Developer uses 108 AI agents to stress-test his content strategy, exposing two false core assumptions

A developer ran a structured multi-agent research process over his own content strategy, deploying 108 agents to fetch 25 sources and extract 124 individual claims for verification. Of the 25 claims put through adversarial review, 13 were confirmed and 12 were refuted — including the two foundational assumptions the entire plan depended on. The key design choice was reversing the burden of proof, instructing independent verifier agents to default to refuting claims rather than supporting them. One refuted premise held that no canonical source owned the English terminology in his niche, which a single Wikipedia fetch disproved with a detailed, actively maintained article dating to 2006. The author argues that standard LLM-based self-review tends to produce confirmation rather than critique, and that only making refutation an explicit, structural role in the pipeline can expose genuine blind spots.