Issue 18, Oct 7, 2026
The Harness Overfitting Trap
Senior AI Engineer interview at Google DeepMind, and the interviewer asks:
“You fine-tuned an agent on 50K trajectories, all collected through one agent harness. A customer runs it in a different harness on the same kind of task, and performance collapses. Same weights, same task. What did your model actually learn?”
Don’t say: “The new harness has a different system prompt. Tweak the prompt, add a few examples, maybe collect more data.”
Why SFT quietly memorizes framework dialects instead of tasks, and how frontier labs use harness-neutral pipelines to stop catastrophic off-distribution collapse.
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The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.