One company is an anecdote. The repricing thesis needs comparables, and once you line them up they split into two different curves that are easy to confuse.
The two curves
The severe curve is AI destroying the option on effort-and-content moats. Airtable sold at roughly 2.7x ARR because its moat was the effort customers spent modeling workflows, and effort deflates as agents make effort cheap. Chegg lost about 99% of its 2021 value because ChatGPT and Google AI Overviews reproduced its decade of curated homework answers. Prosus wrote Stack Overflow down from a $1.8 billion purchase toward roughly $564 million as AI coding tools cut its question volume by more than three quarters. Same mechanism three times: a moat made of accumulated human labor, regenerated cheaply by a model.
The survivable curve is rate-driven. Squarespace went private at about $7.2 billion and Smartsheet at $8.4 billion, both healthy growing businesses repriced from a growth-story premium down to a cash-flow multiple as money got expensive and private equity became the most rational owner. Six to eight times revenue is not a collapse. It is what a solid software business is worth without the story premium.
Why telling them apart is the whole skill
You survive a rate repricing by waiting. You cannot wait out an AI repricing, because time does not restore a moat, it erodes it. From inside a company, early, the two look identical: multiple down, revenue still growing, cash still coming. A team that reads an AI repricing as a rate cycle will burn its runway waiting for a recovery that structurally cannot arrive. The test is one question: what is your moat denominated in? Split your value into the option (AI-exposed) and the cash flow (rate-exposed), and price each honestly before the market does it for you.