If you've felt lost in AI conversations lately, you're not alone. The field has exploded with new terminology that can make even tech-savvy people feel like they're learning a foreign language.
This matters because understanding these terms isn't just academic. When you're evaluating AI tools for your work or trying to explain limitations to your team, knowing the difference between a hallucination and a prompt matters.
The glossary covers the fundamentals you'll encounter most often. Think LLMs (large language models), the foundation behind tools like ChatGPT, and hallucinations, those confident-sounding but completely wrong responses AI sometimes generates.
You'll also find explanations of prompts, tokens, and other concepts that directly affect how you use these tools. The better you understand what's happening under the hood, the better results you'll get.
This isn't about becoming an AI researcher. It's about having enough fluency to make informed decisions, spot limitations, and use these tools effectively in your actual work.
As AI becomes more embedded in daily workflows, this baseline vocabulary stops being optional. Consider this your cheat sheet for staying conversational in an AI-first world.
