Zitron Squeeze

One story here looks like safety theater colliding with geopolitics. The other looks like a business model colliding with arithmetic.

• Anthropic breach and export controls
• Tokenomics and the pricing crisis
• Corporate cost discipline arrives
• Open source alternatives and market structure
• Silicon Valley monoculture

Source:

• Ed Zitron's Where's Your Ed At — AI's Brokenomics

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An OpenAI IPO sounds like a simple milestone story until you put the financing next to the spending. Then it stops looking like a normal growth company and starts looking like a test of how much strain the market will absorb for AI.

• OpenAI and public-market pressure
• Anthropic's financing structure
• Recursive self-improvement as an explanation
• The AI bubble and the Rot-Com theory
• Why venture capital changed
• What actually holds up

Source:

• Ed Zitron's Where's Your Ed At — Premium: The Silicon Valley Bubble (Part 1)

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The core question here isn't whether AI is useful. It's whether the industry's spending plans make any economic sense at the scale being promised. And once you look at the debt, the token billing, and the revenue assumptions together, the stress points start to line up.

• Compute commitments versus plausible revenue
• Data center debt and the financing bottleneck
• Token billing, visibility, and vendor incentives
• Internal token burn and ROI scrutiny
• Workforce strain and the human layer
• The coming exposé and what to watch

Source:

• Ed Zitron's Where's Your Ed At — AI Is Slowing Down

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The loudest AI story says inevitability: massive demand, massive disruption, massive value. The quieter story is about losses, subsidies, weird billing, concentrated customers, and a lot of people treating demos like proof.

• Manufactured hype
• Financial reality
• Token billing and enterprise reality
• Hallucinations and task limits
• Compute overbuild and NVIDIA exposure
• Job displacement claims

Source:

• Ed Zitron's Where's Your Ed At — Premium: The Hater's Guide To The AI Bubble 3.0

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A lot of the AI argument right now comes down to a weird mismatch. The public story is abundance, efficiency, and inevitability. The financial story looks a lot murkier once you ask who pays, what gets measured, and whether any of it actually holds up without subsidies.

• ROI and the accountability problem
• Token billing reveals the real price
• Why subscriptions look fragile
• Compute costs are not falling the way the story says
• Is this worse than Dot Com
• Dark output and the job replacement story
• What leadership still hasn't answered

Source:

• Ed Zitron's Where's Your Ed At — AI Doesn't Have ROI

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A trillion dollars in GPUs sounds like inevitability until you ask who is actually using them, where they’re going, and how any of this gets paid back. The interesting question isn’t whether AI is real. It’s whether the current scale story survives contact with construction timelines, customer concentration, and basic unit economics.

• NVIDIA demand versus installed reality
• Construction bottlenecks and the backlog problem
• Revenue concentration in AI
• Cash burn and the path to profitability
• Token billing and ROI opacity
• Credit markets and supply-chain exposure
• What holds up and what doesn't

Source:

• Ed Zitron's Where's Your Ed At — Premium: What If...We're In An AI Bubble? (Part 3)

This podcast was created with Podkey. Make your own at https://podkey.fm