How do you actually become a hirable AI engineer in 2026? You need to be genuinely good in one area. The problem is AI engineering has an enormous surface area — prompt engineering, RAG, agents, fine-tuning, multi-model embeddings, vector databases, LLMOps, evaluation, MCP, and the list goes on.
If you try to learn five new things at once, you'll never learn one effectively. Yes, you should eventually learn many of these, but take them one at a time and understand each deeply before moving on.
Don't jump to the next AI framework the second it drops just because it's the new hype everyone's talking about.
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