Amazon’s ecommerce business has summoned a large group of engineers to a meeting on Tuesday for a “deep dive” into a spate of outages, including incidents tied to the use of AI coding tools.
The online retail giant said there had been a “trend of incidents” in recent months, characterized by a “high blast radius” and “Gen-AI assisted changes” among other factors, according to a briefing note for the meeting seen by the FT.
Under “contributing factors” the note included “novel GenAI usage for which best practices and safeguards are not yet fully established.”
“Huge rich company responsible for hosting like half of the fucking internet spent the last year pushing code to global-scale production without so much as a review by a senior engineer.”
That’s how I read that headline.
I read it as “now a senior developer will be at fault for all AI code.” Do you think they will have time to review all that code properly and do their jobs.
One of my first big jobs at NASA was as a lead engineer on a multi-experiment platform to fly on the space shuttle. I checked all the work and compiled all the data and trotted my 27 year old self down to Johnson to present my case to the Safety Board. When I stood up to present, the head of the panel asked if I knew why I was there. I confidently told him that I was there to walk them through my evaluation of each of the payload components and show that the payload was safe to fly. He smiled. He then said “You’re here because if something goes wrong on this mission, there had to be one ass to kick. Proceed.”
Everyone needs an ass to kick, and AI doesn’t offer that function.
That sounds like an almost refreshing “you’re one of us now / welcome to the real thing” type of brutal honesty.
Did it have a friendly tone and/or serve as an ice breaker before your presentation?
The preview for the reply notification for this comment started getting my brain so excited when my eyes scanned over the beginning. Screen grab:
They will save time by making them go pee in bottles
How in the glorious fuck was this not a thing from the start? In a system this big and this critical all code should be reviewed by cognizant individuals. Anyone who thought an LLM would be perfect and not need code reviews has their heads so far up their asses they can see through their pee hole.
If you do this, you signal the AI isn’t ready for production capabilities, which limits your sales groups capability to market it. Which is in reality the actual case and AI sucks and should never be trusted.
What is AI good at? Creating thousands of lines of code that look plausibly correct in seconds.
What are humans bad at? Reviewing changes containing thousands of lines of plausibly correct code.
This is a great way to force senior devs to take the blame for things. But, if they actually want to avoid outages rather than just assign blame to them, they’ll need to submit small, efficient changes that the submitter understands and can explain clearly. Wouldn’t it be simpler just to say “No AI”?
If you ask a writer what is Ai good for? They will say it’s good for art. But never use it for writing, because it’s terrible at it.
If you ask a artist what is Ai good for? They will say it’s good for writing. but never use it for art, because it’s terrible at it.
Conclusion… it’s good at neither… or am I missing your point?
The output looks good to people who are poorly versed in the segment for which AI is being asked to perform, but often inefficient or fails in ways that an expert in the field would never miss.
—ignore this part, I’m just rambling from here on Depending on the context, you’ll almost certainly get something that looks correct on first glance, especially if you’re not an expert. If you’re an expert, you wouldn’t need to ask for such a task and, if you did to save time, you’d probably end up adjusting, correcting, or fixing several things to produce a production-ready output. I use it regularly for code because the last language I had any training in proper syntax was Fortran 77. And eventually the simple tasks I ask it to code for me work. I’ve asked it to do some excel calculations (I’m not an excel expert, I do a lot of mathematic manipulation in custom sheets) and some of them work, but most are either wildly convoluted or relay on obscure calls/functions rather than simply using standard logic and mathematic operations which are easy to edit and change. I’ve also asked it to do some graphical illustration (because I’m not a graphic artist) and it has produced nice looking illustrations with zero basis in reality - i.e. “draw me an outline of Scotland in the style you’d see on a tourist map and label, with a star, these four cities”. It produced what I would expect an average American would estimate the outline of Scotland looked like and was equally as accurate with the location of the four cities (i.e. utterly incorrect).
AI’s greatest feature in the eyes of the Epstein class is the ability to shift responsibility. People will do all kinds of fucked up shit if they can shift the blame to someone else, and AI is the perfect bag holder.
Just ask the school of little girls in Iran which were likely targets picked by AI with out of date information about it being a barracks. Why bother confirming the target with current intel from the ground when no one’s going to take the blame anyway?
Or I suppose add extra work by walking an AI tool through making small incremental changes.
In my experience, LLMs suck at making smart, small changes. To know how to do that they need to “understand” the entire codebase, and that’s expensive.
Yeah that’s what I mean by extra work. I can make the change myself or I can argue with claude code until it does what I want.
deleted by creator
Hahaha IT’S ALL ON YOU NOW. HAVE FUN!
