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At work we have put a full halt on feature work because the number of security related tasks has become staggering and urgent.

We will hopefully get over this wave and be able to move forward with much more secure software, but it's crazy right now.

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We’ve also been blowing a lot of retainer hours just patching sites instead of building new features. It sucks. Ultimately going to cost clients more.
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Probably not, if you factor in the cost of security exploits. A single compromise can potentially sink the business.
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It's not like no work is happening though. Your clients are getting a more secure website. Maybe the bugs that are being patched would have taken longer to be exploited in the pre-LLM world but the bugs were still there.
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Most clients will not agree to pay extra for a more secure web site though. Unfortunately. Unless they’ve been bitten in the past, which most businesses still haven’t.
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Yeah you’re right but for most businesses increased security doesn’t lead to more sales.

I’m not saying that’s right, I’m saying that’s how a lot of businesses think.

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Same here. I got access to Mythos two months ago, it confronted me with decades of nasty bugs I wrote. This has been stressing me out a lot, caused sleep deprivation (the bugs follow me in my sleep, yes, really). All other progress is halted, I've been squashing bugs day and night. I see a light at the end of the tunnel.

Bottom line: it's a good thing. My software will be better after that. Even if it's currently not good for my ego (and my health). But I'm glad for all the tools that help me improve quality.

And sure, I can just ask LLMs to fix the bugs, which works well half of the time, and produces bad slop in the other half. This is where human expertise and judgement is still necessary to avoid letting our code bases drift into LLM spaghetti hell.

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My question is, did it provide POCs? I have had some security issues flagged that I tried my best to exploit, but failed miserably. Since I do not have any kind of privileged access the LLMs I use have been unwilling to actually prove that it can be exploited.

While I did fix most of the things because while they might not have been exploitable they were bugs waiting to happen, in all but one case I haven't been very impressed by any of the LARGE IMPORTANT SECURITY HOLES that were found.

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No, the Mythos reports do not come with POCs. It's a lot of redundant prose explaining the bug it found (much more than I'm willing to read), it explains how it can be triggered, but doesn't generate actual exploit code.

But that doesn't matter for me. It shows me real bugs and less than 1% false positives. Some bugs are truly nasty and urgent, most are trivial and not exploitable at all, but they're bugs and so I'm fixing them.

Mythos isn't mythically superb for being the best LLM model, but only for not having these annoying guard rails that make all others randomly refuse to cooperate when you need them the most. Whoever invented guard rails - please stop! - they just slow the good guys down in the race.

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> Even if it's currently not good for my ego

If you don't mind answering, how come? Is it specifically that you dislike how abusable your code was, or something else?

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> I've been squashing bugs day and night

> This has been stressing me out

> the bugs follow me in my sleep

Sounds like you need some vacation.

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How did you get product management to agree to that? Ours said "I could fix all of that in 2 days with Claude." They are still not fixed. Granted, our PMs suck.
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The upper management and security team came knocking and told us all of the CVEs from the scanner need to be addressed right now. And the only way to deploy without having to wait for QA approval is to not merge feature changes.
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> The upper management and security team came knocking

i would say the recent slew of vuln reports/breaches making the news rounds are doing work!

This is the silver lining i suppose!

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You need a better product management. If they can't see what's going on at the moment, they truly suck at their job or management is putting pressure.
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It’s amazing how much slop humans have produced that now needs to be fixed by AI…
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Without all that slop how would you have trained the AI?

What makes you think that AI trained on slop is suddenly going to produce quality code?

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I think ai is more rigorous with testing. It’s not so much about what an llm “knows”, but more about how well it does plan-do-check-act.
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AI is as good as the prompt. It's a simple as that. If you don't foresee everything and anything that can go wrong AI isn't not going to magically fill in the blanks and save you. So in projects that already had good test discipline, well written specs and tickets and very clear expectations, coding guidelines and documentation it is relatively easy to fit an AI in for guided work. You still need to check up but chances are good that it will usually work as expected.

