Github's core platform doesn't really make that separation, anything a human can leverage on github an AI agent can as well, just faster and with heavier usage. End of day agents and humans are using the same services.
Sure, still need to enable access the same info but feels like bucketing the clients into
bucket1 = clients that were working just fine before (users and whatever automation they had in place)
bucket2 = ai clients that contributed to, if not flat out caused, the scale problems
then slowing down/limiting the bucket2 clients while keeping the bucket1 clients rolling as-is, is both doable and keeps existing customers happy while the underlying infra gets scale/perf improvements needed to support ai clients at scale.
bucket1 = clients that were working just fine before (users and whatever automation they had in place) bucket2 = ai clients that contributed to, if not flat out caused, the scale problems
then slowing down/limiting the bucket2 clients while keeping the bucket1 clients rolling as-is, is both doable and keeps existing customers happy while the underlying infra gets scale/perf improvements needed to support ai clients at scale.