LLM Agents Interview Questions, issue 25, Mar 21, 2026
The Diversity Scaling Trap
Senior AI Engineer interview at Google DeepMind, and the interviewer asks:
“You’ve implemented self-consistency (majority voting) to improve an agent’s math reasoning. But scaling the sample size from 10 to 40 yields zero performance gain. What is silently killing your scaling laws?”
Increasing sample count without increasing trajectory entropy breaks the core assumption behind self-consistency gains.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.