That’s a good question. I think LLMs will have a place in the connector space. It would be really cool if they could dynamically handle changes in the source (t

That’s a good question. I think LLMs will have a place in the connector space. It would be really cool if they could dynamically handle changes in the source (the api changed and added some new data new columns etc). But right now — at least I — don’t trust AI to do much of anything in terms of ingestion. When data is extracted from the source it’s got to be as close to a 1:1 of the source as possible. Any errors introduced will have a snowball effect down the line. For data cleaning we do tend to write the same sort of things over and over. And that’s where I think things could improve. Though what makes a data engineer special in my mind is that they get to know the nuances of data in detail. They get familiar with the columns and their meanings to the business and the expected volume and all sorts of things. And when you get that deeply involved with the data you clearly see where things are jarringly and almost like a vet to a sick animal you write data cleaning things because you care about the data that much.