Lesson 1713 of 2116
AI model families: roadmap watching without thrash
New models ship monthly. Pin to dated snapshots, evaluate quarterly, switch only when measurable wins justify the migration cost.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2model roadmaps
- 3snapshots
- 4upgrade discipline
Concept cluster
Terms to connect while reading
Section 1
The premise
If you upgrade every time a new model launches, you spend more time re-evaluating than building. If you never upgrade, you fall behind. A quarterly evaluation cadence with snapshot pins is the discipline that keeps both costs manageable.
What AI does well here
- Behave consistently when pinned to a dated snapshot
- Surface measurable differences between snapshots on the same eval set
- Migrate cleanly when prompts are written portably
What AI cannot do
- Tell you whether a new model is worth migrating to without your eval
- Preserve all prior behaviors across versions
- Promise long-term availability of any given snapshot
Key terms in this lesson
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