How to keep local AI evals useful when models keep changing
Sufficient-Curve4753 · reddit · 2026-07-25
The thread asks how to keep local AI evaluations useful as models keep changing.
It highlights the core tension: a fixed test set makes regressions visible, but it can also let models memorize the fixture and overfit to the harness.
Practical tactics mentioned include:
- versioning prompts and models
- keeping hidden holdout cases
- testing tool calls and refusals
- human review of a small sample
- replaying the same task across multiple local models
The author is especially looking for lightweight setups that stay inspectable without turning evaluation into a second product.
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