Tokens, open weights, paperclips and p(doom)? And that's just for starters. Here's a quick primer on the vocabulary of today's arcane yet everyday technology.

AI is moving at a breakneck pace, and frankly, it’s hard to keep up. Sure, it’s cool to have a chatbot that acts like it has a Ph.D. in everything, but the reality is a lot messier. You can’t turn around without running into ChatGPT, Gemini, Claude or Meta AI. We’re drowning in a sea of AI slop, watching job markets shift in real time, and fretting about data centers and an AI-induced doomsday.

If that’s not enough to get your head spinning, the often arcane vocabulary of artificial intelligence is evolving as fast as the code and the staggering array of products. And if you want to do more than just stare at a blinking cursor, you’ve got to speak the language. You can’t exactly navigate a 2026 job interview (or even a casual happy hour) if you’re stumped by LLM, hallucination or claw.

We’re past the “gee-whiz” phase of AI and into the era where it’s basically the new plumbing of the internet. If you’re tired of just nodding along when the talk gets techie, it’s time for a crash course. We’ve rounded up the essential terms you actually need to know so you can stop guessing and start sounding like you know what’s going on.

agent, agentic: AI that executes a task, often autonomously, is an agent , while agentic is the umbrella term for that software category.

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