Context length used to be one of the headline metrics for new models. I hardly hear about it anymore, but I can't imagine it doesn't still play a huge role in practical performance.

Is this truly no longer a bottleneck, or does it just get rolled up in the headline benchmark numbers now?

The models have reached, on average, the 256k/1M window size and that is more than enough for them to complete most tasks without losing attention. I suspect more people are using fresh sessions and markdown between them, than trying to keep fewer long running sessions - this works better overall. We are moving more into the quality >>> quantity realm.