One thing that speeds up the reviews and improves my ability to find issues and provide guidance is having the agent work on better review guides (think an html page rendered locally, with object diagrams, decisions/assumptions, animations of data flow if it makes sense, whatever). Those in hand I can read the codebase faster and talk against that document too. I think the end result is better code than I could previously write by hand, in probably 5x the speed.
Usually I can't do more than two projects in parallel though.
So, likely: Gemini Flash, Argon, Carbon [2]; and Claude Opus [3]. Maybe more.
https://google.github.io/eng-practices/review/developer/cl-d...
https://blog.google/innovation-and-ai/models-and-research/ge...
https://www.businessinsider.com/google-finally-lets-all-engi...
The models are great, but the experience resonates. It really depends on what you're doing, and ultimately, how much you care. A 10k LoC PR that feels “tacked on” should help you guess the size of the code base.
So do you care about getting 10k LoC to review, in a 1M LoC code base? How about 3 such PRs? How about reviewing another half a dozen, from colleagues? And doing that 2 or 3 times a week?
Functional code that is perhaps overly defensive or specific in ways that will require updating it in the future? All the time.
What many do not yet understand is that the maintenance burden is a fraction of the effort that it takes you to review the code, much less iterate on it.
I see people on here talk about a supposed eventual collapse of maintainability if they do not review or understand the code.
In reality this never happens. The latest models can salvage and refactor even the biggest mess; all you need to do is ask.
They could probably do it even if source code isn't available and you only have a binary to work with.
I think a lot of pointless arguments on HN stem from a failure to realize that "software" is too big of a field to generalize much of anything.