By the description it appears computational chemistry is stuck in batch processing era. They are yet to discover their equivalent to REPL tight feedback loop workflow.
The only two startups I'm aware of who have managed to make compchem-as-a-service a viable business are Mat3ra and Materials Square. Both are a little rough in their own ways (to be expected from startups), but it's still interesting to see some of this move beyond university clusters.
You will see a lot of similar procedures in, say, AI model training and refinement. Those depend on batch jobs as well, pretty heavily. So the batch process isn't really restricted to the weirdness of academia. My source there is actually working on the systems doing training for frontier models...
(Please forgive some of my hand-waviness or vagueness, it's been nearly 20 years since I last touched a lot of this).
I wouldn't call it "stuck," since it's one of the few fields where batch processing makes sense.
You generally run your jobs on a supercomputer that's being shared by a few hundred other people. You need a scheduling system to allocate resources (e.g., 5 jobs requesting 10 nodes for 8 hours, 1000 jobs requesting 0.5 node for 5 minutes, etc).
It's hard to tighten the workflow when the average calculation takes 2-3 hours of time.