Why upfront optimization of AI features is unwise: launch, learn, then post-train
matt_slotnick · x · 2026-09-25
- Matt Slotnick argues upfront optimization of AI features is usually unwise: you don't yet have data to fit the model to the workload.
- The P0 is always identifying the valuable workload and removing friction, since models can be easily and quickly swapped.
- The launch-learn-iterate-post-train pattern applies to every major new functionality.
Related event: Practitioners Advise Overprovisioning Frontier Models at AI Feature Launch(4 posts)→
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