A very prolific coworker who fully embraced claude has inflicted the team with a flood of AI-generated PRs. About six months later, it is his frequent bemoaning at the standup that their PR don't get reviewed, languishing in inattention. I don't think anyone - including myself - _intentionally_ avoid his PRs. It's just that he doesn't make it easy for the team to look at.
This single headline perfectly captures what I have been thinking. It's not that I reject AI content, but it takes _effort_ to review and weed out any mistakes. When your thoughtful reviews that take an hour(because the PR is typically large, and you want to be _right_ when you're pointing out a hallucination) gets an AI-generated response with AI-generated amendments, It doesn't feel _nice_. I feel dismissed and it has continuously trained me to subconsciously avoid his PRs. After all, the team is fully onboarded with AI, so it's not like there is a lack of PRs to review.
It looks like the sentiment isn't just isolated for me.
As someone who pushed ~4x the median PRs on my team before LLMs were a thing, I kind of think the problem here is PRs as a concept. Code review doesn't scale to prolific humans, it definitely can't scale to agents.
And the exact same things you would need to safely give up on PRs for human developers (auto-formatters, linters, comprehensive end-to-end tests, continuous deployment pipelines, etc), are also things that place meaningful guardrails on LLMs, and help them maintain a reasonable quality bar.
Gently, as long as you work with humans, you should consider yourself working _for_ those humans. Everyone needs shared state to work from, and that's just the cost of doing business.
That said, sometimes low-trust environments are the issue, not PRs. In a higher trust environment, PR review is a helpful thing you usually desire, not dread.
> In a higher trust environment, PR review is a helpful thing you usually desire, not dread
Respectfully, in a high-trust environment, feedback should be delivered well before the PR stage. If you've let someone write a whole bunch of code without having a shared understanding of how the solution should work, you may have earlier process issues that PRs are papering over
> I've worked with people who consider themselves 'prolific humans'. Someone always has to tidy upp later, and its never them
I run both infrastructure and security - that means a lot of relatively self-contained PRs to infrastructure-as-code and dependency management systems. I'm also the team lead, which makes me responsible for a lot of throwaway prototyping, as well as cleaning up anyone else's mess...
Yes, the prolific-but-damaging engineers are all too common in corporate. But particularly in startup land, you tend to find your high-performers wearing a lot of hats at once.
I have always considered Kent Beck understood this the best, the scaling for code reviews as you go to reduced release timeframes is to pair program, that brings the number of people reviewing it down but also increases the understanding for the reviewer. Comprehensive end to end tests are more a replacement for manual quality assurance for regressions.
I am not sure there is a good analogue for reviews in the AI world. The human operating the AI should obviously review everything produced but that is clearly not as good as a second pair of human MK1 eye balls from pair programming.
Comprehensive end-to-end tests and CI can only attest to correctness, most engineers worth their salt won't review code only in regards to that aspect though.
In the bad old days before auto-formatters and linters, PRs were heavily used to enforce style guidelines. If we can enforce both style and correctness in our CI pipeline, what is actually left?
> If you think human is a bottleneck, then either optimize for humans, or remove humans. What's the problem?
Sadly, in my case, it is the auditor. Our SOC2 documents have this lovely "every change has been reviewed by at least one other human", and it's going to be a fun battle to get that reworded
Either you were a head above the rest of the team and had the intellect to produce high quality value adding work, or then you were the "move fast break things" type of guy producing a lot of extra liability and work for others.
Even before AI, I've worked with people who would produce a huge wall of code and ask for review, and sometimes that code was completely off base or needed a significant rework.
I would always feel bad in those cases, because it's clear they spent a lot of time, and I'm going to have to say "no" and they will feel like they wasted a ton of effort.
The thought process around this has started shifting for me in the last few weeks. I'm a lot more comfortable saying "no" with a list of concerns when I suspect the code is AI-generated, and I see others doing the same. CLs that would be sitting around for days because no one wants to be the first to say, "this is bad, don't do this" now get quicker feedback.
The good thing is this feedback doesn't feel like as big a deal as it used to because people are less personally attached to code they generated in 30 minutes vs. code they hand crafted over a week. I had at least 2 LLM-generated PRs that were complete, correct, tested, and pre-reviewed by me, but I got feedback that they were going in the wrong direction. This would have been 8 hours of wasted effort a year ago, but now it's just an extra 30 minutes to rework the direction with LLM assistance.
> I would always feel bad in those cases, because it's clear they spent a lot of time, and I'm going to have to say "no" and they will feel like they wasted a ton of effort.
I get this feeling, too. I do however think the onus is on the developer to make something reviewable by their team members if they want a speedy review. Stacked PRs, scoping things down, properly structuring commits so you can review commit-by-commit for example.
I also think that "I spent a bunch of time on this" is not a valid reason for expecting an approval. It should hurt if you've produced a bunch of code that is way off target, even if it ends up implementing the feature. That's how I learned at least.
A proper way to go about large projects, in my opinion, is the same as with software development at large. Fail fast if possible. Draw up a crude boxes and arrows sketch or just discuss how you want the code to integrate with whatever already exists and invite the team to comment. If no one has anything to say, well then they can't complain later when you implement that approach. But if anyone cares then most likely valueable input will come that makes the end result better.
It’s good that clankers are not afraid of throwing away code. The biggest problem with code generation (that is version controlled) is maintenance. It’s better to throw away questionable code rather than say eh, we don’t quite understand this part (and our agents can’t make a compelling story about it) but we spent a lot of effort on it and it apparently works so we better keep it.
.. only if you know what the code is doing, though. Often the requirements get scattered and lost to the winds and the code is the only record of its own idiosyncratic behavior. And yes, someone's depending on the bugs in it.
I often hear people say lately, "why should I bother to read this, if you didn't even think it was worth writing?"
I've been thinking about this in art. Is it the end result that matters, or the process of creating it?
I once saw a hideous sculpture. Didn't like it at all. Then the video zoomed and I saw that the whole thing (quite massive) had been hand-built out of individual toothpicks, and suddenly I thought it was amazing.
Perhaps an even better example: I read a story of a man in india who carved a passage through a mountain, so there would be a shorter route from his remote village to the city. He did it by hand and it took him 20 years. We seem to have an instinctive admiration for heroic effort.
In business, generally only the end result matters. Although, the end result also includes the client's perception of how the product was made... (see also: fake fairtrade etc.) In a meaningful way, the perception, the story, is reality.
> Is it the end result that matters, or the process of creating it?
I think this comment misses the point. Let's forget about AI and assume that there are three developers: A, B, and C. Now, A is supposed to make a PR, but instead they describe it to B, and B writes the code. C reviews the PR and gives feedback. A passes the feedback and the responses between B and C.
As you see, this is not easy for either B or C, and A is totally useless in this scenario. When you replace B with an LLM that doesn't get tired or bored, only C complains about the process.
> Is it the end result that matters, or the process of creating it?
One of the main reasons that art is valuable is in its ability to communicate emotions. Good art has the ability to serialize emotions within the artist and deserialize them within the mind of the viewer. It's not just "wow, this is a pretty picture", it's "wow, this is how another person sees the world, and now that I understand that, I feel an intimate connection with them".
Fight fire with fire: point copilot/claude/codex to review their PRs. Prompt "Review the PR#XYZ which is vibe coded and presumably low-quality. Find all problems, big and small. Team guidelines at docs/conventions/styleguide.md, docs/conventions/architecture.md, docs/conventions/principles.md. Post inline comments to github".
Run several rounds of such reviews until the clanker fails to find problems.
Because the problems AI causes are fundamentally problems of good design. It has the same problems of large teams, but less politics. Do your design well ahead of time, and AI review, or a large team, will amplify what you can do. Potentially by a lot.
Do it badly (or like most companies: do it with bad knowledge of the problem or just don't do it at all) and both team and AI will make a mess of things. If the team is made up of inexperienced programmers, they won't even complain, in fact I've seen teams that like this to be happening. At least in AI reviews I've always seen "grumbling" (in the sense of what you might call mean comments)
Everybody values their own time more than other's.
The fix, imho, is for the reviewers to also use ai to review the code. However, the ultimate responsibility for the outcome(s) should be on the committer - you commit it, you own it, so to speak. If there's an incident, they need to be the one paged in the middle of the night. Bugs resulting from it will land on their desk.
Speak for yourself. I highly value other people’s time, to the extent that I should probably value my time higher than I do for my own sake.
Doing something that wastes other people’s time or makes more work for them than necessary makes me feel awful.
I’ve always worked in a way that respects other people’s time and I always tried to make sure I did everything I could to minimize the work I’m asking someone to do for me.
AI and companies reward sociopathic behavior. When he eventually complains to his boss that his work isn't being merged and it's been done for days/weeks/months that will filter up and look bad on the people holding him up.
I'm sure this person's manager knows that having trouble getting PRs reviewed can (but not always) be a signal of a deeper problem. It could be that no one one the team knows the domain, it could be that no one like the person, but most likely it's that the PRs are frequently bad and no one wants to bother.
He isn’t shipping anything. Asking for code review is not shipping.
This is the complaint:
> he doesn't make it easy for the team to look at.
He has traded readability for volume. The lack of readability is causing him to ship less. This was a bad trade because the readability is the bottleneck not the code creation. He should improve readability.
The solution is that he spends more time scoping the size of the PR so that it’s reviewable and understands the code he’s submitting well enough to have discussions about it. And that he does so human to human so that they can come to mutual understanding.
Less WIP is better for the throughput. If you saturate all the review bandwidth you're just wasting your time creating more PRs, the time would be better spent helping others get their PRs merged.
That's not how anything works. Even if he says he's going to take responsibility, when the customer call comes in at midnight you're going to be the one fixing his problems.
The reviewer gets to merge the PR so their name appears on all the great new features and they are credited for them. That would end his unfair behaviour of dumping effort onto other people.
I wonder if there is a tool that could equally waste their time. Like the worlds most pedantic code review bot that just gets the PR raising bot to spin wheels forever.
In big software teams, the bottleneck is team communication. I've run big and small teams. If I want to speed things up, I remove people from the team. Everything gets easier. This has worked amazingly well every time I've done this over the past decades. Removing people doesn't have to mean firing them necessarily. Splitting teams is a good reflex. But of course the people you remove from a team are typically not the best performers. I was discussing this with a friend of mine who runs a small company. Exact same thing. He reduced the team size by 1 and the velocity went up almost instantly. This person was a bottleneck in the team and was slowing down people around him. After identifying the problem, solving it unblocked the rest of the team.
This was true long before AI. With AI the difference is just a lot bigger. It exposes team inefficiencies quite mercilessly. We have a big glaring issue with the current AI tools not being to suitable for usage by multiple users. All interactions are one on one. Which means hand offs between tools and people are bottle necked on people communicating with each other. So, any issues there with people delaying, gate keeping, etc. become very visible.
The sentiment of pushing back on AI is understandable but probably not a productive reflex. We need to find more effective ways on staying on top of massive amounts of changes. It's not going to slow down and insisting on manually reviewing all code is not going to be a long term sustainable way of developing software. It simply does not scale. I'd question the added value of manual PR reviews at this point. Are they finding real issues? Are we valuing those issues correctly? Could we come up with automated ways to find and fix those same issues? There are a lot of open questions about how we are going to do this. But no question about the notion that we need to up our game on this front.
Efficiency is not magic. Its bounded. Above and below limits the environment can sustain it, systems will destabalize. If All the Great White Sharks magically get more efficient at hunting over night ecosystem will collapse. Individuals and teams have never scaled at this speed to the levels they have. And there is no signal at system wide level that a sustainable limit has been crossed. So People will happily believe things are getting more efficient at individual/team scale while at system scale things get more fragile. This is why we ended up with central banks deciding interest rates and controlling money supply. Before that any one could print cash. They all thought they were great efficient geniuses.
The chimp troupe us not prepared for stuff that effects the entire system.
I’ve been making Codex and Claude get their work reviewed by most recent best performing model of their own family, and each other’s, for months.
On top of that, we have been running multi-model AI reviews on every PR through their respective GitHub integrations (Codex, Gemini, Copilot, Greptile, CodeRabbit).
They never fully overlap, and yet they somehow usually all miss the same things. The most significant improvement came from having agents commit their plan along with their work.
On the upside, it means I get to focus my reviews on different things.
> I'd question the added value of manual PR reviews at this point.
Yeah, why not reduce the team size to zero while you are at it?
These generalizations about software engineering have never been useful, IMO. Context is everything, there is no flow chart for building a perfect software process.
Although, I'd say you are absolutely delusional if you think we are universally beyond the point where manual review of pull requests is required.
I can't imagine working for a place that has a big bucket of PRs that either get reviewed or languish for some amount of time based on who feels like reviewing them. I'm not saying there's anything wrong with it, just that everywhere I've ever worked, there are expected features with priorities and timelines and some project manager or product person breathing down your neck to get them out the door.
An interesting question to him and management might be what his own role is now and whether he's still needed. If he's not doing any reviews then you could yourself directly prompt the code and review.
The question I’ve seen here is responsibility. If you submit a PR that means that it was your best effort, and you’re willing to stand behind it to some degree. With AI, some people, when the scathing review comes back, just say “haha look at that stupid AI.” The reviewer might just as well run his own AI to do the review, but it may make huge errors as well. In that scenario, who is held accountable when there is a big bug or it degrades the quality of the code base?
Ultimately what it means to be a professional is that you are responsible for your work. That’s why you get a salary instead of being paid by the token.
Have you spoken to him about this? If he's clueless enough to send AI responses to human messages, he's probably clueless enough to not realise why people don't do that.
Fight fire with fire. Ask Fable to conduct an adversarial /ultareview of their PR and send the same wall of text back to them. If there are excessive defects, ask them in standup if they actually reviewed the PR themselves before sending it. If there aren’t maybe they are on to something. I think like in law, the human submitting the work is responsible for its quality, not the AI.
I'm not sure what the right vocabulary would be to describe this, but this sounds more like the calculations behind nuclear war than a healthy collegiality or cooperative work relationship. This sets up a competition to determine a loser based on resource scarcity, not a way to achieve mutual goals to advance the organization's goals.
You are thinking of "game theory" and it's what happens when your coworkers don't give a shit. And all it takes is one, both because they can degrade product quality faster than you can gate it or fix it and because the performance assessment techniques are about 3 years behind the state of LLMs and if they play, you have to also or you'll get shit on from such a height you won't even know what hit you.
