It's very easy to produce something that seemingly works but you can't attest to its quality. The problem is producing something resilient, that is easy to adapt and describes the domain of what you want to do.
If all these things are so great, them why do I still need to do so many things to integrate a bigtech cloud agent with popular tool? Why is it so costly or limited?
UX matters, validation matters, reliability matters, cost matters.
You can't simply wish for a problem not to happen. Someone owns the troubleshooting and the modification and they need to understand the system they're trying to modify.
Replacing scrapers with LLM is an easy and obvious thing, specially when you don't care about quality to a high degree. Other systems such as financial ones don't have that luxury.
One thing I'd be wary of is what "LLM-enriched pipelines" look like. If it's "write a sentence and get a pipeline" then I think that does massively simplify the ammount of work, but there's another reality where people use LLMs to get more features out of existing data, rather than doing the same transformations we do now. Under that one, ETL pipelines would end up taking more time, and being more complex.
We're in an energy/environmental crisis, and we're replacing simple pipelines with (unreliable) gas factories?
Recall that while the cost per token may decrease, CoT multiplies the number of tokens by several orders of magnitude.
