Issue 29, Nov 2, 2026
The Sequential Refinement Trap
Senior AI Engineer interview at Google, and the interviewer asks:
“You built a sequential refinement pipeline. Agent 1 drafts, Agent 2 improves it, Agent 3 improves that. Agents 5 through 10 don’t move quality at all. Why is a chain the worst topology for scaling agent collaboration, and what’s the first structural change you’d make?”
Don’t say: “Latency. Each agent waits on the last one. Use a stronger model for each refiner and tighten the prompts.”
Why chaining 10 agents quietly triggers diversity collapse and the structural topology pivot that unlocks true multi-agent scaling.
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The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.