And once you start playing the game, then one day - it doesn't take long - you wake up and ask yourself if this is how you want to spend 8 hours of your life monday through friday. I think a lot of us are saying no but now need to figure out where our money is going to come from. I don't have the answers.
“Token Standoff.” The most efficient token consumer wins. This mutually assured time efficiency destruction is driven by management support of aggressive use of AI in an attempt to, in some combination, increase productive and constrain labor costs.
This is the point where you decide. It used to be low stakes and easy to care about the job you did for other people.
Do you want to put the same effort into your job when nobody else does, or should you reserve your thoughts and just feed it back into the LLM?
The LLMs are being advertised as output increasers but companies so far are using them as excuses to fire people instead of creating previously unbelievable things. It might be better to feed your coworkers output back in and use your thoughts to start the company you thought you never had time for.
What I don’t understand is what value is the person adding to this equation? Put another way, what’s the difference between them feeding the wall of text to the LLM, and you feeding the wall of text to the LLM, bypassing them in the process entirely?
The role of the person in the equation is to take personal responsibility for the proposed change and review the changes prior to PR submission. You can't put AI on a PIP. It's acceptable to use AI as a coding assistant in 2026, but if a human is not reviewing what they submit and taking responsibility, their value is on par with a ChatGPT subscription.
The same as if they said it was copied from stack overflow, or if it’s wrong; “I think there’s a problem here, it’s XYZ”. If your peer ignores you and you were wrong, it was their call to make. If you were right - take it to them or the manager depending on how many times it’s happened.
Don’t ever write this in a professional environment. It’s childish ant achieves nothing other than pissing off the person it’s targeted at and probably the manager who now has to deal with a shitty behaviour complaint.
> Ask Fable to conduct an adversarial /ultareview of their PR and send the same wall of text back to them.
Not necessary. Use Haiku.
The response doesn't need to be good, it just needs to be substantial. Presumably the goal here is basically DoS of the problematic colleague through token limits.
I mean frankly this should just be part of the standard process. By the time any person is looking at it there's no reason it should not have gone through an AI review.
It's not always feasible of course but I think there is real, worthwhile discipline in trying to get change requests small and it matters more with agents. It's very easy to let it balloon into gazillions of files and lines.
why leave comments intended for your human colleague when they will only forward them to the bot?
why not speak directly to the bot yourself instead? then you can drop pretenses and get to the point
I find this to be a new variant of the old behavior where a colleague comments on a typo in a PR, and the team later moans about laborious back and forth for small nitpicks, instead of simply editing the typo right there (and perhaps leaving a note that they did so)
I had this happen to me twice. The first time I ignored it, second time I responddd with “I could have asked ChatGPT myself but I asked you”. Never happened again.
Because it doesn't matter what you say to the bot. You might as well have a conversation with yourself about the PR.
The bot isn't making decisions. It's not choosing to submit extensive PRs with bad code. The colleague is the one who needs to actually learn something here, and the problem is that confronting him about it directly is widely considered to be bad form. This is, of course, a deeply unhealthy aspect of our corporate culture. We need to be more open to honest communication, even when it's either uncomplimentary of one of the people involved, or counter to the prevailing opinions within the company.
"I'm writing tons of code, and the process is stumbling where the guy whose job it is to review code isn't reviewing it."
"I'm not reviewing code."
Sometimes I wonder: how does someone go and think so much about their coworkers, and never once think about how they themselves look?
Even if I sympathize with the people complaining about their poorly chosen GitHub-based workflow - whose purpose is to let pull requests languish, for the most part - and how they stumble when overwhelmed with solutions. It's obvious to me, that the people who complain the loudest about the anti-sociality of LLM authored code in their precious harmonious low-effort workplace status quo: they are projecting.
Imagine you are a restaurant reviewer. Your job is unquestionably to go to restaurants, order and eat food, and write a review. The restaurant's job is to provide you food to eat and review.
You go to a new restaurant, and order some dishes, and one of the plates your server brings out is a big ol pile of dog shit.
Who's being anti-social in this situation? The restaurant is doing its job and all they're asking is that you do yours. On the other hand, you have certain expectations about what you order from the restaurant and they're not being met. Who's anti-social?
I cannot think of a single actual food critic that would consider it acceptable for a restaurant to serve a dish for review that they went to the restaurant next door to get. If the critic wanted to eat at/review that restaurant they would simply have gone there instead.
The person who "writes" code is also supposed to review their own work, and answer for that. If they won't do that - well - they should be fired. But if you have weak or uninvolved leadership, then the team's only rational recourse is to shun them.
It’s much more effort to verify that code is correct than it is to produce it. This is the case even for human-written code, and now that we face a torrent of ok-looking probably-usable AI generated code, the problem is compounded infinitely.
If someone’s using AI to generate a large quantity of actually-tested, actually-good code then that’s one thing. If they’re generating a fire hose of slop and demanding that others do the actual human time-consuming work of validating that code then that person is the problem. It’s hard to tell which is the case here.
This no longer works when bad faith actors will push code straight from LLMs with little review, and respond to your comments with LLM responses. They will constantly leave you with the responsibility of verifying the output. You are the human in their loop. This is a brutal asymmetry. In the past, at least you knew a person probably spent more time handwriting code than you will spend reviewing it. This no longer applies, now the reviewer can easily spend more time than the author.
The thing that makes it scale is to default to "no" and require the other party to convince you of "yes". Just put the burden of proof where it belongs.
If they don't manage, then that's their problem.
Communicating this in a way that is viable for a business scenario certainly comes with its own difficulties, but that is a solvable problem.
In fact, you can use AI to stress test your communication there.
Just throw what you want to say at the AI but don't tell it that it is you who wrote it. Then tune the input until it stops saying that you're the problem and starts agreeing with you.
Highly recommend. It's a perfect emotion-driven cargo-culting normie simulator that never calls HR on you.
Because we're all on call for the service, and tragedy of the commons exists. That coworker isn't paying the cost, everyone else is paying a fraction of it, and it builds over time.
This exactly reflects my feelings lately. I have a specific coworker who has gone somewhat overboard - every single code review, answer to any question on email or Teams, every new story, even their personal opinions during a design or ideas meeting, are all direct AI output with no massaging or human touch or review. They're working on planning out an upcoming project, and I just get verbose and long documents to review, and based on the issues I find I doubt they are even looked over first beforehand.
I understand that the information may be accurate, even helpful at times, but feeling like I'm constantly talking to an AI chat bot all the time gets tiring. And I don't appreciate having to double-check everyone else's AI generated responses for them.
I've seen this, too. There is a workplace personality that sees the job as a 2-player game between themself and the corporation. They think the game is to min-max their effort to personal career benefit, and they don't care how much it inconveniences anyone else.
Before AI they had to actually put in work, or at least play games of trying to steal credit from other people without getting noticed. Now that AI appeared, they see it as the ultimate way to take credit for work they didn't do: Put everything into Claude, let it do the work, copy and past output back to someone else. Minimum effort invested, maximum visibility achieved.
It will continue as long as they think they're getting away with it. If managers aren't willing to intervene, or worse if they encourage this due to the volume of output that seems to be appearing, it's only going to get worse.
I’m conflicted after reading this comment, because I think I would be that personality in my workplace, largely because I believe that’s the only sane position to take as a worker with ~0 power over the decisions made that can entirely destabilise your life.
On the other hand, my priority isn’t maximising my personal career benefit, but the collective benefit of my team, so I suppose I either see it more as a 2v1 sorta game, or perhaps my “player” is an amalgam of myself and my teammates. Playing this way, outsourcing everything you do to an LLM is the worst move, because you lose the touchpoints that tell you where the friction is in your team.
I think everyone should be looking to balance their work effort against the payout of the job. They should also be changing jobs when the effort to reward ratio starts to become unfavorable compared to other jobs on the market.
The problem with the personality above is that the person isn't playing like a team (like you said) but as an individual maximizing their own visibility while loading their coworkers up with the review effort. They found an asymmetry to abuse (they generate text easily, coworkers get a lot of extra work to review it). They don't care what it costs their coworkers. They just like that it makes them look good.
Whenever I try to articulate this issue to people during more casual AI discussions, I always refer to “study guides” in college.
I don’t know how many of y’all did these, but I’m sure I wasn’t the only person. At my undergrad it was very common for a group of students to all to get together, compare notes from lectures and readings, and basically come up with a group study guide of sorts. People were given specific sections to share, you didn’t just send all of your notes - usually 2 people per section’s take on that portion. You could always tell who just copy and pasted their shorthand (usually indecipherable) and who actually took the time to edit it/clean it up. This was at a time when almost everyone did it on laptops.
The people who took the time to make their portion(s) digestible for others were asked back, the others weren’t.
Another idea to slow down the stream of slop of big PRs: request to split big PRs into smaller PRs. This typically keeps the author+clanker busy for quite some time. E.g. I got a 5k lines PR to review; requested to split that into 7 smaller, self-contained PRs. Took them about a week to finish this work.
Either that, or call them / walk up to their desk and pick a point from the wall of text and ask them to explain what they mean by it. Then watch them turn red as they have no idea what the message they sent to you means.
Sure, some people have no self awareness. In that case you can change your approach, if you are a manager or otherwise invested in the company you can put pressure on them to increase the quality of their work and to own the things they submit. Bring up specific examples of poor quality work, errors in documents/messages, etc.
Or if you don't care you can just ignore this persons messages.
I got sent a 6-page spec document with a footnote that says "this spec was created with AI, so it may have nonsensical sections. Feel free to fix them."
I had someone submit a PR that was 3000 lines of shell scripts. Totally useless crap. I tried repeatedly asking him why he made particular choices and it was so painfully obvious that he had absolutely no idea and was just inventing bullshit answers. I would rather he have just said "I don't know, Claude added that", then tell obvious lies to my face.
And that's the point where you can stop to hide your true opinion, no? "How am I supposed to review a thing the supposed author didn't even read or understand himself?"
I tried this when my skip level boss sent us a wall of text from ChatGPT that didn’t make any sense. He didn’t care. He said it was “just an idea”. He likely spent all of 5 minutes on it, while we spent a collective 15 hours dealing with it, before finally going to him and calling it out.
He’s sent a couple more emails like that since. I don’t even bother to read them once I see the format.
This feels like a BOFH response but I'm strangely not opposed to it; If you generate something, you should own it ... regardless of what tool you used to generate it.
I've had a colleague call it out 'Is this AI slop? Please write your opinion'. I don't think I could do that myself, but I really appreciate that they were drawing attention to it
Management, responding to someone who takes your advice to "ignore it": "So we've noticed that there's this guy who is doing tons of work, and you have chosen to do no work?"
Communicate with your boss. "I'm ignoring this guy's slop because he's spewing slop, but not actually doing his job, and if I stop to deal with all of it, I won't be able to do my job".
Yes, "not actually doing his job". If he's sending you un-reviewed, un-filtered, untouched AI output, that's not doing his job.
100% agreed. I've shared output I didn't fully understand, didn't feel good good about it, and now I really try to digest, understand, and be able to actually talk about it if I expect other people to do the same. I hope in time your coworker comes to similar realizations.
I can't imagine my opinions just being AI slop that I've parroted. Surely you embellish just a little? Claude's so often bone-headed about things, this horrifies me. Gemini's worse. Even when the model agrees with me, it starts making me wonder if I'm not somehow wrong.
In any human relationship, nobody wants to be the one who noticeably makes more effort to communicate, keep in touch, resolve conflicts, and so on. The idea of reciprocity and fairness are deeply entrenched in our minds, and that of many other social animals. If they don't care about me, why should I care about them? It's the iterated prisoner's dilemma again – freeriding is equivalent to defecting.
It surprises me how many people have voluntarily relegated their entire job to LLM Prompter. If your work is indistinguishable from that of a machine, what’s to stop your boss cutting out the middleman and using the machine directly? I would have thought that people would be trying their hardest to prove their worth in this new world we’re in.
I actively support “my boss” to run Claude Code. I offered them to help and made jokes it’s so easy these days they might as well just call Claude Code themselves. I’ve shown I could plop in their documents of feedback and Claude fixed the issues.
I have worked with non-tech employees to set up Claude to help them do small tasks. I’ve helped to review and improve completely vibe-coded projects by such employees.
I’m not sure what my role will be, but I fully embrace that my traditional role of writing code is gone.
It's even worse when everyone around you is using it. How can you keep up? Companies face the same dilemma: investors, competitors, and users already use AI and have factored it into their expectations.
Even if there's a lot of noise there's clearly something real there. People are shipping more working products than was previously possible, they're debugging faster than was previously possible, and various other things. I mean you can go fishing for things to confirm your skepticism if you want but it's pretty clear to me.
Sure, but that doesn't mean that you can't filter signal from noise.
So the actual problem statement is not "how do I keep up" but "how do I correctly tune my filter", which is solvable.
The biggest challenge there I think is that many people are not prepared for just how sharp and uncompromising that filter needs to be, but that too is solvable.
If you're not going to experiment at all you're not going to be able to do that. Agentic coding was basically a joke the first time I tried it. Now it isn't.
having worked in tech and now running my own company..
the honest truth is that maybe 10-20% of SWE (at best) are “good”. sure it is harsh but i won't lie. if you're good you'll probably relate.
the rest kind of suck.
i’ve never gotten anything lower than Exceeds Expectations in my career so I’ve seen how awful some engineers were. i’ve seen how amazing a tiny minority were and i made them my mentors.
these days i have a simple policy.
if they cannot think, they are fired. why waste resources (time and money) on someone who can’t use their brain? i’d rather give AI credits to someone who uses their brain.
thinking is the humans job. the ai needs to execute on what the human thought of, improved, planned.
Everybody talks about finding that mythical 10X but in my recent hiring experience it's more like there's a whole bunch of 0Xs and the trick is finding the actual 1Xs among them.
All my experience in trying to hire developers has been wading through an endless stream of people who were just useless.
Me: I want to represent a 2d grid, what data structure should we use?
Them: A string?
This was someone applying for senior engineer. Others I've had filled their CV with SQL related acronyms. But couldn't explain what a foreign key was and then stubbornly insisted that at their current corp they would never ever use foreign keys in their SQL database!
I've had senior engineer when asked how to check if we had a 2d array with an item at x,y tell me if anything is on the same column or row, they couldn't do it, couldn't even verbalise how to approach it.