- Fuckin no one who should ever not be beat to death with a printed stack of emails
Yes, so now when there’s a success, it gets attributed to AI. When there’s an outage, that’s the fault of humans not reviewing correctly. These senior engineers will get fucked in all scenarios.
Precisely. From Cory Doctorow’s latest, very insightful essay on AI, where he talks about the promise of AI replacing 9 out of 10 radiologists:
“if the AI misses a tumor, this will be the human radiologist’s fault, because they are the ‘human in the loop.’ It’s their signature on the diagnosis.”
This is a reverse centaur, and it’s a specific kind of reverse-centaur: it’s what Dan Davies calls an “accountability sink.” The radiologist’s job isn’t really to oversee the AI’s work, it’s to take the blame for the AI’s mistakes.
I don’t think it’s fair to compare LLM code generation to machine vision in this way. These are very different "AI"s. Not necessarily disagreeing with Doctorow, but this is an important distinction.
How the machines work does not matter. The situation is using a machine to replace human expertise while ensuring a human still takes responsibility for things that human is not responsible for. It is not the owning class who is at risk for their machines mistakes, it is the owning classes wage slaves who are at risk.
My understanding is that the tumor detecting machine vision is generally thought useful in addition to the radiologist’s expertise. It basically outputs “yes”, “maybe”, and “no”, which is more expertise respecting than generating somewhere thereabouts code, which the coder has to (now) validate.
This is why I wouldn’t equate these tools. LLM code generation is marketed to do much more than machine vision for tumor detection.
Cory Doctorow actually goes more in depth on the radiologist example in a post from last year:
'If my Kaiser hospital bought some AI radiology tools and told its radiologists: “Hey folks, here’s the deal. Today, you’re processing about 100 x-rays per day. From now on, we’re going to get an instantaneous second opinion from the AI, and if the AI thinks you’ve missed a tumor, we want you to go back and have another look, even if that means you’re only processing 98 x-rays per day. That’s fine, we just care about finding all those tumors.”
If that’s what they said, I’d be delighted. But no one is investing hundreds of billions in AI companies because they think AI will make radiology more expensive, not even if that also makes radiology more accurate. The market’s bet on AI is that an AI salesman will visit the CEO of Kaiser and make this pitch: "Look, you fire 9/10s of your radiologists, saving $20m/year, you give us $10m/year, and you net $10m/year, and the remaining radiologists’ job will be to oversee the diagnoses the AI makes at superhuman speed, and somehow remain vigilant as they do so, despite the fact that the AI is usually right, except when it’s catastrophically wrong.
“And if the AI misses a tumor, this will be the human radiologist’s fault, because they are the ‘human in the loop.’ It’s their signature on the diagnosis.”
This is a reverse centaur, and it’s a specific kind of reverse-centaur: it’s what Dan Davies calls an “accountability sink.” The radiologist’s job isn’t really to oversee the AI’s work, it’s to take the blame for the AI’s mistakes.’
In short, we definitely could (and indeed should) be using tools like tumor detecting machine vision as something that helps humans build a better world for humans. But we’ve seen time and time again, across countless fields that it never works out that way.
That’s because this isn’t a problem with the technology of AI, but the fucked up sociotechnical and economic systems that govern how this tech is used, who gets to use it, who it gets used on, whose consent is required for those uses and most significant of all: who gets to profit?
!Not us, that’s for sure!<
The kind of AI doesn’t matter with this situation. Hell, It could be a magic talking rock™ and it change nothing of Mismanagement using a person to avoid blaming their shiny and expensive new toy.
“this is an important distinction”
it really isn’t
If my job ends up being reviewing AI code spammed at me by vibe coding juniors all day, I’m joining a nunnery.
If nunneries are as gay as I always imagined in my head, I’m in.
or hear me out, they can build it themselves so they don’t have to chase hallucinations. as a matter of fact, let’s cut the ai out of the project and leave it to summarizing emails.
This 1000x. You think that senior dev got to that level hoping one day all they’d have to do is evaluate randomly generated code? No! They want to create, build, design, integrate, share. Cut out the middle, useless step and get back to the work these professionals have dedicated their careers to.
AI is an assistant, not a replacement. It amazes me that Amazon, Microsoft, Google, and all these “tech leader” companies are going to make the same tech fuckup multiple times.
If only the lessons were painful for them and not just us/the workers.
Wonder what the turnover rate in executives is. I bet it is about 8 years.
Couldn’t they, I don’t know, just go back to people writing the code, and stop using AI to do something it clearly can’t handle? Just an idea.
I guess they’ve invested (thrown) so much money at this thing, they’re determined to make it work. Also, I know they’ve gone into insanely deep debt and if it doesn’t work they’re going to lose an eye watering amount of money, and perhaps the bubble bursting will be the catalyst to bringing down the entire world economy.