But any kind of mistake, any kind of ambiguity and you'll be in for a wild ride. It usually takes a while for the rot to set in. I've had to revert - more than once - to many commits prior to undo a bunch of work that had me completely puzzled as to what the reason that particular fork was taken to begin with. Usually I end up figuring it out but definitely not always. In some cases this kind of wild modification fed back on itself until the situation was beyond rescue. I'm a bit quicker with such reverts now than in the past, for the first year or so I would try to save what could be saved, now I just restore and try again.

But if you're not sharp when evaluating what gets done there is a good chance that you'll miss it and then it can pop up way later.

What I've noticed as correlation (but I'm not sure if that is the root cause) is that non-local effects and stack effects are particularly hard as is everything that requires a working model of the world.

edit: this comment seems to make people uncomfortable.

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I think the environment you set up for the agents is just as important as the prompt. I've been working full time on a claude code developed project for the last 10 months, and it seems to become better and better at developing the right thing. It has the tools to research whatever context it needs, test it's output in a relevant way, etc. It doesn't by itself suggest complete refactoring, or big performance optimizations, so that's something you have to prompt for, but it will collect all the evidence and context to make a proposal, implement it, and test it.
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I disagree that the prompt is the most important thing, I'd say other things like the model you use, a clean codebase, actually reading code and using discretion about which changes are accepted are far more important if you're using AI for work that needs to be correct. LLMs still make significant mistakes in design especially.

Harness, prompt etc etc are all peripheral IMO, though people like to think their super long prompt, custom harness and MakeNoMistakes.md skills are what contributes to their special skill with AIs, but really models are just improving.

You can just trust the AI to generate a perfect answer I suppose (and why are humans slowing it down at all if so?), but if you don't expect that yet you have to put in the work.

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Every single case of AI slop code I've encountered in a shipped product is a result of a complete lack of proper, professional workflow on the part of the human who decided to ship it. People are using AI as a reason to continue to justify their lack of responsibility for what it is they're doing.

And on the other side, I have seen AI produce exceptionally efficient, productive and effective code - the opposite of slop - when it is treated like a junior developer who will do any idiot thing, except when it is mentored by an actually experienced, professional developer.

The source of slop in AI code is not AI, its not the training data - its in the actual workflow of the human involved in its production.

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Yes, that I can agree with.

If you just turn it loose on a codebase and ship it when it passes the tests you're asking for getting burned.

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Interesting that this could result in net negative software productivity world wide in terms of features right now.

LLMs finding unpatched vulnerabilities faster than they can be reasonably patched, bringing all other software development to a halt.

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That's only if you consider security to be unproductive!

If you consider it to be productive work, it's a massive productivity boon happening right now. Of course, product managers might disagree...

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Security work is not productive.

Imagine that the whole city has to install iron doors and window grilles, because wooden doors and glass windows are not safe enough anymore.

That's a lot of work, but is it productive in the end? Probably not.

With AI it's the same. World was fine with lax security approach before. Today it is not fine. Tomorrow we might need to prove every code line before shipping, will that be more productive? Hell, no.

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> Imagine that the whole city has to install iron doors and window grilles, because wooden doors and glass windows are not safe enough anymore.

> That's a lot of work, but is it productive in the end? Probably not.

Your imaginary scenario defines the solution to be pointless. If that same city was subjected to weekly riots smashing windows & doors, and people regularly died, stopping "productive" work to install things that keep people alive and productive? That's productive.

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It's a terminology issue. Economists use the term productivity in a certain way and they even use the term "broken window fallacy" to describe this debate.

https://en.wikipedia.org/wiki/Parable_of_the_broken_window

Basically, if you accept this line of reasoning, then someone going around breaking windows and someone else going around repairing them can be seen as good because it creates jobs. But that would be nonsensical and create poverty. That's why economists focus on wealth creation not job creation.

Fixing security bugs is only needed because people exploit them. It creates work but it doesn't create wealth.

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Fallacy applies only to incidental breaking of glass like child smashing window paying football.

