DeepLearning.AI mapped the 20 skills that make an AI engineer
There is a gap between building an AI demo and building an AI system. DeepLearning.AI published a Skills Map that tries to define exactly what fills that gap, and writer Jennifer Fu put together a practical guide to reading it.
The map organizes AI engineering competency into four pillars and twenty specific skills. According to Fu’s breakdown, testing sits at the center of the framework, which is a different emphasis than most AI content that leads with model selection or prompt design.
Why This Is Worth Your Time
If you are a solopreneur or indie hacker who has shipped an AI-powered feature and found it unreliable in production, this framework is the vocabulary for diagnosing why. Vibe coding gets you to a demo. The twenty skills on this map are what get you to something you can charge for and stand behind.
Fu’s full breakdown is on Level Up Coding. The DeepLearning.AI Skills Map itself is the reference material worth bookmarking if you are thinking seriously about AI engineering as a discipline rather than a side feature.
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