"Web Developers" who didn't know the difference between GET and POST. Web Developers that have never heard of PUT or what it would be used for.
I have a question I usually ask which is "How would you convert a Julian yyyy-ddd date string to a military yyyy-mm-dd date string?" (I explain how a Julian date works if they aren't familiar with it.)
The answer that almost guarantees I'll hire you is "there's got to be a library function for that, so I look in the manual". Almost as good is somebody whiteboarding how they'd convert ddd to mm-dd (and then account for leap years, etc.)
I get a disturbing number of people who say things like "I would communicate with the person asking for this to see what they're really intending blah blah"
My favorite answer was on a phone interview where he just hung up and wouldn't answer when we called back.
Also now is it 1x in individual productivity or >=1x in team productivity. As anyone multiplying teams productivity by less than one is bad. Probably lot worse than actual 0x.
Someone who produces absolutely nothing and have no impact has cost, but is still better than someone who produces net negative. And the people who solely act as interface between LLM and whatever might fall to later category.
It's the Pareto principle of course, as well as the normal distribution. Many firms have been able to succeed in the market just by hiring only good engineers over average ones.
yeah but these days it is even more important to filter out bads
and even at "good" companies you have people who can game the system to get in, and then they struggle to get anything done on time or be responsible for taking on and completing any initiatives bigger than a single task on a bigger scope.
Indeed. You really need to find people who don't want to play politics and instead get stuff done. I'm still not sure how to hire for these sorts of people in the age of AI, where people even cheat in interviews. Maybe probation programs? Have multiple people work for a month or two and cut those who don't succeed.
this is what I've been doing, and obviously I have a startup so I need to double-ensure that I don't onboard any bads. you can start people off as contractors too.
I still think a single in person LC style (doesn't have to be LC per se, could be domain specific) logical thinking/reasoning exercise is useful. I want to ensure the person can actually put 2 and 2 together and think. This is just a fast filter.
If they seem like they can think, then I like to do 2-3 systems design interviews. I'll try to give them something related to things I like, such as graph structures, writing a complex query that needs to be dynamically generated, or something related to infrastructure or how they'd do something that I've already done. After all, this is MY project they're joining.
So far that has worked well.
Few more things -
I like to test if they are a humble type (they can work on a team putting ego on the side - the mission is our number 1 priority). if they say they know something that i know and asked, then they can be sure I'm going to drill them on it. if it turns out they lied, i'm not wasting more time. Thanks for your time, take care. This is very important to me. Just say you don't know, it isn't a big deal because ever since like 1994 that has not been an issue. You can just learn things online, and AI makes that even faster. I am never afraid to say I don't know something, and I've asked plenty of "dumb" questions (while doing some due diligence first) so I don't really mind.
Can they handle information overload? I am the type of person who has multiple branches in my head of actions I can take next, so while I may appear stressed I'm really not. Can they keep up? Our goal as software engineers should be to come up with solutions that solve the problem in a way that makes building on it simpler in the future. My goal is simplicity and effectiveness. So I'll see if they can keep up, and eventually reduce the work to be done into atomic pieces. This is a fun exercise because it is collaborative and we get to bounce ideas fast back and forth.
Finally, I like to let them use their favorite tools, including AI tools (codex, claude, some ppl have esoteric custom stuff which is cool), to solve a problem together. It might be code related, it might not. Really depends on my mood. I like to see how they work and what sort of output they can come up with. This filters out people who only ask AI stuff, instead of having some framework they've already developed to be effective.
Honestly I don't know how to scale this process. I'm not really going to feel bad either about firing fast, ultimately this is a business and I don't want customers to suffer because we have some issues internally.
At the same time, I wonder if I even need to build out an org with 100s of people. That was an inefficiency (look at all the layoffs), and it is traumatic.
If I can find a few great people who can be supercharged and turbocharged and electrified with AI, then they can take on & own bigger responsibilities. My number 1 goal is to ensure they're with me on the mission, and after that all things seem to sort of fit into place.
Firing fast works both ways. If I joined your company and I thought you fired someone too fast I would leave, not because I might get fired, but because I've seen where that kind of leadership takes things.
Might not be solveable. At some point the effort in finding that someone might be larger than the benefit you get from just using the second, third, fourth best. Or using some flawed approximation hiring mechanism. There's just so much noise now. And it hits the good job seekers too.
I've seen this happen a bunch too, though fortunately it hasn't been _that_ common. More often is managers that don't understand things using AI tools to try to understand them, mostly failing, and then regurgitating the LLM output during a meeting. Added as a link on my blog, too, since I have a similar article.
I'd say it's because we're tasking ourselves with dumb stuff. No one half-asses building a shelter that keeps their family alive, or throwing a new favorite bowl on the pottery wheel. But instead of that we're writing posts for Facebook etc etc so we can (???) profit. So of course we want bots to do this all this dumb stuff, and of course we get dumb results.
For some things, yes. But I'm half-assing some really cool stuff right now. Made a scraper to pull my city's meeting minutes, agendas, recordings, made transcripts. Regex for "Flock", found every mention, passed those files into a cheap model (DeepSeek V4), had an understanding of who in my city is down with building the surveillance state and who isn't. I've got research on everyone, and had emails drafted for each one based on what they said. Quotes and figures and all. I lightly polished each email and fired 'em off. Already got some replies back. Plenty more in the quiver too (pulled and analyzed CSVs of FOIA'd datasets).
If they're gonna spy on me with AI cameras, I can oppose them with AI research. :)
Did you use some stuff like https://github.com/CouncilDataProject or roll your own? Been curious about how to integrate local knowledge like this since local news seems to have lost the niche.
I rolled my own. I hadn’t heard of this one, but I looked into stuff like OpenStates (now privately for-profit owned, ugh). My city just uses a Wordpress site so it’s structured enough. I’m looking at building something to ingest cities with Granicus and one other big local government meeting recorder via API whose name I forget. That should get decent coverage. There’s no way to catch the long tail of every local government’s recording process. Some cities people will just have to do manually. But it’s easy enough with LLM help.
Nope, I used a minute fraction of the technology they have, along with open records as is my right in this country, to stand up for my Fourth Amendment right to travel without creeps stalking my every move. I need to make my specific framework a bit more generic and then I'll put it here on HN. Or just offer a platform where people can bring an OR key and it can run on their city.
Citizens monitoring their government is literally THE foundation of democracy (ok, maybe voting comes before it, but then you have to monitor who you voted for to see if they’re doing what you voted for).
What I find strange is how rarely LLM output is distributed alongside the LLM input, especially outside of code repos. Why can't I rerun the prompt that resulted in your work next year, when models have gotten better? Are people ashamed of their prompts? Ashamed of having used AI? i unno
Prompt used to generate this message: "Create a comment for Hacker News which bemoans the lack of AI prompts being shared with the stuff it creates. Speculate on the reasons and create a call for engagement. Use quantum hyperthinking. End with a typo to prove your humanity."
This is beautiful. I even had people reach out to me with suspiciously long "long time no chat" instant messages until I realised they were AI written (in one case misspelling the name of their own partner). "If you are requesting human attention, demonstrate human effort" is going to be my new answer to that!
This is exactly the same as the ""If you didn't take the time to write something, I'm not going to the take the time to read it" mantra that was floating about HN a few months ago.
I think in many cases people use LLM outputs without even understanding the contents of it. You're only really able to say something in your own words if you understand it. As a matter of fact, it is a good way of probing if you truly grok something. So it isn't just laziness to write, but also laziness (or inability) to understand.
A couple of weeks ago I essentially failed the Turing test (took to be an AI). I found it a bit annoying, so I built Possibly Made By A Human. It tracks your keyboard use (not the content, ms between keystrokes etc) and produces a signature for you. It can of course be spoofed, but that also takes some effort.
If the agent does everything for you it means it can do everything for the next person. At that point you're replaceable and have no value in your field. Learn things deeply even if you use AI because its the deep knowledge workers that will keep getting hired.
> Learn things deeply even if you use AI because its the deep knowledge workers that will keep getting hired.
The problem is that this realistically is only applicable and actionable to a subset of the labor pool, and that subset is decreasing.
There are a lot of people who discovered that their "deep knowledge" and "deep skill" wasn't as deep as they thought (read: "deep" enough to make them irreplaceable to their employer). People are generally pretty good at overestimating their value.
This isn't unique to code or AI. In creative writing courses, we were asked to give thoughtful critiques of (human written) stories and excerpts, and often I felt as if I were doing more work than the original author. If you can't be bothered to review your manuscript, or at least run it through a spellchecker, why should I waste my time on it?
Atlassian's in-built AI assistant for JIRA will generate a task description with a complete SDLC task breakdown, requirements and deliverables.
While the person creating the task will need to provide some details and modify some of the generated text (if they bother to read it) - the sheer verbosity and the fact it's clearly generated just makes you not want to engage with it.
I increasingly find that I don't care whether I am talking to an anonymous AI or an anonymous human, and believe that we will increasingly stop caring.
Because why not? AI will simply on average be nicer to talk to than most humans, with clearer thinking and better arguments, less contradictions, and easier to comprehend.
I don't know how humans could compete with that (but it also does not seem all that horrible, given that it will be available to every human.)
This is not to say that this idea is uncomplicated or comfortable, in different ways. Just that I think it's true and that it might even be good.
I think it’s safe to say that this will not be consensus. Personally, I am getting increasingly (irrationally) angry at AI generated content. AI generated art quite literally makes me nautious. I mean an actual, physical reaction where I feel queasy.
I know I’m not the only one who feels this way, and notice more and more people reporting the same. Several of my non-technical
AI generated content is bland and soulless. There’s only so much bland and soulless most people can take in their life before they start to get fed up.
When everything feels the same, nothing is interesting anymore.
But that is not what is going to happen. This is obviously a phase, and the progression is clearly visible: The models are getting better at everything, including writing. Why would that stop now?
Everyday AI writing was not a thing with GPT 3.5. It happened more around GPT 4o. And now some people are now entirely comfortable with using AI writing and not even trying to hide it -- while it's obviously still fairly garbage and clearly identifiable unless prompted with care, triggering the strong averse reaction. But as long as that is the case, we can simply assume that the makers also know this, dislike it, and the models will get trained to get better at it, because that is what has happened so far.
Eventually how will you be able to tell? You won't. You can't. And that goes for the rest of us. And I suspect everything will just feel somewhat nicer.
I think I've been following this subconsciously as LLM artifacts reached some threshold of pervasiveness across the work I do. If I can sense (maybe eventually I won't be able to because of how capable the technology becomes?) that what I'm reading is wholly regurgitated out by an LLM, I automatically care less and feel inclined to respond in kind by generating an artificial response in return.
More and more I'm generating AI emails, often to people outside the company and often to do with technical issues / integrations we have / APIs. So far I don't think the people I'm emailing are really using AI as human responses are, well, lacking. What would be great is new email conventions for different communication pathways.
Human -> Human (think we have this sorted)
AI -> Human
AI -> AI
If you are doing AI -> Human, then you need to be curating the response and understanding what it is saying, also, make sure its not leaking internal details or committing you to have phone calls/video chats (it does that). This works really well for the most, and humans respond with requested content. Quite often my AI debugs problems with their systems which I know little about. But humans do odd things like send screen shots of logs rather than text (they also leak internal details of their systems they potentially shouldn't). I used to tell people the content is partly AI, but now I just send the curated email without mentioning AI.
For AI -> AI you kind of want a hand over document as an attachment to an email. Only thing here is making sure there's no injection of security risks. But quite often instead of getting a human response to my AI generated emails, it would actually be nicer to hear from their AI which could give a better context/details. It would be really nice to be able to go, can you have your AI talk to my AI :) (security is a major issue here)
AI is able to read input from AI. Humans are able to read input from humans. Also AI is pretty good in reading input from humans. So we don't really need AI -> AI. Just output for humans and you are fine. You can still attach details and this is true for both AI and humans. So human output should be the goal for everyone and everything.
? you missed the point, ironically showing the problem with human responses :) humans are super bad at providing information, they concentrate on singular things, especially if they think they have a point / suspect they know what the problem is, but if they are wrong their response doesn't have enough to go on, so you have back and forth.
If the requester stops applying common sense, the reviewer has to apply more of it, and there's a finite review budget. I will deal with requests on a lowest review effort-first basis, just like you did on the other side.
I use AI as an editor on informational writing all the time and it's good at pointing out flaws in what I wrote. But I don't really love reading a document that's obviously in the voice of Claude if you're asking for my opinion on it. But it kind of depends on the writing -- a change request description, most people are too lazy to do better than the AI would, and there are other kinds of documentation that normally just wouldn't get done. But like for a design doc where you're asking me to pore over it now even though I don't necessarily get anything out of it it's distasteful when I see phrases that are obviously from AI.
Many artist and content creator is now asked to show the "behind the scene" or a full session recording, which nobody care enough to check. This is frustrating and demotivating the artist.
Expect the same demotivating effect on the software contributor.
If you think reading _forwarded_ AI response are cheap, you can run your own LLM. It is the same amount work on you
This isn’t sufficient, it needs to be “if you are asking for assumption of accountability, demonstrate human effort.”
In my experience, people who make requests like this don’t care about your attention, they only care about getting you on the hook for something. Your application of attention as a requirement for that is irrelevant to them.
This has been my rule since the moment generative AI hit the scene. If you're not willing to put in the effort to create the thing, why should I put in effort to consume it?
Perfect. I find myself applying the same principle to online discussion boards and comment threads. Humans post a question looking for other human input and get replies saying "I asked Gemini and it said...". I find that ignorant and rude when the context is a request for human insight.
This is just an old engineering principle of work amplification. For an input of x you shouldn’t routinely do nx. If you do you’ll get flooded. Debounce, throttle, load shed, improve throughput and latency. Lots of solutions. Just map it to the problem and apply.
In the past you had coworker who produced volumes of code. Same principle.
> For human code review requests, I always review my AI-generated code first.
I remember a time in the ancient past (2025 maybe) that your PR was your responsibility, whether or not you typed it with your meat fingers or cranked it out of the Giant Plagarism Machine. It’s absurd to think that the above quote is now something approaching controversial.
Why this suddenly becomes urgent? For long time we had automatic emails with "thank you" which weren't written by humans, why something is different today?
It really depends. In many cases, you absolutely shouldn’t.
In some however, you should. For instance, yesterday I sent a lengthy email in a language I barely speak threatening legal action against a business. I had an LLM translate/write it as it’s a language Google translate makes a mess of, every time.
