I think all these platforms chasing code review are doomed. My LLM doesn't need any of this tooling.
We should be reviewing the actual working software. Systems that make it easy and instant to demo any proposed change are what is needed. Code (and specs) are going to fade into obscurity. PR review has already shifted towards validating the product (working software) over the process (code).
The future of software production is more like Replit – not GitHub.
QA?
Software development is a continuous operational undertaking, like having a garden, and not a one-shot "task" like designing a logo. Systems need to be tended to and somebody needs to know how they work, especially if they're business-critical or (in the case of software companies), the business itself.
A corollary point is that many of the rules and policies of the business are solely embedded within the software itself. There is rarely a complete set of documents that says "this is how everything works" -- if you want to know how something works, you ask a software engineer, they take a look inside the codebase and then tell you how it works. In that sense, all software engineers are also product managers (or more accurately, product managers are just crude software engineers, but that's besides the point).
Yes! That's sooo accurate. Tools you use change, the level of abstraction you operate changes, but the role remains.
* Share knowledge about a particular area of the codebase between multiple people
* Share overall engineering knowledge between the parties in the review
* Ensure maintainability of the codebase long-term
* Ensure readability of the code
* Catch architectural/directional omissions (yes, from the planning/architecture phase) before it's really too late and non-reversible change goes in (eg. large destructive DB schema change)
* Ensure changes are small, self-contained, and as often as possible, reversible
* Do some basic manual QA
* Do comprehensive integration testing with a fully built-out system
...
* And yes, catch bugs before they hit production.
A lot of the above could be fun and engaging, and especially knowledge sharing and ensuring maintainability/readability was a very motivating thing for me as a more experienced engineer having learned so much from getting good reviews when I was less experienced.Programmers care about style to ensure readability and thus maintainability of the code, but also to keep changes minimal — if every diff converted between tabs and spaces in the entire codebase, it'd be impossible to see what has really changed with the simple tooling we generally use (one could build diffing tools that ignore changes like these, and they even exist, but are not ubiquitous).
This is also known as being a terrible engineer. If a company enforces human review and someone deliberately tries to circumvent this with an LLM, I'd fire that person in an instant
The reason for human code review is:
1. So *you* understand what's going on, not the LLM, and people can ask you questions about it
2. Because LLMs are not that good at code review
It seems weird to brag about literally not doing your job. It sounds like you could be replaced with a python script, what value do you bring?
I can't help but notice that this person is speaking as a programmer, not the person in charge of employing programmers. Is that what the business values code review for? In my experience, managers enforce code review as a quality control mechanism: the "Find Bugs" step in the article's pyramid. And LLMs are already better than human reviewers at the "Find Bugs" part. Design and alignment with PMs and sales can happen before and after software delivery. At least that's how my employer sees it (and I suspect most other businesses).
It's a rough time to be a programmer who cares about the code, who understands software is a creative process, who understands that designing the software is intertwined with the code, who cares about systems. The hyper-focus on delivery was already a lot to deal with before LLMs.
Nope.
To reduce it down to a single word, I'd say we do code-reviews to assess "taste".
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Code-review is one part of a larger process (the SDLC!), and while review does help with "finding bugs" it is not the singular reason why we do it; and other parts of the SDLC are concerned with finding bugs in the first place, namely the various Test and QA steps in the process; when your code is in the (peer) code-review step then there's an expectation that the author already identified and resolved actual bugs/defects (i.e. where actual-program-behaviour deviates from the spec[1]), so a PR for new functionality is expected to include unit and integration tests to demonstrate that.
Now Claude will gladly take a Jira ticket, write-up a plan/spec, write tests, implement the feature, verify the tests pass, address static-analysis issues, push branch, and submit the PR - and if-the-program-works then it's "correct" and so surely there's nothing really to review and so merging the changes should be a breeze... but I find myself rejecting these PRs all the time because these agents still "just don't get it"[2]. (But I'm sure they'll "get it" eventually; you can't stop progress). We can revisit this topic when we get there; but for now I'm going to reject an AI-authored PR that eschews it.
Good taste is important.
[1] I'm not going to pretend anyone actually writes any kind of spec (informal or otherwise) for the vast majority of software out there; but an unwritten-spec exists when you mentally combine a vague Jira ticket, platform-conventions and common-sense (and that's how Claude in an Agentic Loop works too, except it always has to write-out the Spec.md/Plan.md to disk first, whereas us humans keep things in our head).
[2] I cannot define "it".
What I care about with my department:
- alignment on new stuff being introduced into code bases (the bigger it is, the more important to consider promixity on things the teams are working on tho). also: maybe finding a more optimal solution together, implies a proper PR process (which I always created with my teams, it takes time and we plan for that)
- code quality assessment: maintainability, regression tests, taste, security etc. etc.
