Hot take:
A lot of what’s being called “AI engineering” right now feels like:
prompt tweaking
chaining APIs
adding retries/guardrails
Not actually building models or understanding them deeply.
Don’t get me wrong—there’s real skill in making these systems work.
But are we over-labeling it as “engineering” when most of the complexity is still in the model and infra built by others?
Curious where people draw the line between:
using AI effectively
vs actually engineering AI systems
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