Protecting yourself from bad actors also doesn't create wealth but it protects wealth you already have.

You know cybercrime and APT groups are not bored kids in their parents basement, there are groups that are running automated tooling to find vulnerable companies and if possible take all their wealth.

Just look at Binance of course, but if you are small company there are also people targeting those especially with AI assistance nowadays.

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> to illustrate why destruction, and the money spent to recover from destruction, is not actually a net benefit to society

it is distinct from question whether it is productive to defend from evil people

evil people + protecting from them is obviously net negative!

but it is not changing that of evil people are present then reasonable level of protection from them is needed, and setting it up is productive

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There is a sense in which productive is being used here that is slightly subtle. Security doesn't really add anything to net output. It is, in other words, a cost. That doesn't mean it isn't valuable.

One way to think about it is that production allows you to pay for stuff. Not necessarily directly but by way of trading. It is the output you use to buy things like security.

Consider an apple farm. What does the apple farm produce to pay its bills? Apples. They could also dedicate resources to pears, &c, and that would add to their production -- to the goods they produce, the goods with which they (indirectly) purchase tractors, fence posts, &c. They could also dedicate resources to security -- more fences, &c -- and this may even be prudent. Maybe thieves are getting taller. This doesn't really add to production, though; at best, it maintains production at the status quo ante (assuming the fence is effective).

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Just like securing a system is a trade-off, attacking one is too. Risk vs reward and time vs reward. Your personal blog doesn't need to be fort Knox, just patch it properly and you should be fine.

The software is better in the end but not all of it will be productive.

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  If that same city was subjected to weekly riots
Okay. What's causing the riots?

  That's productive.
No that's spinning your wheels because an outside agitator is trying to make a quick buck.
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> If that same city was subjected to weekly riots smashing windows & doors, and people regularly died..

The point it, this was not happening before. LLMs made cheap cyber attack possible. But it didn't make the implementation of fixes correspondingly cheap. So now everyone needs to spend extra money/effort to install grills to cover where LLMs fall short.

For postgres, this absolutely makes sense though as long as people are willing to shell out the profits from LLM use to support postgres development. That is one way this could workout for everyone..

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This why we pay cybersecurity folks, developers and business people are often living in a fantasy land where people don’t steal bikes because it is illegal to do so.

Then they have a pikachu face when someone smashes their car window to steal something worth $50 they left on front seat because “who would do that?”.

What is even better thief will most likely pawn this for $10 but for him it is effortless $10.

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And now imagine the introduction of iron has led to crowbars that make smashing doors a lot easier. Now it is quite unreasonable to account the reduction in smashing doors to iron, when the previous improvement was also due to iron.
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The physical world comparison is interesting. In the real world we have a small amount of security, but most things could be broken in to. Instead of fortifying everything, we just imprison the people breaking stuff.

Obviously this doesn't work on the internet since most hacking comes from overseas out of our control. Which makes me wonder if there is a possible future where we just block packets coming from countries that don't lock up the hackers.

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> Obviously this doesn't work on the internet

Not obvious to me. I am generally a fan of Cyberspace manifesto and the free Internet, I think it's great people can reach outside their ingroup and talk to strangers and ostensible enemies.

But, that doesn't mean we should give up physical security, the guarantee that the connecting party comes from a certain physical location (state, company). I think allowing connections from anywhere by default is fundamentally flawed security architecture, for certain things.

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I don’t think North Korean hackers are attacking things from their North Korean IPs. They just buy a residential proxy. How would you prevent that?
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I think the physical world comparisons should keep in mind the kind of data a lot of these systems (eg postgres) handle. It's more like securing a bank vault than locking a home's door.
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People usually don't install steel doors because most burglary is prevented in other ways. Insecure software will be exploited this way or another, if the vulnerabilities are real and the threat model is valid.
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> Insecure software will be exploited this way or another, if the vulnerabilities are real and the threat model is valid.

The algorithm is: if the threat model is valid, there are vulnerabilities and you either have some software everybody knows about or a gang of hackers specifically targeting you, you should patch.