- code is improved by expecting a review in the end. if you know you're not reviewed, you might rush and push out suboptimal code. hurts the baseline
Maintainability, bugs, incidents, team understanding, complexity (all impacting future delivery, uptime, user retention, onboarding etc.) are all metrics I care about as they impact the software and the company as a whole directly. A lot of CTOs or other execs/managers might not care, but there are a lot of bullshitters out there. Or maybe I'm just used to complex software in regulated/hard fields, I don't know.
Also, it's not just some subjective value put in human review. If a change causes a major outage and it turns out it's because 5 reviewers were all shirking the company-mandated responsibility of review, and it could trivially have been caught, I would 100% expect those people to get fired. It's not a process issue if people are intentionally circumventing the process.
Nobody thinks its a good idea to fully automate PRs, at least not anyone with software engineering experience. It slows down your ability to solve problems if your code base is an absolute disaster
Again: If someone fully automates everything, what service do they provide? Why are they even there? Especially actively lying in the process when people are trying to force knowledge dissemination with human reviewed PRs
SOX requires code review by a second party. If the reviews are automated, the development process isn't in compliance and that can get expensive in a hurry.
Sort of like how simply having a uniformed police officer on a street corner reduces street crime significantly even if the officer never interacts with anyone.
You’re arguing for experiment over logical proof or reasoning. That’s qualitatively a very different thing, and the former is no adequate replacement for the latter.
I'm always skeptical when I read absolute statements like this.
Especially about specs. They drive and document how the software should work, behave, and under which conditions. In the same moment you write a prompt in natural language, you are writing a spec.
Why should they disappear?
For the same reasoning, we could no longer need books or manuals or documents (is it valuable to keep around that doc about F-22 specs?).
Without them, code drift is a guarantee.
Does anyone trust that a set of human sentences typed into a box is more reliable and precise than objectively exact descriptions of data?
This is not to diminish the utility of these code factories. But surely, if anything provides resistance to drift, it's codebase consistency, standards, and things which must objectively be true for the software to function.
This is not a certain fate but it sure looks likely and is a serious risk. Some software is so low stakes that you can get away with it I’m sure - there are always trade offs.
from the footnotes (sorry if this got a little buried)
> yes of course you can get gpt-5.5 xhigh to do BRILLIANT refactors. But you had to tell it to do that. And to tell it to do that you had to understand your codebase well enough to know it needed doing. We're here talking about why lights-off wont work
i suppose this would also be a good place to ask if you fall in the "high stakes production systems" camp
> If you love vibe coding, please, go on vibing. I still vibe code lots of things, I just also maintain lots of production software (and through HumanLayer, help 1000s of other engineers do the same), so the rest of this is aimed at folks solving hard problems in complex codebases.
In other words you can make the AI act like a software engineer complete with fixing and improving code autonomously (Cursor gave a glimpse of this [0]). It is not a failure of the model to do this automatically but a failure of the human having the wrong instructions.
generic prompting like "review this code" or "make the architecture better" will raise the floor but cannot come close to human-quality code without humans understanding what code exists and what to ask for.
Obviously cursor and other labs have a stake in this going one direction, but I don't buy it, and I don't think you should either.
In fact, "Rebuild sqlite from spec" has all the problems with every other benchmark that I cited - model knows the whole problem up front and never has to iterate on the pile of slop it created cheating its way to a solution.
In any case, politely, I think we're mostly arguing vibes here and I'm not sure its going to get anywhere.
Ok, sure, if your software can be easily exhaustively re-tested on every change.
But in that case, why were you ever doing PR's in the first place? Cargo cult?
"Program testing can be used to show the presence of bugs, but never to show their absence!" -- Edsger W. Dijkstra
I firmly believe there's no reason to employ the latter group. I have several coworkers like this that I could replace with a Claude session or two every week and I'd still have to push back on work and review a lot, but I'd still wind up saving time because then I'd talk directly to Claude.
So I guess my point is that I dislike AI era code review because for some subset of it, I basically can't even assume a human has ever looked at it, and that by doing so, I'm doing the work for one of my coworkers who is probably doing his grocery shopping at 2PM as I read it.
I am currently ignoring them.
Slop merchants get slop reviews. I just point my clanker at their PRs and ask them to critically review the PR and they typically find lots of issues.
Isn't that what commits are? Or ... should be?
That's the most killer feature of git, that it's so easy to slice your commits any way you desire, and then redo again. The use case of taking a chunk and commit separately is so common it even got a special mode in the add command. That, and the super fast jumping between branches is what set it apart from contemporary version control systems.
The extra context provided by the review tool is gone when the review is done anyway. Review systems come and go, but the commit log is for eternity.
I tried experimenting with what is ultimately a treesitter based approach - https://github.com/0x007BA7/codebook
And really liked it. Definitely nowhere near production ready but I think theres room for a player to come in and do something similar.
(more precisely the sub-tickets merge into a bigger feature branch, which in turn gets squash merged into the main branch at the end. i have a tool that automates this flow with a gui and ticket management.)
