What AI Engineering Actually Looks Like in Production
SMRTR summary
AI engineering is what happens after the demo works — keeping a GenAI system reliable, safe, and affordable under real traffic. The real work lives in retrieval pipelines, context assembly, eval suites, and LLMOps, not in the model call itself. MIT found 95% of enterprise GenAI pilots show no measurable ROI, blaming integration gaps, not model quality. This post breaks down the full production stack and development loop.
SMRTR provides this summary for quick context. The original article belongs to Daily.dev.
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