Research

Original research into the economics of AI products: what they cost, how the companies behind them charge, and what a customer can actually find out before paying. Every paper here ships with the dataset behind it.

Wave 1 · Preprint · Dataset frozen 17 August 2026

I spent 4.1 billion tokens to investigate 76 AI platforms. They publish what they're selling — not what you're buying.

A documents-only audit of 76 consumer AI products across 15 categories, coded against an instrument published before collection began. 67 of 72 publish a headline price. 7 of 64 document whether you are charged when a generation fails. The open dataset ships with the audit trail, including 90 dated deviations.

76 products15 categories~48 min readOpen dataset on GitHub

Read the full paper

What we hold ourselves to

Findings come from data we collect and verify ourselves, not from figures reported elsewhere.
Every figure states the date it was collected and the size of the sample behind it.
The method and its limits are published alongside the findings, including what the data cannot show.
Every paper ships with the underlying dataset, so a reader can redo the arithmetic.

Every paper here ships its dataset publicly on GitHub — the records, the instruments, the tools, and every dated correction, so a reader can disagree with us on the evidence rather than on our word.

The standards behind our tool investigations are a separate document: how we investigate. Corrections to research follow the same corrections policy as everything else on this site.