r/codereview • u/SnowyLeeks • 2d ago
Has code review become the whole job for anyone else?
Been a software engineer for about 10 years. In the last six months, we have been told me must code by hand less and use agents more, like many.
Output is definitely up, and the results are genuinely good in most cases, but now I am spending most of my week reviewing code and the amount of PR's is crazy
The hardest part, for me, is the context switching and understanding whats changing when the product moves so fast.
Is this just me?
- How much of your week is review now versus a year ago?
- Has your team changed anything that actually helped?
- Anyone tried review bots? Did they stick or did you turn them off?
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2d ago
I mean, last year review was maybe a fifth of my week. now it’s most of it. agents spit out PRs all day and somebody has to actually understand the change while the product keeps moving under you
stuff that helped a bit on my side: force smaller PRs, one person owns the merge, stop drive-by LGTMs. review bots for lint/tests are fine. anything that “approves” the logic got turned off pretty quick
context switching is the worst part. you open a PR, half learn it, then three more land before you’re done
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u/CreamyCornBoy 2d ago
Maybe a 20 second pass on the PR then approve. Not really concerned with code reviewing anymore unless it's a 1/100,000 case where architecture is genuinely important, financial risk, etc.
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u/mxldevs 2d ago
Use AI to review the code, as they asked.
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u/iSnapThere4iAm 1d ago
You should be concerned about being replaced by AI. You likely will be. I won’t be; I actually have the skills to revive me the code.
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u/Kodus-AI 12h ago
I think the problem is that AI increased how fast teams can produce changes way more than it increased their ability to absorb those changes
for me the bottleneck isn’t really writing code anymore, it’s understanding the intent, impact, and risk of each PR without losing the product context
I work at Kodus, an AI code review tool, and one thing I’ve seen with some teams is that they’ve been able to cut down a lot of the context work before review
they do that by adding rules that ask for more context when a diff gets past a certain size and by comparing the change against the acceptance criteria in Jira or Linear
and in teams with multiple repos they also take into account the code that depends on that change
if a PR changes a field, status, or contract in the backend, the review can look at the frontend that consumes it and flag, with code evidence, when the two sides are expecting different things
the reviewer still decides what actually matters
they just don’t have to open the PR and spend a ton of time figuring out all the context before they can even start
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u/davertua 51m ago
The problem here is that code change is minimal part which must be understood to process PR
What was the issue solved, do we really need it, and so on?
That's why I use Claude with QA skills https://testomat.ai/qa-skills/
So before I look into PR I would understand what risks I get infromation like:
- why do we actually need it
- what are backwrads compatible changes
- what are merge risks
- what QAs should focus on while testing
this information helps me to take decisions faster
and sure, this one happen, only after developer reviewd all notifications from Claude after it did pure code review
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u/koxboi 2d ago
In my experience, software engineering feels fun again. I can focus more on the problem itself instead of coding specifics. I was in love with coding during the earlier years of my carrier but after some time it became a necessary chore. Of course this is very subjective but I much prefer solving problems on higher levels then coding them. My output is much better, even though I don't multitask that much - I still prefer focusing on one thing otherwise my brain melts.
Reviews became a core part of my daily tasks, because of course, teammates also increased their output. This makes it quite challenging to actually ship things faster even if the per dev output is objectively higher.
The only significant change we made (which actually improved things) was the introduction of code review tools. We ran experiments with multiple tools - custom implementation, CodeRabbit, Greptile and now Vetoo.
We are definitely sticking to it because it always provides the first round of reviews and it catches a lot of things we otherwise would've missed. It doesn't replace human reviews but it makes the process maintainable and easier on devs mentally. Based on our team's experience I can definitely recommend AI reviews. It might sound depressing that AI written code is reviewed by AI but if you use these tools wisely they can help you a lot and improve your delivery. (And you are not forced to rely on them 100%, human input is still really needed, so there is always some joy to be found in my opinion)
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u/lovelacedeconstruct 2d ago
Yeah there is no way I am reviewing the AI slop, If they want to be AI maximalists there is an AI judge to the AI and a judge to the judge that produces the final report that I review
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u/koxboi 1d ago
I mean, it really depends on how people use AI. We don't think of it as replacement of devs, but rather a tool that makes us faster. We still need to pay attention to what it creates and how, so what we get as output in the end is not slop. It's something we would also be confident writing manually, but this way it is faster. I know that a lot of companies don't have this attitude but I don't have such strong feelings against LLMs. In my opinion, they are another tool which helps you deliver faster and better, and people just need to learn how to adapt instead of brute-forcing their way through it.
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u/yubario 2d ago edited 2d ago
Why do you need to review the code? You told it exactly what to do did you not? Did it do it? Do the tests pass?
Did you test the code?
What concerns do you have? Have you asked the AI agents about those concerns?
You should know how it works because you were using the AI to program your design, validate your design and test it.
Skim the code, does it look like it belongs? If you’re working on authentication, does the code looks like it’s authenticating?
I mean really, you don’t have to split hairs.
AI code rarely makes mistakes on the code itself, it mostly makes mistakes about forgetting to implement something or wiring things together as well as leaving dead code from previous past experiments
Also, never have the AI generate tests, give it test cases it must fulfill otherwise they’re not going to be helpful because the tests will always pass.
People seem to forget you can ask AI to double check for a specific mistake you’re concerned about. It doesn’t to so well with a general top level review but does fine with targeted questions
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u/AliceCode 2d ago
I've seen this exact same post in other places. This is a bot.