1. Opus 5.5 is a pretty good answer. We iterated a lot on the coordinator, and combined with Opus 5.5 or other modern models, it feels like it strikes the right balance of acting with autonomy while going back to inform you and to validate assumptions.
2. In AB tests and evals, we’ve found that the coordinator has <10% token overhead compared to running sessions directly, and users feel it’s well worth the cost. We’re thinking through ideas for better planning how to pace/use tokens, but don’t have a perfect solution yet. One thing that somewhat works is just asking the model eg. “use around 300k tokens”.
[edit: forgot HN needs newlines for lists]
Does it work to ask them to pace themselves so they can work at a pace that stays within the usage limit windows, so that it can just keep going but perhaps slower?