When $EDITOR = VSCode there's a shortcut on the GitHub PR page: if you type a . it opens in github.dev in a VSCode instance.
PR review of agent generated code sucks because agents are, in my experience, very poor at authoring for review. This makes sense because the review process is not represented in the resulting code artifact which is what they're trained on. Agents are always producing much larger changes than should be in a single step, and often touch unrelated code with poor judgement of whether it should be included or not.
A good PR tells a story to the reader that leaves them confident in the result. That means knowing the reader and how they think, and that is something LLMs are very bad at.
If you leave it up to raw LLM outputs you're not going to get the results you're after. If you put on your engineering hat and think about your problem statement and what tools you can bring to bear on it you'll find you can likely craft a PR authoring skill and a set of evals for that skill that satisfies your requirements with a high enough degree of reliability.
I'm sure we can improve things, I'm sure it will get better over time, but I'd say we're a small fraction of the way towards where we need to be, and trending in the wrong direction with long trajectory development creating bigger changes on average.
This sounds good for review. Except… the comments are never intent or trade-offs, they’re always the “what”, which the code then duplicates right after. Comments should be short, concise “why”. Often I look at code and think “hm this is odd, I wouldn’t have done it this way, is there some constraint I don’t know about?”
The comment should explain that, not what the code is doing. If I wanted to know what the code is doing I’d read the code!
They don't do them. They discuss the changes as the team are doing them (software design and architecture), they automate all the things that would be nitpicks (linting, formatting, etc), and they adhere to a strict 'Do not break the build' rule so merging in something can't be disastrous (with a lot of automated checks and tests to prove that's true). They also make sure there's a robust rollback process just in case.
Once you do all that the PR process is pointless. It never catches anything useful. The team can trust one another to merge without that gate.
manual PR reviews can catch things that llms currently miss. Examples are duplicated code, lack of unit tests or introducing security issues. None of these really break the build. So just requiring "do not break the build" is a very low barrier.
Tests also are useless unless you have a smart system that runs the new test WITHOUT the changes and see it break. Most teams I see today have the LLM write a test along with the change, without a guarantee that the tests actually guard the feature.
I didn't say LLMs though. I'm talking about the sort of code quality tooling that's been in use for decades - Sonarqube, Codacy, CodeClimate, etc for code quality, eslint for AST-based code rule checking (easily picks up duplication for example), Istanbul for code coverage, Wiz or Github Advanced Security for security.
These are well known industry standards for knowing a code change is correct without giving it to an LLM to guess at. If you have them, and they're well configured, and you maintain the tooling properly, then PRs become unhelpful gates that don't find problems.
They will not handle any architectural problems (i.e. this method is correct but doesn't belong on this package, or this method is called isX - but has side effects).
And I am pretty sure that none of them do what I am saying with the tests. i.e. run tests without the associated code change and see them fail. I am also pretty certain that none of them will understand problems with breaking backward compatibility (i.e., a fix that is correct that breaks the setup of all existing users).
In other words, it is possible today to create a PR that passes all checks, all security scans, all analysis tools, all test suite while still being wrong due to architecture, backwards compatibilty, wrong scope etc. So even before and even after LLMs a human is needed there.
PRs might become unhelpful as you say if in the future one of the two things we happen
1) LLMs have unlimited context so you can pass all source code plus all architectural designs them 2) We have a super smart analysis tool that is one level above what we have today (including llms)
We are not there yet.
I find the format of PRs to be better suited to discussion than slack/teams messages. Key developers need to actively sign off, code suggestions are much easier, and the CICD makes sure we're not wasting time discussing code that's not compliant with obvious standards.
Obviously some level of agreement is needed before creating a ticket at all, but implementation details around say creating a terraform module to share functionality between teams do need to be discussed somewhere - and it can be difficult for any individual dev to have all the low level context.
Yes, in an ideal world, PRs read well, are a joy to review, reflect what you discussed etc etc. We have to be real; there is only so much we can do to that end.
I'm not sure how the best teams do PR review, from my perspective it sucks. I'm talking specifically about the UX. I've always hated Github's PR page, so I typically reviewed by pulling down the branch and opening the diff with $EDITOR.
These days I think there's really no excuse for the awful UX. Linear (a company that isn't even in the domain of code review) put out a basic PR review feature[0] that is already better than what GH offers. It's simple: point a small model at the PR, group file changes together based on theme, add some commentary and sort by importance (schema changes > openapi spec).
Immediately, so much mental load has been reduced without the reviewer or the requester doing anything. This feature is pretty damn basic, and I think there are obvious next steps like generating visualisations which a dedicated product could find the time to implement.
Keen to hear others thoughts on why this is the wrong approach, or if there are tools in wide use that solve for this, or why this isnt the right problem to focus on.
0 - https://linear.app/docs/diffs#guides