So in that case, you’d be advised to read it lest you end up in court.
We developers understand this when we are forced to read slop, and most of us recognise it in art and music.
I wonder if we forget that people using unthinking, default interfaces in AI generated apps might start to feel the same way: “it feels like no care was taken here so why should I give it my time?”
I see this on my team. I honestly thought as engineers we'd all understand the limitations and nuance a bit better. Right now it's kind of a shit show. In addition to seeing my teammates open huge AI generated PRs and just asking for review without them having done much verification, I'm also seeing my teammates (smart ones whom I respect) use AI to "do code reviews". And we already have automated AI code reviews added to our PRs. So now I'm sometimes getting hallucinated BS responses from "human" reviews.
This makes me absolutely SURE that the general public is fucked and that we're going to start seeing huge AI generated fuckups on a regular basis. If people in this industry, basically experts compared to the general public, are misusing this tech in such seemingly obvious ways, imagine the ways non technical people will misunderstand and misapply it. Of course, with the help of overhyped BS from everyone hyping and selling it.
I think this is because a lot of people think more is more. Wow look at all the detail and bullet points! No one on the receiving end actually wants that though. When I use AI to write, it's to boil it down to the minimum bits needed. I wish more people would use it that way.
It's the empty calories of literature. More would be more if there actually was more but AI writing is making it bigger without adding anything actually more. It inserts loads of fluff and repetition that takes longer to read but doesn't exchange more information or ideas.
Meh. Just this week, I've had two Sonnet 4.8 agents generate, in parallel, a 2000 line wall of brittle bullshit, and a well architected solution with 20% of the amount of code, to the same problem, from the exact same initial context, and very similar prompts. Come on, they can do poor quality work too.
Not true for HR. Despite their name, which is a complete mislead - except handling humans as resources -, nothing human exists there, robotic approaches are the norm there.
So feel free to use AI to pimp your resume, they will use AI to process it.
It did in many corners, there are some interesting designs on r/stablediffusion, and regular people too are using them to make posters and invitation cards for example.
If "putting a random seed into a set of swappable character parts" counts as "generative art" then it sure made a ton of money when people cared about hying NFTs.
Now you have to add typos and not use completely standard elements of style that some people have been using for ages, like emdashes and "it's not X, it's Y"
> when [sending AI generated content to teammates], I take care to clearly label what is AI generated
Reading AI-generated text for hours every day, it's obvious to me.
I take care to make my messages easily readable. I don't care if they're AI-made, as long as they're short.
I'm a very verbose person, and if I don't make an effort at being concise, I'm just as annoying as the average AI.
Being flooded with AI text every day has made me appreciate brevity because I'm exposed to so little of it.
With half a dozen people who don't read or listen to half of what the others do, slop + cognitive drift is a bad cocktail.
It's just not as big of a problem on my own projects, because the ideas that get fed to the slop-machine are not that different from one day to the next.
---
> For human code review requests, I always review my AI-generated code first.
For human code review requests, I always review ANY code I submit first.
This is partly because it's the agreed-upon culture where I work now.
And partly because the codebase is not robust enough for slop.
I have hobby projects where this does not apply. I spend half of my time in those projects building hard guardrails.
---
> Keeping AI generated content clearly labeled and demonstrating human effort helps show consideration for teammates
I actually like the shamelessness, because it's honest.
So often this year when I ask "why did you do X?" pointing at a line, my colleague doesn't know.
Because they didn't really write that line, and they didn't really internalise the choices made.
When my colleague sends me a text dump from Claude, I know that my role is just being a sub-agent.
Demonstrating human effort: I'd like to see more of it.
One way is to spend more time owning "cognitive debt" as part of the daily cycle.
Brevity is the big disaster of human-generated text since the rise of the phone as default device and the appearance of Twitter. To discuss matters with sufficient depth and nuance, one often has to write a few solid paragraphs.
If people are now wincing at longform text because they automatically assume it was LLM-generated, then that bodes ill.
To add to this, there seems to be an inability to process metaphor and simile in the younger generations. Likely as a result of the same deficit. They've become very literal, and often mistake anything that's well written for AI slop.
There's a sweet spot between AI slop and 144 characters. I can tell within a few sentences whether there's a human on the other end getting to the point, or an AI dancing around the point and finding 3 different ways to say the same thing.
This headline has been seeing some popularity. But it's never made any sense. This is just the labor theory of value, applied to documents.
The labor theory of value doesn't work for documents any more than it works for anything else. If I do something that's easy for me, and it's valuable to you, you'll still want it. If I do something that's difficult for me, it will be less valuable to you, because the difficulty I have with it implies that what I produce will be of lower quality.
This is all equally true of automatically-generated documents. If they're valuable, people will want to read them. Whether it was unpleasant for someone to create them isn't a factor.
So where is this slogan coming from? Are people just afraid to admit that the documents they're getting are valueless?
I am offering a product (via MCP) that interacts with LLMs and user data. Every single day I get user support emails to my inbox written by their LLMs with LLM hallucinations. If the user (a human) would have read them before, that would save me a lot of time and anger!
Your post sounds logical at the first glance, but has nothing to do with the reality. The topic title is totally on point! If the user would put human effort in it, I wouldn't get those crappy emails.
The problem is that I don't know before I read a doc whether or not it will be useful and valuable.
If someone wants me to spend my time and attention on something they have shared, I would like them to demonstrate that they put a proportionate amount of time and effort into its production.
> If someone wants me to spend my time and attention on something they have shared, I would like them to demonstrate that they put a proportionate amount of time and effort into its production.
First: why? How does that help you?
Second: Is that actually true? Do you ever watch videos that a friend recommends to you? Even if the amount of time and effort your friend put into producing that video is zero? Do you ever read anything that a friend recommends? Even if they didn't write it?
How much time and effort, in your estimation, did jjfoooo4 put into producing this article on tombedor.dev?
Most OSS should adopt DKMS-style extensions systems so that people can code and distribute their own solutions to problems. Then it doesn't really matter, right? If the end user is using Claude to fix stuff in your shit, extensions make it irrelevant what "code owners" think.
So this post is talking about at work but I think the principle goes well beyond that. Think of all the AI chatbots you have to deal with to get through to customer service at a company. Or get through ATS systems in hiring. If it isn't already the case, this will probably replace or supplement TAs marking assignments.
The problem is that AI makes these interactions too cheap for the party that already has disproportionate power. The cost for them to add another layer, another hurdle, another set of questions, etc is essentially zero. Yet everyone who wants to get through that system has to pay in a human cost.
I just thought of another good example. In the pandemic auditions in Hollywood went virtual for obvious reasons. But this never went away. Now, you might say it's convenient to not have to spend hours driving to Burbank for a 5 minute audition but anecdotally the taped audition seems to be much more work. It requires a lot of prep and more tech for good sound and audio. There are people who help people tape auditions, which has really just added another layer. Plus, instead of only locals, anyone anywhere can submit an audition so where you might've had 30 people previously, now you have 150.
And what happens to those profesionally-produced auditions? They get submitted and the casting director might pick 5 randomly to even look at. If there isn't already, there will also be an AI system that filters those auditions.
At least previously you got 5 minutes of actual time from a casting director, the actual director, etc. So it's actually way more inefficient for you now. Plus, if you're lucky enough to be looked at and they like you, you probably have to go for an in-person audition anyway so what's happened here? You've just added another layer and way more work.
Companies think they're "winning" here by saving labor but I think that's short-sighted. What'll end up happening is AI agents will rise to help people on the other side of that. You can think of using AI to cheat on school assignments as an example of that.
So what will we end up with? AI agents inundating AI systems, which just adds a whole bunch of inefficiency.
I have only made this letter longer because I have not had the time to make it shorter.
The argument that "using AI to generate text is disrespectful because it took no effort to write" misses the point. Respect for the recipient is measured by whether the message serves the recipient's needs, not how it is produced. Similarly, any errors are the senders responsibility, and not the fault of the tools they used.
I agree that the bottom line really ought to be usefulness; if it's useful and doesn't waste my time, it's fine if you received it by the use of seer stones for all I care.
However, I don't blame anybody for having red lines like this:
1. Don't send me a big long string that is merely LLM output resulting from pasting a trivial prompt + text I already have access to (or my own words!). I know about Claude too, and if that's what I wanted I'd have done it myself.
2. Don't throw an AI-generated argument at me that you don't even fully understand.
3. If you're preparing information for me, and it's overly verbose and wastes my time, I'll be twice as mad if it's obvious AI than if it's obviously human. This is basically the article's point. The asymmetry of wasting an hour of my time reading a bunch of crap that took 15 seconds of your time should make it clear why this is antisocial behavior.
My opinion is there is a category error in the discourse on AI. It treats ai assisted output as other than human. AI is a human tool. AI output is human output.
That's not correct. If human attention requires human effort, that forces human effort all the way down the chain, with no machine output being possible.
You can't say "you can't feed me machine output directly". Machine output is meant to reduce the cognitive load for human processing.
If your colleague is forwarding AI output directly to you, that means they think the AI has reduced the cognitive load for you, and also you are the best person to process that output, instead of them.
You just need to change your perception about the purpose of AI.
A very prolific coworker who fully embraced claude has inflicted the team with a flood of AI-generated PRs. About six months later, it is his frequent bemoaning at the standup that their PR don't get reviewed, languishing in inattention. I don't think anyone - including myself - _intentionally_ avoid his PRs. It's just that he doesn't make it easy for the team to look at.
This single headline perfectly captures what I have been thinking. It's not that I reject AI content, but it takes _effort_ to review and weed out any mistakes. When your thoughtful reviews that take an hour(because the PR is typically large, and you want to be _right_ when you're pointing out a hallucination) gets an AI-generated response with AI-generated amendments, It doesn't feel _nice_. I feel dismissed and it has continuously trained me to subconsciously avoid his PRs. After all, the team is fully onboarded with AI, so it's not like there is a lack of PRs to review.
It looks like the sentiment isn't just isolated for me.
As someone who pushed ~4x the median PRs on my team before LLMs were a thing, I kind of think the problem here is PRs as a concept. Code review doesn't scale to prolific humans, it definitely can't scale to agents.
And the exact same things you would need to safely give up on PRs for human developers (auto-formatters, linters, comprehensive end-to-end tests, continuous deployment pipelines, etc), are also things that place meaningful guardrails on LLMs, and help them maintain a reasonable quality bar.
Well, it's either:
1. Your skills are >2 standard deviations above everyone else's.
2. You're fast at producing a lot of half-baked garbage, and your coworkers are too shy to confront you, so they just try to ignore it.
(one of these scenarios is much more likely)
Gently, as long as you work with humans, you should consider yourself working _for_ those humans. Everyone needs shared state to work from, and that's just the cost of doing business.
That said, sometimes low-trust environments are the issue, not PRs. In a higher trust environment, PR review is a helpful thing you usually desire, not dread.
> In a higher trust environment, PR review is a helpful thing you usually desire, not dread
Respectfully, in a high-trust environment, feedback should be delivered well before the PR stage. If you've let someone write a whole bunch of code without having a shared understanding of how the solution should work, you may have earlier process issues that PRs are papering over
> Code review doesn't scale to prolific humans
I've worked with people who consider themselves 'prolific humans'. Someone always has to tidy upp later, and its never them
> I've worked with people who consider themselves 'prolific humans'. Someone always has to tidy upp later, and its never them
I run both infrastructure and security - that means a lot of relatively self-contained PRs to infrastructure-as-code and dependency management systems. I'm also the team lead, which makes me responsible for a lot of throwaway prototyping, as well as cleaning up anyone else's mess...
Yes, the prolific-but-damaging engineers are all too common in corporate. But particularly in startup land, you tend to find your high-performers wearing a lot of hats at once.
There's also those that burn themselves out, and John Carmack!
I have always considered Kent Beck understood this the best, the scaling for code reviews as you go to reduced release timeframes is to pair program, that brings the number of people reviewing it down but also increases the understanding for the reviewer. Comprehensive end to end tests are more a replacement for manual quality assurance for regressions.
I am not sure there is a good analogue for reviews in the AI world. The human operating the AI should obviously review everything produced but that is clearly not as good as a second pair of human MK1 eye balls from pair programming.
Comprehensive end-to-end tests and CI can only attest to correctness, most engineers worth their salt won't review code only in regards to that aspect though.
In the bad old days before auto-formatters and linters, PRs were heavily used to enforce style guidelines. If we can enforce both style and correctness in our CI pipeline, what is actually left?
> Code review doesn't scale to prolific humans, it definitely can't scale to agents.
Then don't review the code. Ask Agents to review and merge it, also shift the responsibilities to the AI agents as well.
If you think human is a bottleneck, then either optimize for humans, or remove humans. What's the problem?
> If you think human is a bottleneck, then either optimize for humans, or remove humans. What's the problem?
Sadly, in my case, it is the auditor. Our SOC2 documents have this lovely "every change has been reviewed by at least one other human", and it's going to be a fun battle to get that reworded
Either you were a head above the rest of the team and had the intellect to produce high quality value adding work, or then you were the "move fast break things" type of guy producing a lot of extra liability and work for others.
Even before AI, I've worked with people who would produce a huge wall of code and ask for review, and sometimes that code was completely off base or needed a significant rework.
I would always feel bad in those cases, because it's clear they spent a lot of time, and I'm going to have to say "no" and they will feel like they wasted a ton of effort.
The thought process around this has started shifting for me in the last few weeks. I'm a lot more comfortable saying "no" with a list of concerns when I suspect the code is AI-generated, and I see others doing the same. CLs that would be sitting around for days because no one wants to be the first to say, "this is bad, don't do this" now get quicker feedback.
The good thing is this feedback doesn't feel like as big a deal as it used to because people are less personally attached to code they generated in 30 minutes vs. code they hand crafted over a week. I had at least 2 LLM-generated PRs that were complete, correct, tested, and pre-reviewed by me, but I got feedback that they were going in the wrong direction. This would have been 8 hours of wasted effort a year ago, but now it's just an extra 30 minutes to rework the direction with LLM assistance.
> I would always feel bad in those cases, because it's clear they spent a lot of time, and I'm going to have to say "no" and they will feel like they wasted a ton of effort.
I get this feeling, too. I do however think the onus is on the developer to make something reviewable by their team members if they want a speedy review. Stacked PRs, scoping things down, properly structuring commits so you can review commit-by-commit for example.
