AI
No model without an eval gate
- 1 min read
How we stop a model reaching production before it proves it beats the one already there.
A model that looks better in a demo is not necessarily better for the user. What separates the two is a fixed evaluation set and a metric agreed before the experiment, not after it.
Every release here passes a gate: a set of examples from your own business, and a metric comparing the candidate against what is in production now. It does not pass unless it wins.
This costs a week of release time and prevents the silent regression nobody notices for a month.
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