicon Valley

(01:00) Frontier labs have airline economics

(01:48) Can the frontier lab unicorns reach escape velocity?

(02:31) AI venture themes and the cost of being late

(03:21) OpenAI's valuation and its capex obligations

(04:27) Is Coatue the new Tiger Global?

(05:46) A venture investor's read on the midterms

(07:20) Owning stocks after the midterms

(08:26) Big tech is hoarding talent

(09:49) Experience as a service

(11:05) Back-to-back markups in hot rounds

(11:51) It's really hard being a VC

(13:35) AI still needs its next big breakthrough

(14:12) Code review and the dev tools that grow fastest

(15:41) Take a look at the momentum factor

(16:11) Build an agentic firm instead of buying one

Lumida Wealth Management LLC is a registered investment adviser. SEC registration does not constitute endorsement by the U.S. Securities and Exchange Commission and does not indicate a particular level of skill or ability.

References to companies, industry themes, market statistics, prior investment activity, or case studies are included for context and should not be construed as a recommendation or endorsement.

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From the 42nd floor of the Transamerica building in San Francisco, after Money 2020, Ram shares what he learned comparing notes with venture investors: most teams still use AI agents for tasks, and very few have AI workers that own whole workflows.

He looks at where token demand is heading and the questions around the frontier labs' spending, why the AI private markets feel expensive and crowded to him, and the choice he thinks Anthropic faces: compete with software companies, or be part of every company's stack.

Then his take on CoreWeave and the neoclouds: a crowded theme in a cost of capital game, NVIDIA's interest in a multipolar cloud, how Elon's spot-price approach differs, and why venture funding is the risk to watch. He closes on public markets, defense tech, and getting every team building with AI.

Chapters

(00:00) Live from San Francisco after Money 2020

(01:01) Agents, AI workers and AI executives

(02:15) Comparing notes on AI-native organizations

(03:23) Token demand and the labs' spending

(04:05) Why the AI private markets feel crowded

(04:54) Anthropic has to pick a side

(06:23) The shift to open weight models

(07:03) Ram's quick take on CoreWeave

(07:52) The neocloud play is done

(08:19) NVIDIA wants a multipolar cloud

(09:04) Would NVIDIA let a neocloud fail?

(10:58) A cost of capital game

(12:48) Elon's spot-price bet

(13:46) Venture funding is the risk

(14:48) Earnings versus sentiment

(15:40) Still early in the AI cycle

(16:19) Defense tech and public markets

(16:46) Get your team building with AI

Lumida Wealth Management LLC is a registered investment adviser. SEC registration does not constitute endorsement by the U.S. Securities and Exchange Commission and does not indicate a particular level of skill or ability.

References to companies, industry themes, market statistics, prior investment activity, or case studies are included for context and should not be construed as a recommendation or endorsement.

Prospective investors should conduct their own diligence and consult their own legal, tax, and financial advisers as appropriate.

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00:00 Intro
00:56 Today's agenda
01:20 The Tesla Roadster: a demonstration of human ingenuity
01:51 "Flying cars and 140 characters": the Roadster demo
02:45 Admiring the products, not the valuation
03:36 Attracting talent, capital, and focus
04:09 What it signals for humanoids and precision engineering
05:03 Agents: hands-on with Meta's Muse
05:55 $11 for tens of millions of tokens: value vs. cost
06:32 Agent orchestration across models and platforms
06:55 OpenRouter: a simple problem with a big outcome
07:31 Why models need to check each other: blind spots and ensembles
08:00 Setting up agents in Slack
08:28 Big Tech does this internally: hundreds of agents
09:16 A startup opportunity: just go build it
09:48 Compute demand and the developer UX gap
10:23 100 agents vs. 1,000 agents
11:22 Data center sentiment and foreign information operations
11:56 Memory and the limits to AI revenue growth
13:09 New markets for coding tools: design and video editing
14:14 Personal assistants and the application layer
15:29 Owning the customer relationship
16:21 Regulated industries: compete with slow incumbents
17:13 Markets: rate-sensitive names and value vs. growth
17:40 Apple and Palantir as valuation barometers
18:53 Buybacks, Anthropic secondaries, and the Jensen interview
20:15 Open-weight models and secondary liquidity
20:42 Live demo constraints: Zoom and parallel agents
21:26 Closing: the promise of AI

