Why this matters
Because model outputs vary, an AI product manager must define quality, failure modes and acceptable trade-offs early.
The practical takeaways
- Define an evaluation set before launch.
- Separate model quality from workflow value.
- Design fallbacks and user correction paths.
How to apply it
Start with one measurable workflow, define the failure boundary, and publish the result with enough context for another builder to reproduce the decision. The goal is not to chase every announcement; it is to turn useful changes into better products, skills and deployment practice.
Editorial note
This is an original FDE editorial synthesis based on the linked source. It is not a translation or reproduction of the source article.