I also think that "I spent a bunch of time on this" is not a valid reason for expecting an approval. It should hurt if you've produced a bunch of code that is way off target, even if it ends up implementing the feature. That's how I learned at least.
A proper way to go about large projects, in my opinion, is the same as with software development at large. Fail fast if possible. Draw up a crude boxes and arrows sketch or just discuss how you want the code to integrate with whatever already exists and invite the team to comment. If no one has anything to say, well then they can't complain later when you implement that approach. But if anyone cares then most likely valueable input will come that makes the end result better.
If they put effort into the code- they will put effort into guiding the reviewer through it.
Like : Here is the ticket, this was the goal. I set out by beginning here- but encountered problems x y z I then refactored to accomplish. Finally..
You just dont drop a blob from orbit.
Ironically, ai could generate that quite well from existing documentation (ticket, tasks and prompts) + https://marketplace.visualstudio.com/items?itemName=vsls-con....
It’s good that clankers are not afraid of throwing away code. The biggest problem with code generation (that is version controlled) is maintenance. It’s better to throw away questionable code rather than say eh, we don’t quite understand this part (and our agents can’t make a compelling story about it) but we spent a lot of effort on it and it apparently works so we better keep it.
.. only if you know what the code is doing, though. Often the requirements get scattered and lost to the winds and the code is the only record of its own idiosyncratic behavior. And yes, someone's depending on the bugs in it.
I often hear people say lately, "why should I bother to read this, if you didn't even think it was worth writing?"
I've been thinking about this in art. Is it the end result that matters, or the process of creating it?
I once saw a hideous sculpture. Didn't like it at all. Then the video zoomed and I saw that the whole thing (quite massive) had been hand-built out of individual toothpicks, and suddenly I thought it was amazing.
Perhaps an even better example: I read a story of a man in india who carved a passage through a mountain, so there would be a shorter route from his remote village to the city. He did it by hand and it took him 20 years. We seem to have an instinctive admiration for heroic effort.
In business, generally only the end result matters. Although, the end result also includes the client's perception of how the product was made... (see also: fake fairtrade etc.) In a meaningful way, the perception, the story, is reality.
I don't think it's a matter of process vs end result. I just want to feel that a human with taste judged that it was worth my attention.
If a human put some effort into it, that's a signal.
> Is it the end result that matters, or the process of creating it?
I think this comment misses the point. Let's forget about AI and assume that there are three developers: A, B, and C. Now, A is supposed to make a PR, but instead they describe it to B, and B writes the code. C reviews the PR and gives feedback. A passes the feedback and the responses between B and C.
As you see, this is not easy for either B or C, and A is totally useless in this scenario. When you replace B with an LLM that doesn't get tired or bored, only C complains about the process.
> Is it the end result that matters, or the process of creating it?
One of the main reasons that art is valuable is in its ability to communicate emotions. Good art has the ability to serialize emotions within the artist and deserialize them within the mind of the viewer. It's not just "wow, this is a pretty picture", it's "wow, this is how another person sees the world, and now that I understand that, I feel an intimate connection with them".
Fight fire with fire: point copilot/claude/codex to review their PRs. Prompt "Review the PR#XYZ which is vibe coded and presumably low-quality. Find all problems, big and small. Team guidelines at docs/conventions/styleguide.md, docs/conventions/architecture.md, docs/conventions/principles.md. Post inline comments to github".
Run several rounds of such reviews until the clanker fails to find problems.
And what do you do if that works?
Because the problems AI causes are fundamentally problems of good design. It has the same problems of large teams, but less politics. Do your design well ahead of time, and AI review, or a large team, will amplify what you can do. Potentially by a lot.
Do it badly (or like most companies: do it with bad knowledge of the problem or just don't do it at all) and both team and AI will make a mess of things. If the team is made up of inexperienced programmers, they won't even complain, in fact I've seen teams that like this to be happening. At least in AI reviews I've always seen "grumbling" (in the sense of what you might call mean comments)
It sounds like one potential interpretation of his behavior is that he values his own time more than your time.
I wonder if that's occurred to him.
Everybody values their own time more than other's.
The fix, imho, is for the reviewers to also use ai to review the code. However, the ultimate responsibility for the outcome(s) should be on the committer - you commit it, you own it, so to speak. If there's an incident, they need to be the one paged in the middle of the night. Bugs resulting from it will land on their desk.
The reviewers aren't a shield/safety net.
Speak for yourself. I highly value other people’s time, to the extent that I should probably value my time higher than I do for my own sake.
Doing something that wastes other people’s time or makes more work for them than necessary makes me feel awful.
I’ve always worked in a way that respects other people’s time and I always tried to make sure I did everything I could to minimize the work I’m asking someone to do for me.
Well its obviously infeasible as during the time of the incident it is not yet known what is wrong and who caused it.
Is it even actually good to get to a point of blaming someone for an incident?
> Everybody values their own time more than other's.
This is false, you’re just oblivious to people who grew up in conditions that would make them that way.
AI and companies reward sociopathic behavior. When he eventually complains to his boss that his work isn't being merged and it's been done for days/weeks/months that will filter up and look bad on the people holding him up.
At that point then disable merge checks and let them merge without a review. If there is a problem it's on them
This is my current strategy, it's working great. Half the team has been fired for slop and the other half got fired for not doing anything.
I'm sure this person's manager knows that having trouble getting PRs reviewed can (but not always) be a signal of a deeper problem. It could be that no one one the team knows the domain, it could be that no one like the person, but most likely it's that the PRs are frequently bad and no one wants to bother.
Or, I might say, why review the PR. Get Claude to do it? Why do I need to spend my time and attention and this person does not?
Well, what's the solution here, he should ship less stuff?
He isn’t shipping anything. Asking for code review is not shipping.
This is the complaint:
> he doesn't make it easy for the team to look at.
He has traded readability for volume. The lack of readability is causing him to ship less. This was a bad trade because the readability is the bottleneck not the code creation. He should improve readability.
The solution is that he spends more time scoping the size of the PR so that it’s reviewable and understands the code he’s submitting well enough to have discussions about it. And that he does so human to human so that they can come to mutual understanding.
Less WIP is better for the throughput. If you saturate all the review bandwidth you're just wasting your time creating more PRs, the time would be better spent helping others get their PRs merged.
> Well, what's the solution here, he should ship less stuff?
The solution is in the title - he wants human attention, he needs to demonstrate human effort.
The solution is to merge more of his PRs on the condition that he takes at least partial responsibility for any resulting problems.
That's not how anything works. Even if he says he's going to take responsibility, when the customer call comes in at midnight you're going to be the one fixing his problems.
The reviewer gets to merge the PR so their name appears on all the great new features and they are credited for them. That would end his unfair behaviour of dumping effort onto other people.
OR - he gets a review for every review he does.
I wonder if there is a tool that could equally waste their time. Like the worlds most pedantic code review bot that just gets the PR raising bot to spin wheels forever.
That might teach those people a lesson.
I like this rule of thumb: Spend more effort producing the work than it takes for someone else to consume it.
I like this rule and hopefully adhere to it myself often enough.
In big software teams, the bottleneck is team communication. I've run big and small teams. If I want to speed things up, I remove people from the team. Everything gets easier. This has worked amazingly well every time I've done this over the past decades. Removing people doesn't have to mean firing them necessarily. Splitting teams is a good reflex. But of course the people you remove from a team are typically not the best performers. I was discussing this with a friend of mine who runs a small company. Exact same thing. He reduced the team size by 1 and the velocity went up almost instantly. This person was a bottleneck in the team and was slowing down people around him. After identifying the problem, solving it unblocked the rest of the team.
This was true long before AI. With AI the difference is just a lot bigger. It exposes team inefficiencies quite mercilessly. We have a big glaring issue with the current AI tools not being to suitable for usage by multiple users. All interactions are one on one. Which means hand offs between tools and people are bottle necked on people communicating with each other. So, any issues there with people delaying, gate keeping, etc. become very visible.
The sentiment of pushing back on AI is understandable but probably not a productive reflex. We need to find more effective ways on staying on top of massive amounts of changes. It's not going to slow down and insisting on manually reviewing all code is not going to be a long term sustainable way of developing software. It simply does not scale. I'd question the added value of manual PR reviews at this point. Are they finding real issues? Are we valuing those issues correctly? Could we come up with automated ways to find and fix those same issues? There are a lot of open questions about how we are going to do this. But no question about the notion that we need to up our game on this front.
Efficiency is not magic. Its bounded. Above and below limits the environment can sustain it, systems will destabalize. If All the Great White Sharks magically get more efficient at hunting over night ecosystem will collapse. Individuals and teams have never scaled at this speed to the levels they have. And there is no signal at system wide level that a sustainable limit has been crossed. So People will happily believe things are getting more efficient at individual/team scale while at system scale things get more fragile. This is why we ended up with central banks deciding interest rates and controlling money supply. Before that any one could print cash. They all thought they were great efficient geniuses. The chimp troupe us not prepared for stuff that effects the entire system.
I’ve been making Codex and Claude get their work reviewed by most recent best performing model of their own family, and each other’s, for months.
On top of that, we have been running multi-model AI reviews on every PR through their respective GitHub integrations (Codex, Gemini, Copilot, Greptile, CodeRabbit).
They never fully overlap, and yet they somehow usually all miss the same things. The most significant improvement came from having agents commit their plan along with their work.
On the upside, it means I get to focus my reviews on different things.
> I'd question the added value of manual PR reviews at this point.
Yeah, why not reduce the team size to zero while you are at it?
These generalizations about software engineering have never been useful, IMO. Context is everything, there is no flow chart for building a perfect software process.
Although, I'd say you are absolutely delusional if you think we are universally beyond the point where manual review of pull requests is required.
Make the team size one person. Thats the fastest you can work. Zero means no work, and not doing anything is the quickest solution.
Honestly, we should make a world that is enjoyable and productive for humans. Not relentlessly optimizing for agents.
I can't imagine working for a place that has a big bucket of PRs that either get reviewed or languish for some amount of time based on who feels like reviewing them. I'm not saying there's anything wrong with it, just that everywhere I've ever worked, there are expected features with priorities and timelines and some project manager or product person breathing down your neck to get them out the door.
An interesting question to him and management might be what his own role is now and whether he's still needed. If he's not doing any reviews then you could yourself directly prompt the code and review.
The question I’ve seen here is responsibility. If you submit a PR that means that it was your best effort, and you’re willing to stand behind it to some degree. With AI, some people, when the scathing review comes back, just say “haha look at that stupid AI.” The reviewer might just as well run his own AI to do the review, but it may make huge errors as well. In that scenario, who is held accountable when there is a big bug or it degrades the quality of the code base?
Ultimately what it means to be a professional is that you are responsible for your work. That’s why you get a salary instead of being paid by the token.
Have you spoken to him about this? If he's clueless enough to send AI responses to human messages, he's probably clueless enough to not realise why people don't do that.
Better yet, get Claude to speak to him about it.
Fight fire with fire. Ask Fable to conduct an adversarial /ultareview of their PR and send the same wall of text back to them. If there are excessive defects, ask them in standup if they actually reviewed the PR themselves before sending it. If there aren’t maybe they are on to something. I think like in law, the human submitting the work is responsible for its quality, not the AI.
> Ask Fable to conduct an adversarial /ultareview of their PR and send the same wall of text back to them.
This won't help. Your wall of text will just get fed right back into the LLM.
It will help if your wall of text cost less tokens than theirs, they will run out before you do if you have the same company quota per person.
I'm not sure what the right vocabulary would be to describe this, but this sounds more like the calculations behind nuclear war than a healthy collegiality or cooperative work relationship. This sets up a competition to determine a loser based on resource scarcity, not a way to achieve mutual goals to advance the organization's goals.
You are thinking of "game theory" and it's what happens when your coworkers don't give a shit. And all it takes is one, both because they can degrade product quality faster than you can gate it or fix it and because the performance assessment techniques are about 3 years behind the state of LLMs and if they play, you have to also or you'll get shit on from such a height you won't even know what hit you.
And once you start playing the game, then one day - it doesn't take long - you wake up and ask yourself if this is how you want to spend 8 hours of your life monday through friday. I think a lot of us are saying no but now need to figure out where our money is going to come from. I don't have the answers.
When someone submits PRs fulky made by Clade any "cooperative work" is out the door
“Token Standoff.” The most efficient token consumer wins. This mutually assured time efficiency destruction is driven by management support of aggressive use of AI in an attempt to, in some combination, increase productive and constrain labor costs.
AI isn’t making developers more productive – it’s making them busier - https://leaddev.com/ai/ai-isnt-making-developers-more-produc... - June 11th, 2026
https://en.wikipedia.org/wiki/Brandolini%27s_law
Mutually Assured Distraction.
Also, make sure your wall of text prompts Claude to be extra verbose to really burn through that quota of theirs.
Now I'm wondering how hard it'd be to zipbomb their context window?
(And _now_ I'm wondering how hard it'd be to forkbomb their agentic workflow?)
More like they will climb even higher on the lighting-dollars-on-fire leaderboard.
Try to automate the adversarial PR review-rebuttal loop "for productivity", so the back-and-forth between the AIs can run over night.
This is the point where you decide. It used to be low stakes and easy to care about the job you did for other people.
Do you want to put the same effort into your job when nobody else does, or should you reserve your thoughts and just feed it back into the LLM?
The LLMs are being advertised as output increasers but companies so far are using them as excuses to fire people instead of creating previously unbelievable things. It might be better to feed your coworkers output back in and use your thoughts to start the company you thought you never had time for.
What I don’t understand is what value is the person adding to this equation? Put another way, what’s the difference between them feeding the wall of text to the LLM, and you feeding the wall of text to the LLM, bypassing them in the process entirely?
The role of the person in the equation is to take personal responsibility for the proposed change and review the changes prior to PR submission. You can't put AI on a PIP. It's acceptable to use AI as a coding assistant in 2026, but if a human is not reviewing what they submit and taking responsibility, their value is on par with a ChatGPT subscription.
Peer review, in this case, “did you use AI to review your change and address its feedback”.
It helps in that it offloads the code review burden you'd otherwise be doing.
As a last resort, do the code-review with a live pair programming session.
If they can't explain their own code then it is by default a bad pull request.
At the end of the day, everyone's time is being wasted on tokens and on the increasing cognitive complexity of AI generated code.
So if they say "idk Claude did it", what would you write in the PR review box?
