AI engineering vs traditional software engineering: what changes in architecture?
The question is about AI Engineering .
The core shift is from deterministic control flow to probabilistic components. Traditional software guarantees that the same input produces the same output every time, which is why unit tests with fixed pass/fail assertions work. AI systems built on trained models can return different outputs for identical inputs depending on sampling settings, context, or model version, so the architecture has to plan for that variability instead of assuming it away.
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