The Future of AI: It’s Not About Training—It’s All About RAG.

In the last few months, I’ve been on a mission to solve a problem an old colleague brought up—though I’m pretty sure he had no idea what he was really asking for. That journey made one thing very clear: AI is still so new in everyday life that most people don’t really know what it can or can’t do. Many “cutting-edge” solutions that feel routine to AI developers are still lightyears from making a difference for the average person.

It got me thinking: what could I build using today’s AI technology that actually makes sense for the work people do every day? So I created [ChatterKB](https://chatterkb.com, a platform designed to add real-world value without requiring a deep tech background.

One big concept that keeps popping up is retrieval augmented generation (RAG). Think of it like this: Instead of teaching AI everything from scratch, you hook it up to existing sources of information—like your product docs, web pages, or social media content. Whenever you ask the AI something, it “retrieves” exactly the details it needs from your own data and uses that info to craft the best response possible.

The standard way to make this work is through vector storage, which is just a fancy term for “chopping your data into smaller pieces and saving it in a system that can instantly find the right information.”

Now, Anthropic is making a similar idea more flexible with their Model Context Protocol. Instead of always relying on these “chopped-up chunks” (embeddings), you can query information from just about anywhere using similar methods.

Why does this matter to you? Soon, any AI tool could instantly tap into all of your relevant data. Forget spending a fortune on specialized training; you’ll be able to provide your files, your brand style guides—whatever you have—right into an AI system. The result? Smarter, faster answers, right when you need them.

And as input limits for these AI models increase, we’ll likely see more specialized use cases—think AI assistants tailored specifically for marketing tasks or brand management. But that’s a conversation for another day.