I had hoped that with the whole “agent” push that we would start seeing more sane usage, like having AI be a fuzzy logic step in a chain of formal logic and existing deterministic tools

I think this is the best you can expect out of LLMs, and the relatively more successful "agentic" AI efforts are probably doing exactly this, but their relative success is serving as hype fuel for the more impossible promises of LLMs. Also, if you have formal logic and deterministic tools wrapping and sanity checking the LLM bits... I think the value add of evaporating rivers and firing up jet turbines to train and serve "cutting edge" models that only screw up 1% of the time isn't there because you can run a open weight model 1/100th the size that screws up 10% of the time instead. (Note one important detail: training costs go up quadratically with model size, so a 100x size model is 10,000x training compute.) I think the frontier LLM companies should have pivoted to prioritizing smaller size, greater efficiency, and actually sustainable business practices 4 years ago. At the very latest, 2 years ago, with the release of 4o OpenAI should have realized pushing up model size was the wrong direction (as they should have realized training Chain-of-Thought was not going to be the magic bullet).

And to be clear I still think this is really generous to the use case of smaller LMs.