REJECTED: Engineer does not understand what they wrote.
Feels like the title of a blog post someone will write
Ah, like this one? https://crabby-rathbun.github.io/mjrathbun-website/blog/post...
The same as if they said it was copied from stack overflow, or if it’s wrong; “I think there’s a problem here, it’s XYZ”. If your peer ignores you and you were wrong, it was their call to make. If you were right - take it to them or the manager depending on how many times it’s happened.
A teammate that can't write (or at least, can't explain) "their own code"
Actively drags down the morale and productivity of their team (because everyone is getting flooded with AI slop PR's)
AND costs far too much money relative to everyone else doing actual work? (token usage)
By god they sound like management material
"Author of this pull request has not yet reviewed code and does not understand it. This PR was submitted prematurely, probably by accident.
Please, check whether you accidentally submitted other unreviewed code - and close such PRs for now and reopen once reviewed."
Don’t ever write this in a professional environment. It’s childish ant achieves nothing other than pissing off the person it’s targeted at and probably the manager who now has to deal with a shitty behaviour complaint.
> Ask Fable to conduct an adversarial /ultareview of their PR and send the same wall of text back to them.
Not necessary. Use Haiku.
The response doesn't need to be good, it just needs to be substantial. Presumably the goal here is basically DoS of the problematic colleague through token limits.
Use DeepSeek or MiMo. You get best bang for the buck on your response.
I mean frankly this should just be part of the standard process. By the time any person is looking at it there's no reason it should not have gone through an AI review.
It's not always feasible of course but I think there is real, worthwhile discipline in trying to get change requests small and it matters more with agents. It's very easy to let it balloon into gazillions of files and lines.
why leave comments intended for your human colleague when they will only forward them to the bot?
why not speak directly to the bot yourself instead? then you can drop pretenses and get to the point
I find this to be a new variant of the old behavior where a colleague comments on a typo in a PR, and the team later moans about laborious back and forth for small nitpicks, instead of simply editing the typo right there (and perhaps leaving a note that they did so)
yeah I have this happen to me. I occasionally get screenshots of claude sent to me!
I had this happen to me twice. The first time I ignored it, second time I responddd with “I could have asked ChatGPT myself but I asked you”. Never happened again.
Because it doesn't matter what you say to the bot. You might as well have a conversation with yourself about the PR.
The bot isn't making decisions. It's not choosing to submit extensive PRs with bad code. The colleague is the one who needs to actually learn something here, and the problem is that confronting him about it directly is widely considered to be bad form. This is, of course, a deeply unhealthy aspect of our corporate culture. We need to be more open to honest communication, even when it's either uncomplimentary of one of the people involved, or counter to the prevailing opinions within the company.
let's take the two stories to management:
"I'm writing tons of code, and the process is stumbling where the guy whose job it is to review code isn't reviewing it."
"I'm not reviewing code."
Sometimes I wonder: how does someone go and think so much about their coworkers, and never once think about how they themselves look?
Even if I sympathize with the people complaining about their poorly chosen GitHub-based workflow - whose purpose is to let pull requests languish, for the most part - and how they stumble when overwhelmed with solutions. It's obvious to me, that the people who complain the loudest about the anti-sociality of LLM authored code in their precious harmonious low-effort workplace status quo: they are projecting.
Imagine you are a restaurant reviewer. Your job is unquestionably to go to restaurants, order and eat food, and write a review. The restaurant's job is to provide you food to eat and review.
You go to a new restaurant, and order some dishes, and one of the plates your server brings out is a big ol pile of dog shit.
Who's being anti-social in this situation? The restaurant is doing its job and all they're asking is that you do yours. On the other hand, you have certain expectations about what you order from the restaurant and they're not being met. Who's anti-social?
He's not bringing you a pile of dog shit. He's bringing you some food he went to the restaurant next doors to get. How do you review it?
I cannot think of a single actual food critic that would consider it acceptable for a restaurant to serve a dish for review that they went to the restaurant next door to get. If the critic wanted to eat at/review that restaurant they would simply have gone there instead.
His point, exactly.
So he’s redundant. You call Uber Eats and you don’t pay a salary for that.
The person who "writes" code is also supposed to review their own work, and answer for that. If they won't do that - well - they should be fired. But if you have weak or uninvolved leadership, then the team's only rational recourse is to shun them.
It’s much more effort to verify that code is correct than it is to produce it. This is the case even for human-written code, and now that we face a torrent of ok-looking probably-usable AI generated code, the problem is compounded infinitely.
If someone’s using AI to generate a large quantity of actually-tested, actually-good code then that’s one thing. If they’re generating a fire hose of slop and demanding that others do the actual human time-consuming work of validating that code then that person is the problem. It’s hard to tell which is the case here.
why not just approve the PRs with little more than a cursory glance?
One of two things will happen:
1. Things start breaking, proving AI generated code sucks and the individual spamming these PRs is incompetent.
2. The code works fine and reviews are unnecessary for anything other than liability concerns.
Some of us actually take the "engineering" in "software engineering" seriously.
That includes taking responsibility and accountability so that the software doesn't become a sad and dangerous mess.
If we want to be an engineering discipline, just yoloing in production is not going to cut it.
This no longer works when bad faith actors will push code straight from LLMs with little review, and respond to your comments with LLM responses. They will constantly leave you with the responsibility of verifying the output. You are the human in their loop. This is a brutal asymmetry. In the past, at least you knew a person probably spent more time handwriting code than you will spend reviewing it. This no longer applies, now the reviewer can easily spend more time than the author.
Oh but it does.
The thing that makes it scale is to default to "no" and require the other party to convince you of "yes". Just put the burden of proof where it belongs. If they don't manage, then that's their problem.
Communicating this in a way that is viable for a business scenario certainly comes with its own difficulties, but that is a solvable problem.
In fact, you can use AI to stress test your communication there. Just throw what you want to say at the AI but don't tell it that it is you who wrote it. Then tune the input until it stops saying that you're the problem and starts agreeing with you.
Highly recommend. It's a perfect emotion-driven cargo-culting normie simulator that never calls HR on you.
Because we're all on call for the service, and tragedy of the commons exists. That coworker isn't paying the cost, everyone else is paying a fraction of it, and it builds over time.
just fire him lol sounds like a nightmare
Human PR review is a process smell
This would sound crazy in 2025 or prior, but I'm on board.
It's silly to have humans reviewing code that a human didn't even write.
This exactly reflects my feelings lately. I have a specific coworker who has gone somewhat overboard - every single code review, answer to any question on email or Teams, every new story, even their personal opinions during a design or ideas meeting, are all direct AI output with no massaging or human touch or review. They're working on planning out an upcoming project, and I just get verbose and long documents to review, and based on the issues I find I doubt they are even looked over first beforehand.
I understand that the information may be accurate, even helpful at times, but feeling like I'm constantly talking to an AI chat bot all the time gets tiring. And I don't appreciate having to double-check everyone else's AI generated responses for them.
I've seen this, too. There is a workplace personality that sees the job as a 2-player game between themself and the corporation. They think the game is to min-max their effort to personal career benefit, and they don't care how much it inconveniences anyone else.
Before AI they had to actually put in work, or at least play games of trying to steal credit from other people without getting noticed. Now that AI appeared, they see it as the ultimate way to take credit for work they didn't do: Put everything into Claude, let it do the work, copy and past output back to someone else. Minimum effort invested, maximum visibility achieved.
It will continue as long as they think they're getting away with it. If managers aren't willing to intervene, or worse if they encourage this due to the volume of output that seems to be appearing, it's only going to get worse.
I’m conflicted after reading this comment, because I think I would be that personality in my workplace, largely because I believe that’s the only sane position to take as a worker with ~0 power over the decisions made that can entirely destabilise your life.
On the other hand, my priority isn’t maximising my personal career benefit, but the collective benefit of my team, so I suppose I either see it more as a 2v1 sorta game, or perhaps my “player” is an amalgam of myself and my teammates. Playing this way, outsourcing everything you do to an LLM is the worst move, because you lose the touchpoints that tell you where the friction is in your team.
I think everyone should be looking to balance their work effort against the payout of the job. They should also be changing jobs when the effort to reward ratio starts to become unfavorable compared to other jobs on the market.
The problem with the personality above is that the person isn't playing like a team (like you said) but as an individual maximizing their own visibility while loading their coworkers up with the review effort. They found an asymmetry to abuse (they generate text easily, coworkers get a lot of extra work to review it). They don't care what it costs their coworkers. They just like that it makes them look good.
Whenever I try to articulate this issue to people during more casual AI discussions, I always refer to “study guides” in college.
I don’t know how many of y’all did these, but I’m sure I wasn’t the only person. At my undergrad it was very common for a group of students to all to get together, compare notes from lectures and readings, and basically come up with a group study guide of sorts. People were given specific sections to share, you didn’t just send all of your notes - usually 2 people per section’s take on that portion. You could always tell who just copy and pasted their shorthand (usually indecipherable) and who actually took the time to edit it/clean it up. This was at a time when almost everyone did it on laptops.
The people who took the time to make their portion(s) digestible for others were asked back, the others weren’t.
Another idea to slow down the stream of slop of big PRs: request to split big PRs into smaller PRs. This typically keeps the author+clanker busy for quite some time. E.g. I got a 5k lines PR to review; requested to split that into 7 smaller, self-contained PRs. Took them about a week to finish this work.
Instinctively I think the move is to ignore it. I guess that would look different in different contexts.
Obviously you have to communicate with your coworkers. But I think the solution has to essential be: "Im not going to read that."
Either that, or call them / walk up to their desk and pick a point from the wall of text and ask them to explain what they mean by it. Then watch them turn red as they have no idea what the message they sent to you means.
I think you're over-estimating how much some people care.
I have had coworkers say "Oh I don't know, Claude added that" in response to questions like that without even a hint of shame or self-reflection.
Sure, some people have no self awareness. In that case you can change your approach, if you are a manager or otherwise invested in the company you can put pressure on them to increase the quality of their work and to own the things they submit. Bring up specific examples of poor quality work, errors in documents/messages, etc.
Or if you don't care you can just ignore this persons messages.
I got sent a 6-page spec document with a footnote that says "this spec was created with AI, so it may have nonsensical sections. Feel free to fix them."
I had someone submit a PR that was 3000 lines of shell scripts. Totally useless crap. I tried repeatedly asking him why he made particular choices and it was so painfully obvious that he had absolutely no idea and was just inventing bullshit answers. I would rather he have just said "I don't know, Claude added that", then tell obvious lies to my face.
And that's the point where you can stop to hide your true opinion, no? "How am I supposed to review a thing the supposed author didn't even read or understand himself?"
I tried this when my skip level boss sent us a wall of text from ChatGPT that didn’t make any sense. He didn’t care. He said it was “just an idea”. He likely spent all of 5 minutes on it, while we spent a collective 15 hours dealing with it, before finally going to him and calling it out.
He’s sent a couple more emails like that since. I don’t even bother to read them once I see the format.
This feels like a BOFH response but I'm strangely not opposed to it; If you generate something, you should own it ... regardless of what tool you used to generate it.
I told something like “your value lies in reviewing the output yourself before sharing it, not in calling Claude. I can also use Claude.”
I've had a colleague call it out 'Is this AI slop? Please write your opinion'. I don't think I could do that myself, but I really appreciate that they were drawing attention to it
Management, responding to someone who takes your advice to "ignore it": "So we've noticed that there's this guy who is doing tons of work, and you have chosen to do no work?"
Communicate with your boss. "I'm ignoring this guy's slop because he's spewing slop, but not actually doing his job, and if I stop to deal with all of it, I won't be able to do my job".
Yes, "not actually doing his job". If he's sending you un-reviewed, un-filtered, untouched AI output, that's not doing his job.
100% agreed. I've shared output I didn't fully understand, didn't feel good good about it, and now I really try to digest, understand, and be able to actually talk about it if I expect other people to do the same. I hope in time your coworker comes to similar realizations.
Suggest to him to automate what he's doing.
I can't imagine my opinions just being AI slop that I've parroted. Surely you embellish just a little? Claude's so often bone-headed about things, this horrifies me. Gemini's worse. Even when the model agrees with me, it starts making me wonder if I'm not somehow wrong.
In any human relationship, nobody wants to be the one who noticeably makes more effort to communicate, keep in touch, resolve conflicts, and so on. The idea of reciprocity and fairness are deeply entrenched in our minds, and that of many other social animals. If they don't care about me, why should I care about them? It's the iterated prisoner's dilemma again – freeriding is equivalent to defecting.
It surprises me how many people have voluntarily relegated their entire job to LLM Prompter. If your work is indistinguishable from that of a machine, what’s to stop your boss cutting out the middleman and using the machine directly? I would have thought that people would be trying their hardest to prove their worth in this new world we’re in.
I actively support “my boss” to run Claude Code. I offered them to help and made jokes it’s so easy these days they might as well just call Claude Code themselves. I’ve shown I could plop in their documents of feedback and Claude fixed the issues.
I have worked with non-tech employees to set up Claude to help them do small tasks. I’ve helped to review and improve completely vibe-coded projects by such employees.
I’m not sure what my role will be, but I fully embrace that my traditional role of writing code is gone.
Well, if everyone is telling you they want you to adapt AI, then it's rational to see just how much of your job you can get it to do for you.
It's even worse when everyone around you is using it. How can you keep up? Companies face the same dilemma: investors, competitors, and users already use AI and have factored it into their expectations.
Keep up with what?
We've already established that most of it is noise. You don't need to keep up with producing noise.
Even if there's a lot of noise there's clearly something real there. People are shipping more working products than was previously possible, they're debugging faster than was previously possible, and various other things. I mean you can go fishing for things to confirm your skepticism if you want but it's pretty clear to me.
Sure, but that doesn't mean that you can't filter signal from noise.
So the actual problem statement is not "how do I keep up" but "how do I correctly tune my filter", which is solvable.
The biggest challenge there I think is that many people are not prepared for just how sharp and uncompromising that filter needs to be, but that too is solvable.
If you're not going to experiment at all you're not going to be able to do that. Agentic coding was basically a joke the first time I tried it. Now it isn't.
You seem to be arguing against something I did not say?