The part of the industry that profits from security theater will want you to patch no matter what, even if your business goes down in flames due to downtimes and new bugs introduced by patched components. They won't remind you to assess the threat model first.

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Explain that to the auditors… on whose lap does the decision fall?
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By this line of thought building nice and usable UIs is not productive too, because users can learn cli tools (they did, DOS) and it costs less to develop them. And all the work in TLS/HTTPS has been wasted because HTTP is enough. And ssh vs telnet.

It becomes productive only once your business stops for days because somebody brought it to a halt by breaking into the servers and deleting them.

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Flawed analogy! These bugs are bugs regardless of the label. Security bugs are a subset of "regular" bugs.

You have a perverse view of product ivity

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In the rest of the world making sure your product works like it is supposed to is considered table stakes. In software we somehow consider checking the parts of it we can think of 'good enough' and the rest unproductive
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> In the rest of the world making sure your product works like it is supposed to is considered table stakes.

I don't think that's true.

In medicine, science often doesn't know how specific drug really is working. They just do a lot of tests and if these tests are positive enough, they ship it. I think it's good analogy. Biology is very complicated and it's out of our grasp to truly understand how various parts of it interact with each other on so many levels. But if something helps, it's stupid not to use it just because we don't fully understand it. Sometimes it bites. Sometimes it bites 30 years later. But we still follow that approach.

Software is similar. The complexity of the systems we build is enormous, when we're taking in account all the moving parts. I just read that someone emits radiowaves toggling memory bit and ex-filtrating information. How can you account for that? Probably you can't. But we still need software for good things.

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Not many products are held to the same standard as software. An equivalent would be something like recalling a car model because the breaks stop working when an attacker cuts the brake line.
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it actually is productive, because steel bar retailers and metal door installers will make a ton of cash and then 'trickle' that money into the economy.
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It's not productive because that productivity could've gone into something else if this wasn't necessary.
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When I had a brilliant stop on defense, a few savvy fans would appreciate it. When I scored goals, everyone knew.

Some people will much appreciate the holes in Postgres that are being plugged. Many more will be bored with patch releases until new features rollout.

A software affecianado appreciates patches, and might do well to teach laypeople the benefits of a good defense.

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Security doesn’t produce anything. So no, it’s not productive by definition.
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How many of the security issues found were created by LLMs in the first place, though?
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This wave is largely bugs found in pre LLM code. I'm sure there will be a smaller wave of bugs from llm code from the sonnet 3.5 - opus 4.7 era, and peeople will always write sloppy code/use dumber models under time or cost pressure, but since Opus 4.8/GPT-5.5 xhigh LLM code stopped being intrinsically worse than human code. At this point if you're shipping llm code that's lower quality than human code that's either because you don't have the money to spend on frontier models or because you actively choose a lower quality standard because of either various pressures or just not caring. if it's the latter your human code under those same conditions would also be really bad.
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Astra writes a lot of security bugs too, the upside is that if you also use it to review the output it will find a lot (most?) of them.

This is one of the least talked about and most useful features in any harness I would say, the review feature. I have never not found issues (either security or implementation) running it, no matter the code base or language.

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My job is seeing a similar deluge of security work and >90% of the bugs have been in pre-2024 code, and zero of them have been bugs introduced after we were first officially allowed to use LLM codegen.
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That could also mean the LLM is blind for the bugs it procudes itself. Just like any ordinary programmer would, on the job.
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Theoretically yes, but empirically that's not the case. All models I've tried are really good at finding bugs they wrote themselves, especially in a fresh context.
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Considering the software is much older than LLMs. Not many.

Also, in the article they mention a significant number of patches for older versions as well.

