Independent AI-economics research desk — measuring the economics of the AI build-out: the race between the productivity lag and the financing runway.
01 · The question
Michael Burry's 2008 call was never that houses were expensive. It was the math of the financing structure underneath them. The AI build-out deserves the same treatment, and the same refusal to argue about vibes. We are not bears shouting "bubble." We do the arithmetic the consensus is skipping, and we report what it says.
The arithmetic resolves to a single tension. The spending is enormous and immediate. The payoff is uncertain and lagged. So the question becomes a race: does the productivity arrive before the financing that funded it has to be repriced?
02 · Two clocks
Clock one — the runway. Can the spending survive? This is capital expenditure versus demand, circular financing, and depreciation that hasn't been honestly marked. The arithmetic of whether the capex is paid for by revenue that actually exists.
Clock two — the lag. Will the payoff arrive? Solow's computers took the better part of a decade to show up in the aggregate productivity statistics — "everywhere except the numbers." AI may earn its own lag-then-boom. Or the lag may outlast the money.
The bull case is a lag-then-boom. The fragility case is capex repriced before the payoff ever lands. Others time one clock or the other; we hold both on a single scoreboard — with explicit falsifiers, revised in public.
03 · Clock one — the money carousel
Capital recirculates among a tight loop — Nvidia, the hyperscalers, OpenAI, Oracle, CoreWeave, Anthropic — where vendors finance the customers who buy their product. When a vendor finances its customer to buy the vendor's product, revenue and demand stop meaning what they appear to mean. The growth is real; what it measures is the open question.
Indicator I4 · circular leverage04 · Clock one — the unmarked cost
Amazon shortened a subset of servers and networking from six years to five, effective Jan 1 2025, citing AI/ML obsolescence verbatim — a change that raised 2025 depreciation by ~$1.4B (FY2025 10-K). Separately, it took ~$920M of one-time accelerated depreciation retiring AI-exposed gear early in Q4 2024 (FY2024 10-K). That reversal is the canary: the first time a hyperscaler names AI to shorten asset lives, and both charges sit in filed 10-Ks.
Meta extended useful life to about 5.5 years the same month — near −$2.9B of FY2025 depreciation, which flatters earnings. Microsoft, Google and Meta extended useful lives and held them; Amazon alone reversed, shortening for AI-exposed gear — the contrarian tell.
Stretch the assumed life and today's earnings look better than the cash can support. Michael Burry (Scion) estimates the understated depreciation near $176B across 2026–2028 — enough to flatter the very earnings base that justifies the capex. We carry it as his allegation: a disclosed short-seller's projection, not an audited figure. The canary, by contrast, is filed. Naming the difference is the point.
Amazon FY2025 10-K Note 1 · Meta FY2025 · $176B — Burry/Scion allegation, Nov 202505 · Clock two — the demand problem
The infrastructure layer is booking real, record revenue. The end-user layer, where the investment must ultimately be repaid, is not yet showing the productivity that would justify it. That is exactly the shape of a lag — and a lag is survivable only for as long as the financing holds. This is where clock two meets clock one.
MIT Project NANDA · Gartner06 · Convergence
We score six indicators — depreciation integrity, capex-vs-demand, insider selling, circular financing, energy, and organic demand. Any one can be explained away. The signal is corroboration: when several light at once, the explanations have to start contradicting each other. They share a common driver (capex ahead of monetization), so we weight their agreement for that overlap rather than as fully independent votes. On the compute bellwether, four of six are elevated — not a coincidence you can narrate around.
The discipline cuts both ways. We deliberately hold two indicators — insider selling and energy — as contained, because forcing them red to fit the story would forfeit the only thing that makes the rest worth reading.
07 · The fork
Demand fails to close the gap in time, depreciation is marked honestly, and the financing structure reprices quickly. Painful, visible, and over relatively fast — the market clears.
The structure is held up — sovereign AI subsidies, national-security compute mandates, too-big-to-fail support. The cost is not erased. It is relocated, and stretched over a longer, quieter horizon.
Propping a structure never deletes the cost; it moves it. The operational tell is the transition itself — the moment market repricing gives way to administrative support. Watching for that handoff is part of the standing read.
08 · Falsifiers
A thesis that can't be killed isn't research, it's faith. Each pillar has an explicit exit. If these print, we revise — in public.
The spending is certain. The payoff is lagged. Everything hangs on which clock finishes first.
This is a living document. Verified figures trace to primary filings; attributed estimates are named as such; unverified figures are flagged, not dressed up. As the data moves, so does the read.