I tear through my $200 subscription because I often have 3-4 agents running simultaneously, exploring performance optimizations, building features, monitoring production rollouts, or investigating production problems/customer issues in parallel.

The downside is that I do spend most of my time reading the agent's output these days.

I was with you until this paragraph, which is straight up incorrect. Language choice absolutely matters if your goal is performance.

The most obvious counterexample is that the TypeScript team pretty much did a direct port from TS to Golang, without significantly rewriting their core algorithms or changing their data structures, and it sped up the TS compiler by 10X, which is an enormous performance improvement that would be silly to dismiss as just a "constant." This is because JS is a bad choice of language for implementing a fast compiler, primarily due to its poor support for multithreading.

Umm what? Lots of people do

All of the pelicans so far have had really weird flaws / quirks so I am always a little interested to see how well these models perform at this task, since I've seen all the past pelicans and have some anchoring.

Seeing a truly flawless pelican would tell me that the model has true visual reasoning capabilities as well as good taste.

Not saying it's ideal, just saying it's an option

"LLMs will never " is constantly being disproven every time they scale up to the next 10X and apply architectural improvements.

Their internal representations are so cryptic and complex that even the top AI researchers don't really know how they work or what their limits are. No one is going to take you seriously as a rando HN user if you're claiming to know better than them.