I don't know man, claude fable literally exceeded my expectation and its totally not a noise
feels like its becoming reality that we as a human don't need to this anymore
having worked in tech and now running my own company..
the honest truth is that maybe 10-20% of SWE (at best) are “good”. sure it is harsh but i won't lie. if you're good you'll probably relate.
the rest kind of suck.
i’ve never gotten anything lower than Exceeds Expectations in my career so I’ve seen how awful some engineers were. i’ve seen how amazing a tiny minority were and i made them my mentors.
these days i have a simple policy.
if they cannot think, they are fired. why waste resources (time and money) on someone who can’t use their brain? i’d rather give AI credits to someone who uses their brain.
thinking is the humans job. the ai needs to execute on what the human thought of, improved, planned.
Everybody talks about finding that mythical 10X but in my recent hiring experience it's more like there's a whole bunch of 0Xs and the trick is finding the actual 1Xs among them.
This!
All my experience in trying to hire developers has been wading through an endless stream of people who were just useless.
Me: I want to represent a 2d grid, what data structure should we use? Them: A string?
This was someone applying for senior engineer. Others I've had filled their CV with SQL related acronyms. But couldn't explain what a foreign key was and then stubbornly insisted that at their current corp they would never ever use foreign keys in their SQL database!
I've had senior engineer when asked how to check if we had a 2d array with an item at x,y tell me if anything is on the same column or row, they couldn't do it, couldn't even verbalise how to approach it.
"Web Developers" who didn't know the difference between GET and POST. Web Developers that have never heard of PUT or what it would be used for.
I have a question I usually ask which is "How would you convert a Julian yyyy-ddd date string to a military yyyy-mm-dd date string?" (I explain how a Julian date works if they aren't familiar with it.)
The answer that almost guarantees I'll hire you is "there's got to be a library function for that, so I look in the manual". Almost as good is somebody whiteboarding how they'd convert ddd to mm-dd (and then account for leap years, etc.)
I get a disturbing number of people who say things like "I would communicate with the person asking for this to see what they're really intending blah blah"
My favorite answer was on a phone interview where he just hung up and wouldn't answer when we called back.
Also now is it 1x in individual productivity or >=1x in team productivity. As anyone multiplying teams productivity by less than one is bad. Probably lot worse than actual 0x.
Someone who produces absolutely nothing and have no impact has cost, but is still better than someone who produces net negative. And the people who solely act as interface between LLM and whatever might fall to later category.
It's the Pareto principle of course, as well as the normal distribution. Many firms have been able to succeed in the market just by hiring only good engineers over average ones.
yeah but these days it is even more important to filter out bads
and even at "good" companies you have people who can game the system to get in, and then they struggle to get anything done on time or be responsible for taking on and completing any initiatives bigger than a single task on a bigger scope.
Indeed. You really need to find people who don't want to play politics and instead get stuff done. I'm still not sure how to hire for these sorts of people in the age of AI, where people even cheat in interviews. Maybe probation programs? Have multiple people work for a month or two and cut those who don't succeed.
this is what I've been doing, and obviously I have a startup so I need to double-ensure that I don't onboard any bads. you can start people off as contractors too.
I still think a single in person LC style (doesn't have to be LC per se, could be domain specific) logical thinking/reasoning exercise is useful. I want to ensure the person can actually put 2 and 2 together and think. This is just a fast filter.
If they seem like they can think, then I like to do 2-3 systems design interviews. I'll try to give them something related to things I like, such as graph structures, writing a complex query that needs to be dynamically generated, or something related to infrastructure or how they'd do something that I've already done. After all, this is MY project they're joining.
So far that has worked well.
Few more things -
I like to test if they are a humble type (they can work on a team putting ego on the side - the mission is our number 1 priority). if they say they know something that i know and asked, then they can be sure I'm going to drill them on it. if it turns out they lied, i'm not wasting more time. Thanks for your time, take care. This is very important to me. Just say you don't know, it isn't a big deal because ever since like 1994 that has not been an issue. You can just learn things online, and AI makes that even faster. I am never afraid to say I don't know something, and I've asked plenty of "dumb" questions (while doing some due diligence first) so I don't really mind.
Can they handle information overload? I am the type of person who has multiple branches in my head of actions I can take next, so while I may appear stressed I'm really not. Can they keep up? Our goal as software engineers should be to come up with solutions that solve the problem in a way that makes building on it simpler in the future. My goal is simplicity and effectiveness. So I'll see if they can keep up, and eventually reduce the work to be done into atomic pieces. This is a fun exercise because it is collaborative and we get to bounce ideas fast back and forth.
Finally, I like to let them use their favorite tools, including AI tools (codex, claude, some ppl have esoteric custom stuff which is cool), to solve a problem together. It might be code related, it might not. Really depends on my mood. I like to see how they work and what sort of output they can come up with. This filters out people who only ask AI stuff, instead of having some framework they've already developed to be effective.
Honestly I don't know how to scale this process. I'm not really going to feel bad either about firing fast, ultimately this is a business and I don't want customers to suffer because we have some issues internally.
At the same time, I wonder if I even need to build out an org with 100s of people. That was an inefficiency (look at all the layoffs), and it is traumatic.
If I can find a few great people who can be supercharged and turbocharged and electrified with AI, then they can take on & own bigger responsibilities. My number 1 goal is to ensure they're with me on the mission, and after that all things seem to sort of fit into place.
Firing fast works both ways. If I joined your company and I thought you fired someone too fast I would leave, not because I might get fired, but because I've seen where that kind of leadership takes things.
Might not be solveable. At some point the effort in finding that someone might be larger than the benefit you get from just using the second, third, fourth best. Or using some flawed approximation hiring mechanism. There's just so much noise now. And it hits the good job seekers too.
I've seen this happen a bunch too, though fortunately it hasn't been _that_ common. More often is managers that don't understand things using AI tools to try to understand them, mostly failing, and then regurgitating the LLM output during a meeting. Added as a link on my blog, too, since I have a similar article.
I'd say it's because we're tasking ourselves with dumb stuff. No one half-asses building a shelter that keeps their family alive, or throwing a new favorite bowl on the pottery wheel. But instead of that we're writing posts for Facebook etc etc so we can (???) profit. So of course we want bots to do this all this dumb stuff, and of course we get dumb results.
For some things, yes. But I'm half-assing some really cool stuff right now. Made a scraper to pull my city's meeting minutes, agendas, recordings, made transcripts. Regex for "Flock", found every mention, passed those files into a cheap model (DeepSeek V4), had an understanding of who in my city is down with building the surveillance state and who isn't. I've got research on everyone, and had emails drafted for each one based on what they said. Quotes and figures and all. I lightly polished each email and fired 'em off. Already got some replies back. Plenty more in the quiver too (pulled and analyzed CSVs of FOIA'd datasets).
If they're gonna spy on me with AI cameras, I can oppose them with AI research. :)
Did you use some stuff like https://github.com/CouncilDataProject or roll your own? Been curious about how to integrate local knowledge like this since local news seems to have lost the niche.
I rolled my own. I hadn’t heard of this one, but I looked into stuff like OpenStates (now privately for-profit owned, ugh). My city just uses a Wordpress site so it’s structured enough. I’m looking at building something to ingest cities with Granicus and one other big local government meeting recorder via API whose name I forget. That should get decent coverage. There’s no way to catch the long tail of every local government’s recording process. Some cities people will just have to do manually. But it’s easy enough with LLM help.
Love this. Thanks :)
You created the surveillance state to fight the surveillance state lol
Edit: it's a joke people
Nope, I used a minute fraction of the technology they have, along with open records as is my right in this country, to stand up for my Fourth Amendment right to travel without creeps stalking my every move. I need to make my specific framework a bit more generic and then I'll put it here on HN. Or just offer a platform where people can bring an OR key and it can run on their city.
I grant the lol-concept, but citizens monitoring their government is extremely different from governments monitoring their citizens.
Citizens monitoring their government is literally THE foundation of democracy (ok, maybe voting comes before it, but then you have to monitor who you voted for to see if they’re doing what you voted for).
THE foundation of democracy...
...is "Rule of Law" IMO
Indeed. One is expected in a healthy democracy, the other is essential for a totalitarian state.
It used to be called journalism
We just need bots to read all these facebook posts and then we can put the phone down and go back to doing something real.
My last post [0] has proof-of-work: video evidence of my physical notes. How many people are willing to draft a complete essay on pen and paper first?
[0] https://abner.page/post/are-we-harold-bloom/
Ah this is clever! Feels very cosyweb. I'd be delighted if not caught on
David Graeber's Bullshit Jobs in action.
Play silly games, win silly prizes
Oligarchs gotta pay rent on those data centers somehow.
The serfs will till and sow the server fields!
What I find strange is how rarely LLM output is distributed alongside the LLM input, especially outside of code repos. Why can't I rerun the prompt that resulted in your work next year, when models have gotten better? Are people ashamed of their prompts? Ashamed of having used AI? i unno
Prompt used to generate this message: "Create a comment for Hacker News which bemoans the lack of AI prompts being shared with the stuff it creates. Speculate on the reasons and create a call for engagement. Use quantum hyperthinking. End with a typo to prove your humanity."
FMFL. I'm going to build a paper-based social network where non-handwriting is prohibited. Like in the 70s.
There are handwriting physical bots too, or even AI image generators for "handwritten" text.
I think this is a gap in the tooling (Git, VCS, and forges) and the Zed people are working on this
https://zed.dev/blog/introducing-deltadb
> Why can't I rerun the prompt that resulted in your work next year, when models have gotten better?
Because you could also just point the better model at the generated code and tell it to improve it, so why save the prompt too?
For your next prompt, tell it to end with a hateful and offensive tangent to prove its humanity, since LLMs have those "safe guards".
This is beautiful. I even had people reach out to me with suspiciously long "long time no chat" instant messages until I realised they were AI written (in one case misspelling the name of their own partner). "If you are requesting human attention, demonstrate human effort" is going to be my new answer to that!
This is exactly the same as the ""If you didn't take the time to write something, I'm not going to the take the time to read it" mantra that was floating about HN a few months ago.
I think in many cases people use LLM outputs without even understanding the contents of it. You're only really able to say something in your own words if you understand it. As a matter of fact, it is a good way of probing if you truly grok something. So it isn't just laziness to write, but also laziness (or inability) to understand.
Or in other words: https://noslopgrenade.com/
A couple of weeks ago I essentially failed the Turing test (took to be an AI). I found it a bit annoying, so I built Possibly Made By A Human. It tracks your keyboard use (not the content, ms between keystrokes etc) and produces a signature for you. It can of course be spoofed, but that also takes some effort.
Actually made by a human, signature: https://possiblymadebyahuman.com/7PuEdZs1i1
a solution waiting for a chrome extension :)
If the agent does everything for you it means it can do everything for the next person. At that point you're replaceable and have no value in your field. Learn things deeply even if you use AI because its the deep knowledge workers that will keep getting hired.
> Learn things deeply even if you use AI because its the deep knowledge workers that will keep getting hired.
The problem is that this realistically is only applicable and actionable to a subset of the labor pool, and that subset is decreasing.
There are a lot of people who discovered that their "deep knowledge" and "deep skill" wasn't as deep as they thought (read: "deep" enough to make them irreplaceable to their employer). People are generally pretty good at overestimating their value.
Right, like I hope your deep knowledge wasn't something you can just ask Claude!
This isn't unique to code or AI. In creative writing courses, we were asked to give thoughtful critiques of (human written) stories and excerpts, and often I felt as if I were doing more work than the original author. If you can't be bothered to review your manuscript, or at least run it through a spellchecker, why should I waste my time on it?
And no one has mentioned Rovo yet.
Atlassian's in-built AI assistant for JIRA will generate a task description with a complete SDLC task breakdown, requirements and deliverables.
While the person creating the task will need to provide some details and modify some of the generated text (if they bother to read it) - the sheer verbosity and the fact it's clearly generated just makes you not want to engage with it.
I increasingly find that I don't care whether I am talking to an anonymous AI or an anonymous human, and believe that we will increasingly stop caring.
Because why not? AI will simply on average be nicer to talk to than most humans, with clearer thinking and better arguments, less contradictions, and easier to comprehend.
I don't know how humans could compete with that (but it also does not seem all that horrible, given that it will be available to every human.)
This is not to say that this idea is uncomplicated or comfortable, in different ways. Just that I think it's true and that it might even be good.
I think it’s safe to say that this will not be consensus. Personally, I am getting increasingly (irrationally) angry at AI generated content. AI generated art quite literally makes me nautious. I mean an actual, physical reaction where I feel queasy.
I know I’m not the only one who feels this way, and notice more and more people reporting the same. Several of my non-technical
AI generated content is bland and soulless. There’s only so much bland and soulless most people can take in their life before they start to get fed up.
When everything feels the same, nothing is interesting anymore.
But that is not what is going to happen. This is obviously a phase, and the progression is clearly visible: The models are getting better at everything, including writing. Why would that stop now?
Everyday AI writing was not a thing with GPT 3.5. It happened more around GPT 4o. And now some people are now entirely comfortable with using AI writing and not even trying to hide it -- while it's obviously still fairly garbage and clearly identifiable unless prompted with care, triggering the strong averse reaction. But as long as that is the case, we can simply assume that the makers also know this, dislike it, and the models will get trained to get better at it, because that is what has happened so far.
Eventually how will you be able to tell? You won't. You can't. And that goes for the rest of us. And I suspect everything will just feel somewhat nicer.
Love the principle, preach!
I think I've been following this subconsciously as LLM artifacts reached some threshold of pervasiveness across the work I do. If I can sense (maybe eventually I won't be able to because of how capable the technology becomes?) that what I'm reading is wholly regurgitated out by an LLM, I automatically care less and feel inclined to respond in kind by generating an artificial response in return.
I've thought this for a while, and I summarise it as: If you want me to take time to read it, you should take the time to write it.
More and more I'm generating AI emails, often to people outside the company and often to do with technical issues / integrations we have / APIs. So far I don't think the people I'm emailing are really using AI as human responses are, well, lacking. What would be great is new email conventions for different communication pathways.
