Edition 6

Meritech's argument is that in fast-rotating AI markets the terminal structure simply cannot be known yet, so the old playbook of waiting for clarity or forcing prior frameworks onto new markets fails.

More specifically, you can wait until markets settle and remove market structure or TAM as a risk, yet miss out on generational returns that accompany such risk. You can also attempt to apply old frameworks to new markets, in turn falling into the trap of paralysis analysis.

A third option, that Meritch espouses, is abstracting recent successes to new frameworks that help simplify decisions down the line. They screen for "Outlier Components": Outlier Growth (top 0.1% of a cohort, north of 100% net dollar retention), Outlier Customer Access (captive or hard-to-reach relationships like government, open-source communities, or hyperscaler partnerships), and an Outlier Team (founders in the top 0.1% by demonstrated achievement, not merely talented).

I've loved this term since I first heard it years ago and, like the author, attributed it to Bill Ackman, though he points out this appears to be wrong.

Return on Brain Damage (ROBD) is a cousin of Buffett's "too hard" pile, and relatedly also a subgroup of return on time.

While a useful metric to consider, you of course cannot calculate it. This author treats it as binary, a red flag that nixes an otherwise interesting idea, and makes clear there is both a financial capital and mental capital side to it, something that can be 5% of your book yet eat 50% of your focus.