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00:00 Intro and agenda
00:45 Bank earnings: lending growth and a strong economy
01:43 The midterm-year pattern: narrow breadth, large caps lead
02:52 Year-after reversals: financials, data center, defense
03:22 Tax-loss harvesting and seasonality
04:07 Product market fit vs. go-to-market fit
05:22 The AI assistant land grab: losing money to own the customer
06:08 Experience market fit: SMS, email, app, and the relationship
07:19 Apple as the master of experiences
08:21 Bank earnings detail: mortgage-sensitive banks lag
08:42 Goldman crushes: volatility and capital markets
09:43 Why Goldman's consumer banking attempts failed
10:02 Go-to-market velocity is the moat
10:47 Low consumer confidence, strong spending
11:15 Consumer health from bank earnings: JPMorgan and Wells Fargo
12:17 JPMorgan's consumer bank: 36% ROE and doubling book value
14:26 Willingness and ability to pay: stories from the front desk
16:19 The economics Nobel and rational expectations
17:12 AI is underestimated: Meta's new model and puzzle training
19:53 Google goes after video editing
20:15 Nvidia, open-weight models, and sovereign AI
24:36 Experience market fit as a moat
25:09 What to look for in a frontier lab's S-1
26:16 Adjusted EBITDA: Buffett's warning
27:21 Skill as a moat: Michael Jordan, Higgsfield, Whisper Flow
29:31 AI in financial services: the big opportunity
30:22 Wealth management vs. investment banking
32:50 What investment bankers actually do
34:29 The size of JPMorgan's consumer bank
36:02 Close: the economy is roaring

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00:00 Intro and agenda
00:35 October 15 tax anxiety: private investments, penalties, and CPAs
01:34 Experience as a service: the new form factor
02:32 Experience-market fit: unified context across channels
03:06 The AI CPA: pulling 1099s and K-1s, estimating returns
04:31 The whole ecosystem: client, CPA, and bookkeeper agents
05:36 From "software eating the world" to "AI eating experiences"
06:34 Early glimmers: Granola, SMS-first AI, and AI advisors on Zoom
07:44 Agents that act: booking, emailing, and the agentic family office
08:16 Licensing and regulation: humans in the car, not driving
09:20 White-collar disruption in the next 6-12 months
10:25 Demand pull vs. slow diffusion
10:31 AI SDRs that know who's calling
11:00 "Tech on tech violence": Meta, GitHub, and new audio models
13:55 Startup and small business mindset in the AI era
14:46 From AI enablement to labor substitution
15:30 SaaS, insurers, and public CPA firms at risk
16:00 Markets: rates have topped, and preferreds at 7.7%
16:46 Mag 7 safe havens vs. rate-sensitive leadership
17:10 Midterm-year dynamics: 2018 and 2022
17:45 Value in semis and memory: Nvidia, TSMC, Applied Materials
18:07 Gap down, close stronger: a familiar pattern
20:13 Hot inflation prints get priced in faster
20:40 A hot economy and the Fed behind the curve
22:14 Real Vision: why 2002 and 2008 comparisons don't hold
24:10 Private credit: coupons vs. principal losses
25:24 Redemptions, refinancing, and rate resets
25:53 The commercial real estate "cheese grater"
27:01 Public markets: AmEx, Goldman, and rate-sensitive conviction
27:49 Compute demand: "any chip made will be sold"
28:37 Preview: defense tech interview
30:20 The four-year cycle and midterm seasonality
31:41 Policy uncertainty, defense stocks, and exquisite consumables

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