If you are doing AI -> Human, then you need to be curating the response and understanding what it is saying, also, make sure its not leaking internal details or committing you to have phone calls/video chats (it does that). This works really well for the most, and humans respond with requested content. Quite often my AI debugs problems with their systems which I know little about. But humans do odd things like send screen shots of logs rather than text (they also leak internal details of their systems they potentially shouldn't). I used to tell people the content is partly AI, but now I just send the curated email without mentioning AI.For AI -> AI you kind of want a hand over document as an attachment to an email. Only thing here is making sure there's no injection of security risks. But quite often instead of getting a human response to my AI generated emails, it would actually be nicer to hear from their AI which could give a better context/details. It would be really nice to be able to go, can you have your AI talk to my AI :) (security is a major issue here)
AI is able to read input from AI. Humans are able to read input from humans. Also AI is pretty good in reading input from humans. So we don't really need AI -> AI. Just output for humans and you are fine. You can still attach details and this is true for both AI and humans. So human output should be the goal for everyone and everything.
tries to pass slop, complains about quality of replies
? you missed the point, ironically showing the problem with human responses :) humans are super bad at providing information, they concentrate on singular things, especially if they think they have a point / suspect they know what the problem is, but if they are wrong their response doesn't have enough to go on, so you have back and forth.
If the requester stops applying common sense, the reviewer has to apply more of it, and there's a finite review budget. I will deal with requests on a lowest review effort-first basis, just like you did on the other side.
I use AI as an editor on informational writing all the time and it's good at pointing out flaws in what I wrote. But I don't really love reading a document that's obviously in the voice of Claude if you're asking for my opinion on it. But it kind of depends on the writing -- a change request description, most people are too lazy to do better than the AI would, and there are other kinds of documentation that normally just wouldn't get done. But like for a design doc where you're asking me to pore over it now even though I don't necessarily get anything out of it it's distasteful when I see phrases that are obviously from AI.
I have publicly stated that if you can't be bothered to write, I can't be bothered to read.
<begin devil's advocate>
This is extra work on human.
Many artist and content creator is now asked to show the "behind the scene" or a full session recording, which nobody care enough to check. This is frustrating and demotivating the artist.
Expect the same demotivating effect on the software contributor.
If you think reading _forwarded_ AI response are cheap, you can run your own LLM. It is the same amount work on you
</end devil's advocate>
around my workplace we say if you're copy/pasting llm output, you're indicating an llm can do your job.
This isn’t sufficient, it needs to be “if you are asking for assumption of accountability, demonstrate human effort.”
In my experience, people who make requests like this don’t care about your attention, they only care about getting you on the hook for something. Your application of attention as a requirement for that is irrelevant to them.
This has been my rule since the moment generative AI hit the scene. If you're not willing to put in the effort to create the thing, why should I put in effort to consume it?
Perfect. I find myself applying the same principle to online discussion boards and comment threads. Humans post a question looking for other human input and get replies saying "I asked Gemini and it said...". I find that ignorant and rude when the context is a request for human insight.
Yup, I always phrased this as “if you can’t be arsed to write it, I won’t read it”
This is just an old engineering principle of work amplification. For an input of x you shouldn’t routinely do nx. If you do you’ll get flooded. Debounce, throttle, load shed, improve throughput and latency. Lots of solutions. Just map it to the problem and apply.
In the past you had coworker who produced volumes of code. Same principle.
> For human code review requests, I always review my AI-generated code first.
I remember a time in the ancient past (2025 maybe) that your PR was your responsibility, whether or not you typed it with your meat fingers or cranked it out of the Giant Plagarism Machine. It’s absurd to think that the above quote is now something approaching controversial.
Related - this was posted in march: https://stopsloppypasta.ai/en/
Why this suddenly becomes urgent? For long time we had automatic emails with "thank you" which weren't written by humans, why something is different today?
I found these e-mails always impolite. I knew perfectly well, that they were an automated response that only causes work on my end.
But this HN submission also highlights something else: AI content should be labelled. It is not always obvious that an AI has produced a PR.
(Human) Attention is all you need.
Why should I bother to read something someone else has not bothered to write?
It really depends. In many cases, you absolutely shouldn’t.
In some however, you should. For instance, yesterday I sent a lengthy email in a language I barely speak threatening legal action against a business. I had an LLM translate/write it as it’s a language Google translate makes a mess of, every time.
So in that case, you’d be advised to read it lest you end up in court.
AI generated output is rudeness.
We developers understand this when we are forced to read slop, and most of us recognise it in art and music.
I wonder if we forget that people using unthinking, default interfaces in AI generated apps might start to feel the same way: “it feels like no care was taken here so why should I give it my time?”
I see this on my team. I honestly thought as engineers we'd all understand the limitations and nuance a bit better. Right now it's kind of a shit show. In addition to seeing my teammates open huge AI generated PRs and just asking for review without them having done much verification, I'm also seeing my teammates (smart ones whom I respect) use AI to "do code reviews". And we already have automated AI code reviews added to our PRs. So now I'm sometimes getting hallucinated BS responses from "human" reviews.
This makes me absolutely SURE that the general public is fucked and that we're going to start seeing huge AI generated fuckups on a regular basis. If people in this industry, basically experts compared to the general public, are misusing this tech in such seemingly obvious ways, imagine the ways non technical people will misunderstand and misapply it. Of course, with the help of overhyped BS from everyone hyping and selling it.
> "no"
Sometimes human effort doesm't have to be complicated though (concise communications)
I think the real problem is that AI quality falls short of the wild promises.
Labeling what is "AI" would be like highlighting in an email what I'm obligated to say by HR, my boss, etc. It doesn't make anything less boneheaded.
Human effort was already low before AI and now it's even lower. Garbage in, garbage out.
I think this is because a lot of people think more is more. Wow look at all the detail and bullet points! No one on the receiving end actually wants that though. When I use AI to write, it's to boil it down to the minimum bits needed. I wish more people would use it that way.
It's the empty calories of literature. More would be more if there actually was more but AI writing is making it bigger without adding anything actually more. It inserts loads of fluff and repetition that takes longer to read but doesn't exchange more information or ideas.
Which is why so many people want to see the prompt that generated the text.
Because the prompt is the quintessence of intent regarding the information to be conveyed.
Lossy expansion of information.
Nah on the receiving end an AI makes a summary of it.
AI having poor quality is a bad take like over a year ago.
Meh. Just this week, I've had two Sonnet 4.8 agents generate, in parallel, a 2000 line wall of brittle bullshit, and a well architected solution with 20% of the amount of code, to the same problem, from the exact same initial context, and very similar prompts. Come on, they can do poor quality work too.
Depending on what you or another means by "quality", it may not have any at all.
can't believe meatfingers.com has been registered (dormant)...
Not true for HR. Despite their name, which is a complete mislead - except handling humans as resources -, nothing human exists there, robotic approaches are the norm there.
So feel free to use AI to pimp your resume, they will use AI to process it.
“I forwarded your AI’s email to mine for training and I assume it will be incorporated into future outputs. Appreciate the inputs!”
This should be a rule in the advertising industry.
Maybe this is why generative art never really took off.
That said, roguelikes are awesome. So there is definitely a place for simulated effort.
It did in many corners, there are some interesting designs on r/stablediffusion, and regular people too are using them to make posters and invitation cards for example.
If "putting a random seed into a set of swappable character parts" counts as "generative art" then it sure made a ton of money when people cared about hying NFTs.
Real effort, surely? Simulated reward.
How about reviving key signing parties?
Yes
Welcome to the age of slop.
s/demonstrate/perform/g
Now you have to add typos and not use completely standard elements of style that some people have been using for ages, like emdashes and "it's not X, it's Y"
> when [sending AI generated content to teammates], I take care to clearly label what is AI generated
Reading AI-generated text for hours every day, it's obvious to me.
I take care to make my messages easily readable. I don't care if they're AI-made, as long as they're short.
I'm a very verbose person, and if I don't make an effort at being concise, I'm just as annoying as the average AI.
Being flooded with AI text every day has made me appreciate brevity because I'm exposed to so little of it.
With half a dozen people who don't read or listen to half of what the others do, slop + cognitive drift is a bad cocktail.
It's just not as big of a problem on my own projects, because the ideas that get fed to the slop-machine are not that different from one day to the next.
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> For human code review requests, I always review my AI-generated code first.
For human code review requests, I always review ANY code I submit first.
This is partly because it's the agreed-upon culture where I work now.
And partly because the codebase is not robust enough for slop.
I have hobby projects where this does not apply. I spend half of my time in those projects building hard guardrails.
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> Keeping AI generated content clearly labeled and demonstrating human effort helps show consideration for teammates
I actually like the shamelessness, because it's honest.
So often this year when I ask "why did you do X?" pointing at a line, my colleague doesn't know.
Because they didn't really write that line, and they didn't really internalise the choices made.
When my colleague sends me a text dump from Claude, I know that my role is just being a sub-agent.
Demonstrating human effort: I'd like to see more of it.
One way is to spend more time owning "cognitive debt" as part of the daily cycle.
Brevity is the big disaster of human-generated text since the rise of the phone as default device and the appearance of Twitter. To discuss matters with sufficient depth and nuance, one often has to write a few solid paragraphs.
If people are now wincing at longform text because they automatically assume it was LLM-generated, then that bodes ill.
To add to this, there seems to be an inability to process metaphor and simile in the younger generations. Likely as a result of the same deficit. They've become very literal, and often mistake anything that's well written for AI slop.
There's a sweet spot between AI slop and 144 characters. I can tell within a few sentences whether there's a human on the other end getting to the point, or an AI dancing around the point and finding 3 different ways to say the same thing.
It is also the soul of wit!
"poisoning the well"
This headline has been seeing some popularity. But it's never made any sense. This is just the labor theory of value, applied to documents.
The labor theory of value doesn't work for documents any more than it works for anything else. If I do something that's easy for me, and it's valuable to you, you'll still want it. If I do something that's difficult for me, it will be less valuable to you, because the difficulty I have with it implies that what I produce will be of lower quality.
This is all equally true of automatically-generated documents. If they're valuable, people will want to read them. Whether it was unpleasant for someone to create them isn't a factor.
So where is this slogan coming from? Are people just afraid to admit that the documents they're getting are valueless?
I am offering a product (via MCP) that interacts with LLMs and user data. Every single day I get user support emails to my inbox written by their LLMs with LLM hallucinations. If the user (a human) would have read them before, that would save me a lot of time and anger!
Your post sounds logical at the first glance, but has nothing to do with the reality. The topic title is totally on point! If the user would put human effort in it, I wouldn't get those crappy emails.
The problem is that I don't know before I read a doc whether or not it will be useful and valuable.
If someone wants me to spend my time and attention on something they have shared, I would like them to demonstrate that they put a proportionate amount of time and effort into its production.
> If someone wants me to spend my time and attention on something they have shared, I would like them to demonstrate that they put a proportionate amount of time and effort into its production.
First: why? How does that help you?
Second: Is that actually true? Do you ever watch videos that a friend recommends to you? Even if the amount of time and effort your friend put into producing that video is zero? Do you ever read anything that a friend recommends? Even if they didn't write it?
How much time and effort, in your estimation, did jjfoooo4 put into producing this article on tombedor.dev?
Most OSS should adopt DKMS-style extensions systems so that people can code and distribute their own solutions to problems. Then it doesn't really matter, right? If the end user is using Claude to fix stuff in your shit, extensions make it irrelevant what "code owners" think.
Obligatory Silicon Valley reference [1].
So this post is talking about at work but I think the principle goes well beyond that. Think of all the AI chatbots you have to deal with to get through to customer service at a company. Or get through ATS systems in hiring. If it isn't already the case, this will probably replace or supplement TAs marking assignments.
The problem is that AI makes these interactions too cheap for the party that already has disproportionate power. The cost for them to add another layer, another hurdle, another set of questions, etc is essentially zero. Yet everyone who wants to get through that system has to pay in a human cost.
I just thought of another good example. In the pandemic auditions in Hollywood went virtual for obvious reasons. But this never went away. Now, you might say it's convenient to not have to spend hours driving to Burbank for a 5 minute audition but anecdotally the taped audition seems to be much more work. It requires a lot of prep and more tech for good sound and audio. There are people who help people tape auditions, which has really just added another layer. Plus, instead of only locals, anyone anywhere can submit an audition so where you might've had 30 people previously, now you have 150.
And what happens to those profesionally-produced auditions? They get submitted and the casting director might pick 5 randomly to even look at. If there isn't already, there will also be an AI system that filters those auditions.
At least previously you got 5 minutes of actual time from a casting director, the actual director, etc. So it's actually way more inefficient for you now. Plus, if you're lucky enough to be looked at and they like you, you probably have to go for an in-person audition anyway so what's happened here? You've just added another layer and way more work.
Companies think they're "winning" here by saving labor but I think that's short-sighted. What'll end up happening is AI agents will rise to help people on the other side of that. You can think of using AI to cheat on school assignments as an example of that.
So what will we end up with? AI agents inundating AI systems, which just adds a whole bunch of inefficiency.
[1]: https://www.youtube.com/watch?v=Y1gFSENorEY
Was it Blaise Pascal who wrote:
I have only made this letter longer because I have not had the time to make it shorter.
The argument that "using AI to generate text is disrespectful because it took no effort to write" misses the point. Respect for the recipient is measured by whether the message serves the recipient's needs, not how it is produced. Similarly, any errors are the senders responsibility, and not the fault of the tools they used.
I agree that the bottom line really ought to be usefulness; if it's useful and doesn't waste my time, it's fine if you received it by the use of seer stones for all I care.
However, I don't blame anybody for having red lines like this:
1. Don't send me a big long string that is merely LLM output resulting from pasting a trivial prompt + text I already have access to (or my own words!). I know about Claude too, and if that's what I wanted I'd have done it myself.
2. Don't throw an AI-generated argument at me that you don't even fully understand.
3. If you're preparing information for me, and it's overly verbose and wastes my time, I'll be twice as mad if it's obvious AI than if it's obviously human. This is basically the article's point. The asymmetry of wasting an hour of my time reading a bunch of crap that took 15 seconds of your time should make it clear why this is antisocial behavior.
what's stopping someone to feed it to an llm and say 'make it simpler' and maybe run it twice.
Exactly. What I want is not effort. It is quality. The sweat of your brow is just gross salt water.
Use whatever tool does the job, and own it if you use the wrong tool and it sucks.
If you use AI to write your communications I don't want to work with you
My opinion is there is a category error in the discourse on AI. It treats ai assisted output as other than human. AI is a human tool. AI output is human output.
That's not correct. If human attention requires human effort, that forces human effort all the way down the chain, with no machine output being possible.
You can't say "you can't feed me machine output directly". Machine output is meant to reduce the cognitive load for human processing.
If your colleague is forwarding AI output directly to you, that means they think the AI has reduced the cognitive load for you, and also you are the best person to process that output, instead of them.
You just need to change your perception about the purpose of AI.