GPT-6 Astra in code review: Gains, privacy, and cost

Post by embedding-shape » Sat, Sep 05, 2026, 12:39 PM UTC

9dev wrote: post #50

embedding-shape wrote: post #27

Earlier quoted context omitted.

> All of these are angles an AI reviewer can test for as well, and will (IME) mostly catch mistakes correctly. No, none of today's AI would give you enough signal around "should this thing be built in the first place" nor if it's the correct solution on a high level. They don't understand why you are doing what you are doing, and even if you explain it, they still don't actually understand the motivation and lots of…

I don’t think I claimed agent reviews to be a panacea. It’s a tool that can help you lower the review pressure in companies working with agentic coding tools.

Post by mjmjmjmj » Sat, Sep 05, 2026, 12:40 PM UTC

eterps wrote: post #48

fabianlindfors wrote: post #41

Earlier quoted context omitted.

Forking! We run the entire stack (browser, frontend, backend, database, etc) in a Linux VM, so latency between each of the pieces is as tiny as can be. This is quite different from "standard" E2E tests I've seen where the test browsers uses something like a persistent staging environment. The real key is that we can fork that entire Linux VM to take different paths down our testing scenarios, and can run multiple of…

Which VM technology do you use?

Post by CuriouslyC » Sat, Sep 05, 2026, 12:54 PM UTC

ZephyrBlu wrote: post #43

stingraycharles wrote: post #9

Earlier quoted context omitted.

Yeah I personally don’t understand the point of AI code review tools all that much, as AI is already generating the code as well. All of these AI code review tools create so much noise, yet don’t catch the really important things.

Thinking of AI-generated code and AI code reviews as the same "AI" is not correct. The reviewer is using a fresh context window with no previous knowledge of the changes. That is why it's powerful, because you get the agent to interrogate the code without any preconception about the changes. I found the Devin reviewer to be very good, and have heard good things about Cursor's Bugbot. I've also found asking an agent w…

Post by embedding-shape » Sat, Sep 05, 2026, 1:02 PM UTC

9dev wrote: post #54

embedding-shape wrote: post #51

Earlier quoted context omitted.

Someone asked: > What really important things are human reviews catching in your org? Another person said: > 1. Whether the thing should be done in the first place And you replied: > All of these are angles an AI reviewer can test for as well, and will (IME) mostly catch mistakes correctly Which as I noted, is very far from the truth. I neither claimed that you said "agent reviews are a panacea", but when you claim "…

But that’s the thing, when I say "mostly" that sure doesn’t imply it can solve all those things - it can help to a great extent.

Post by irthomasthomas » Sat, Sep 05, 2026, 1:31 PM UTC

nkmnz wrote: post #36

stingraycharles wrote: post #9

Earlier quoted context omitted.

Yeah I personally don’t understand the point of AI code review tools all that much, as AI is already generating the code as well. All of these AI code review tools create so much noise, yet don’t catch the really important things.

The noise is a huge problem, indeed. Still, a panel of review agents using models and harnesses different from the one implementing a set of changes has proven immensely useful for myself. The panel is basically an n×m matrix of agents and highly specific review prompts, i.e.: - review for intent fulfillment: is the ticket done? - review for correctness: race condition bugs, ... - review for security: check against t…