I'm a principal engineer, been working on the same set of codebases for almost 10 years. I handle the 20% or so of my time that constitutes inbound faster than ever and I know because that inbound volume has clearly increased and yet I have, for the first time ever, begun chipping away at the "nice to have" backlog. My biggest time sink now is interviewing and code reviews -- the latter being directly proportional to the velocity increase across the teams I work with. Actually that's my biggest concern -- we are approaching a breaking point for code review volume.
Sorry I don't have DX stats or token usage stats I can share, but based on the directives from on high, those stats are highly correlated (in the positive).
Assuming inbound volume clearly increased is something like we've been handling more tickets than ever before over the last few quarters or something like that.
I've read this code review thing before, and this tends to go into these studies suggesting that the whole process is taking the same amount of time, but for that to be the case the code reviews would have to take longer on the individual code review level and for you it is just volume increase because of increased tickets being pushed through.
Is there anything about your ticketing strategy? For example do you make your tickets much more atomic than lots of teams who say they do but then end up with things that could be split up into two or three tickets? How much time do spend on preparing tickets for ready for development / ready for AI?
Just trying to identify behavioral patterns in your successful usage that would explain the success. Given the example of throughput of tickets over long time I suppose we can assume that the gain is not illusory.
Sorry I don't have DX stats or token usage stats I can share, but based on the directives from on high, those stats are highly correlated (in the positive).
[edit] And SEV rates are not meaningfully higher.