Every pitch deck this year is dense with AI acronyms. If you're funding or buying one of these products, nodding along without knowing what the words actually mean is an expensive habit. Here's the plain translation.
RAG is the mechanism that turns plausible-sounding into grounded in something real.
LLM - the engine, not the product
A large language model is the underlying engine - ChatGPT, Claude, and similar tools are all LLMs. At its core, it's a very large statistical system that predicts the next word in a sequence, trained on enormous amounts of text. On its own, it knows nothing about your specific business, your customers, or your data. It's general-purpose by default, which is exactly why it needs the next two pieces to become useful for something specific.
API - how the pieces actually talk
An API is simply how two pieces of software exchange information. When a team says they're "building AI," what that usually means in practice is that their product sends a user's text to a model provider through an API, gets a response back, and displays it. That's a legitimate, useful thing to build - it's just worth knowing it's what's actually happening under the phrase.
RAG - the difference between guessing and knowing
Retrieval-Augmented Generation is what makes a model actually accurate about your business instead of just fluent. Rather than hoping the model already knows the answer, RAG searches your own documents first, retrieves the specific relevant passage, and hands that to the model with an instruction to answer using only that material. It's the mechanism that turns "plausible-sounding" into "grounded in something real" - and it's the difference between a chatbot that's occasionally impressive and one you can actually put in front of a customer.
Agents - when the software starts acting, not just answering
An AI agent goes a step further than answering a question: it can take an action - check a database, send an email, update a record - based on what it concludes. That's real capability, and it's also real responsibility, because an agent making a mistake isn't a wrong sentence, it's a wrong action. Knowing which of these four words actually describes what a vendor is proposing is the fastest way to tell a serious technical plan from a slide with the right vocabulary on it.
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