Oh, so yeah, they do have great incentive to make this work, but I don’t see it happening. As usual, they fuck up and the rest of us pay the bill. None of the billionaires will suffer any more than loss of face over this. Even if they’ve broken laws, all they ever get is a small fine and a slap on the back, “Better luck, next time, ol’ boy!”
Morged.
I always saw a code review like a dissertation defense. Why did you choose to implement the requirement in this way? Answers like ‘I found a post on Stackoverflow’ or ‘the AI told me to’ would only move the question back one step; why did you choose to accept this answer?
I was a very unpopular reviewer.Likely, but you did not let poor code pass. That is valuable.
Junior and mid-level engineers will now require more senior engineers to sign off any AI-assisted changes, Treadwell added.
So instead of getting a human to write it and AI peer reviewing it you want the most expensive per hour developers to look at stuff a human didn’t write and the other engineers can’t explain? Yeah, this is where the efficiency gains disappear.
I read stuff from one of my Jr’s all the time and most of it is made with AI. I don’t understand most of it and neither does the Dev. He keeps saying how much he’s learned from AI but peer programming with him is the pits. I try to say stuff like, “Oops! Looks like we forgot the packages.” And then 10 secs of silence later, “So you can go to line 24 and type…”
Just to add to this:
- When a senior dev reviews code from a more junior dev and gives feedback the more junior person (generally) learns from it.
- When a senior dev reviews code from an AI, the AI does not learn from it.
So beyond the first order effects you pointed out - the using of more time from more experience and hence expensive people - there is a second order effect due of loss of improvement in the making of code which is both persistent and cumulative with time: every review and feedback of the code from a junior dev reduces forever the future need for that, whilst every review and feedback of the code from an AI has no impact at all in need for it in the future.
Given enough time, the total time wasted in reviews and feedback for code from junior devs is limited - because they eventually learn enough not to do such mistakes - but the total time wasted in reviews and feedback for code from an AI is unlimited - because it will never improve.
Seniors reviewing code is fine but only when, as someone else mentioned, the code writer is learning from the review. The AI doesn’t learn at all and the Jr Dev probably learns very little because they didn’t understand the original code. Reviewing AI code often turns into me rewriting most of it.
Exactly.
The best way to learn is to have done the work yourself with all the mistakes that come from not knowing certain things, having wrong expectations or forgetting to account for certain situations, and then get feedback on your mistakes, especially if those giving the feedback know enough to understand the reasons behind the mistakes of the other person.
Another good way to learn is by looking through good quality work from somebody else, though it’s much less effective.
I suspect that getting feedback on work of “somebody” else (the AI) which isn’t even especially good, yields very little learning.
So linking back to my previous post, even though the AI process wastes a lot of time from a more senior person, not only will the AI (which did most of the implementation) not learn at all, but the junior dev that’s supposed to oversee and correct the AI will learn very little thus will improve very little. Meanwhile with the process that did not involve an AI, the same senior dev time expenditure will have taught the junior dev a lot more and since that’s the person doing most of the work yielded a lot more improvement next time around, reducing future expenditure of senior dev time.
Lol I would be your Jr, except instead of 10 seconds of silence it would be 10 seconds of me frantically clacking on the keyboard “add a block to this for these packages with proper syntax, I forgot to include it” to claude. Then I’d of course be all discombobulated and shit so I wouldn’t even bother to open code, I’d just ctrl-c about 100 lines somewhere around the general area of where I think the new code block should go, then ctrl-v the whole thing into the chat box because why not the company is paying out the dick for these tokens so might as well use them.
And two weeks later half our website crashes which results in you having to go to a meeting where management tells you to keep a closer eye on me. Which is basically what you had been already doing before AI but now you get to babysit me and claude!
I read stuff from one of my Jr’s all the time and most of it is made with AI. I don’t understand most of it and neither does the Dev. He keeps saying how much he’s learned from AI but peer programming with him is the pits. I try to say stuff like, “Oops! Looks like we forgot the packages.” And then 10 secs of silence later, “So you can go to line 24 and type…”
So what kind of code is that? Code lyoko? Are they using more advanced code than their training should make one think?
It’s usually fine code but it just doesn’t follow the same conventions and flow. It’s kind of like reading a novel typed in block letters written in 3rd person then suddenly it’s cursive letters and 1st person.
It’ll be temporary, a gut reaction to add more experienced engineers in the loop. These folks will try to codify and then push better checks/guardrails into CI/CD and tooling to save themselves time. Given how new this all is, it’s almost the blind leading the blind though.
Amazon might also have some poor system boundaries, leading to non-critical systems/code impacting critical systems. Or they just let junior devs with their AI tools run wild on critical components without adequate guardrails… also likely. :-P
as a sr, I would just keep rejecting them and make AI find “reasons” why.
