AI BriefingCore Skills Map for AI Engineering
Key point
Andrew Ng analyzed over 10,000 job postings to identify four core skills for AI engineering.
Details
As AI fundamentally transforms software development, Andrew Ng has released the Core Skills Map for AI Engineering to help developers prioritize learning and employers hire suitable talent. This map was derived from the analysis of over 10,000 job postings, expert interviews, and surveys.
The core skills are as follows:
- Building and Deploying AI Applications: The ability to understand AI components such as LLMs, RAG, and agent workflows, control unpredictable outputs using statistical techniques, and run evals and error analysis loops.
- Software Engineering Fundamentals: The ability to design system architectures by understanding trade-offs such as cost, scalability, reliability, and security, and to control coding agents with precise language.
- Leveraging Coding Agents: The ability to understand how agents work and their limitations, manage context, balance planning and execution, and orchestrate multiple agents.
- Shaping the Build
All developers (Full-stack, DevOps, ML Engineer, etc.) must possess these AI engineering skills regardless of their specific role.
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