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The barriers to AI engineering are crumbling fast
The barriers to AI engineering are crumbling fast
Having lived through the evolution from DevOps (ClusterHQ) to MLOps (Dotscience) and now diving deep into GenAI with HelixML, I keep seeing the same pattern: complex tools get simpler, workflows get standardized, and suddenly what seemed like rocket science becomes just... more engineering. Something we're calling an " AISpec" - a YAML file that pulls all these pieces together in a way that feels natural to anyone who's worked with modern infrastructure tools. The main thing I want you to take away is this: if you can handle version control and basic deployment workflows, you can build production-ready AI applications.
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