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12 AI Terms You Need to Know Before Calling Yourself an AI Engineer
No jargon, no fluff. Just the words you’ll hear in every AI engineering interview and every PR review, explained the way I wish I’d first heard them.
I remember sitting in a meeting where someone said “we need better context engineering before we touch the harness” and I nodded like I understood.
Honestly, I did not understand.
I went home and spent two hours figuring out what I’d just agreed to.
That happens to almost everyone learning AI right now.
The field moved fast, the vocabulary moved faster, and most explanations assume you already know half the words they’re using to explain the other half.
So here are the twelve terms that show up in real work: in interviews, in pull request descriptions, in the Slack messages where something broke at 2am.
Not a textbook glossary. The words people use.
I’ve grouped them into four stages, because that’s roughly the order you’ll run into them as a project grows from “a chatbot that answers questions” into something real people depend on.
