How I Created an AI Version of Myself

Using Retrieval Augmented Generation (RAG) on my content to create a bot that answers using my knowledge

Generative AI could best be described as a frustrating breakthrough. When ChatGPT was first released in late 2022, there was open-mouthed, wide-eyed amazement at the quality of the natural language it produced. Since then, numerous updates to that product have come on the scene, as well as a plethora of competitor products.

But the initial excitement has given way to numerous frustrations about the technology. Controlling the output of these models seems challenging, with hallucinations meaning that the content of what they generate is not always reliable, even if the natural language is persuasive. Cut off dates often mean content is out of date. Models usually don’t have the background context for a specific request, meaning their response is often off the mark or too generic to be useful, especially in organizational or business settings.

Retrieval Augmented Generation (RAG) is a way of using large language models in a substantially more controlled way. Without expensive fine tuning, and using a fairly simple workflow, a model can be fed with relevant contextual information and restricted to only respond based on the information given, or to prioritize…