La partie après le lancement est celle que vous payez
Évaluation, supervision, et les défaillances qui n'apparaissent qu'une fois de vrais utilisateurs arrivés.
Brouillon. Cet article accompagne la section Articles comme gabarit de mise en page, et il est exclu de la recherche et de l'assistant du site tant qu'il ne porte pas un vrai texte.
Cet article est publié en anglais. Le reste du site est traduit, pas les articles, parce qu'un raisonnement technique traduit automatiquement vaut moins que le même lu dans la langue où il a été écrit.
An AI feature is not finished when it is deployed. That sentence is easy to agree with and almost nobody budgets for it, which is why so many pipelines that were accurate in month one are quietly wrong by month four.
Three things that change without anyone touching the code
- The provider updates the model behind the version string you pinned, or deprecates it entirely.
- An upstream API adds a field, reorders a list, or starts returning
nullwhere it used to return an empty array. - Your own data changes shape, because the business changed and nobody thought to mention it to the pipeline.
What a maintenance loop contains
An evaluation set that reflects real traffic rather than the examples used during the build. A scheduled run of it. An alert when a score moves, and a human who reads that alert. None of this is sophisticated; the reason it is rare is that it produces no demo.
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