We used to spend 40–80 hours writing and maintaining brittle ETL code for every integration. Now we spend 4–8 hours deploying MCP (Model Context Protocol) interfaces and letting AI handle the rest. No hardcoded pipelines.

You naively replaced deterministic process w probabilistic process - following a trend that is uneducated.

I am taking screenshots of blogposts like this for a museum exhibit opening next year - lmk if you’re willing.

That's a bold move. Hopefully there are no stray cats.

I have asked AI on multiple occasions to take items from some input and output a table, or a json structure and every time it has simply skipped or ignored several items from the input for no reason.

This sounds like a terrible idea, and nearly impossible to debug when it inevitably drops data.

As others have mentioned this is an extremely odd thing to expect to work....

I'll give an example. I worked for a FTSE 100 company using a very old Product Lifecycle Management system (model manager - based actually on pre-DOS technology)....we had to upgrade it to a new fancy one.

Therefore we had to migrate all data relating to the company, and group companies engineering designs...everything to do with 2D drawings, 3D designs...any important connections etc....all electrical designs....excel sheets related to these containing lists of PCBs and their component parts in Bills Of Materials etc...There is absolutely no way in hell I would trust AI with almost any of that, to get it right....or even to attempt a load without almost immediately erroring.