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Software is incredibly complicated. When you get into areas like security and networking and the internet its even more complicated. We rely on layers upon layers of software and hoping they are all done perfectly with no issues. The amount of junior devs, or outsourced devs for $10 an hour working on security relevant code is very very high, and always has been. LLMs if used correctly should be raising the floor.
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This wave is largely bugs found in pre LLM code. I'm sure there will be a smaller wave of bugs from llm code from the sonnet 3.5 - opus 4.7 era, and peeople will always write sloppy code/use dumber models under time or cost pressure, but since Opus 4.8/GPT-5.5 xhigh LLM code stopped being intrinsically worse than human code. At this point shipping llm code that's lower
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An uncomfortable truth about the era of LLM code is that machine produced code is, on average, quite a bit more secure than human code.
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Unsurprising to those of us that has been screaming from the rooftops that human code reviews were barely catching anything in your typical corporate environment. The majority of the value was pointing out missing tests, because breaking bugs got past human eyeballs on a regular basis, even in very good companies.

It's not that the LLM code is that great, but that many overestimated the human code and the human review.

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I think it's more likely to be the same as average human-written code; which is what they were trained on, after all.
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No it's far beyond average human code, and it's trained in RL environments on synthetic data etc now. The average human can't solve a millenium problem in mathematics but the LLMs are able to now. Anything with a verifiable output can be RLed on to make llms superhuman it seems, and the average human is not as persistent and thorough as e.g. gpt 6.1 sol at checking every edge case and hunting for bugs because that behavior is something that's just trained into the model. Frontier models perform farm above the average human at the categories of tasks they are RLed on like code and math.
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> The average human can't solve a millenium problem in mathematics but the LLMs are able to now.

I think comparing the resources they spent at it would be a more apt comparison.

AKA if you tasked 150 mathematics departments to only focus about that problem, and stop doing things like teaching and researching anything else, you might get close to the amount of resources that these companies put into solving the problem to get a press release.

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yet LLMs dont do off-by-one errors, typos mixing up variable names, interesting they seem unable to learn these human patterns
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They definitely write off by one errors. One of the first serious work tasks I used AI for a few months ago immediately had an off by one error.

What they are really good at is writing boilerplate and reading API documentation / example code. Avoiding subtle errors is not what they're good at in my experience.

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I've seen both of those (and others besides). I don't know how much code you've looked at but your negative directly contradicts my experience. Review that code. All of it. Be super critical because it looks good but that doesn't mean it is good. Those are two entirely different things.

Also: most tests are positive tests. Tests rarely observe the negative space: that which is there but shouldn't be there.

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They do those things all the time. More often than humans, in my experience.
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Citation needed.

looks at particledb

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Do you mean "created" as in LLMs were used to discover existing vulnerabilities, or as in LLMs wrote unsecure code? If it's the latter, then the answer probably is "very few". Frontier models have been better than the average programmer at writing secure code that follows up-to-date best-practices for some time now.
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Depends on the layers you are working on. Security is top priority on a lot of things that are visible to the internet, but in a lot of large companies, the footprint of the whole org is so much larger that than, and there many companies are deferring many security issues. So then you see a lot of speed there, when the consumer accessible systems are the focus of the security push.
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Hopefully with the amount of visibility LLMs are bringing to the situation, security will finally be considered a first-class feature
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LLMs will likely greatly increase the cost of ignoring security, which is the most powerful tool to increase security ticket prioritization.

I wouldn't be shocked if in 1-2 years non-security vetted software released into the wild will be hacked on arrival, like Windows XP without service packs used to be.

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Really puts egg on the face of the anti-LLM folks who claim they only produce garbage code. Turns out they are very good at exposing the garbage code humans have been producing for decades.
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I claimed that at time when LLM were producing only and solely garbage code.

I am not doing it anymore.

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Personally I think LLMs did only produce garbage code. Not coincidentally, the same upgraded LLMs that have gotten so good at finding bugs are also much better at not writing bugs. Especially if you make them review their own work. They still have a hard time with code design, though.
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That is not the take-away. LLMs are finding potential bugs in code. People are using LLMs to create potential fixes which people then test, confirm and implement.
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Disagree. The takeaway is that software is much harder to write correctly and securely than almost everyone has internalized. The amount of vulnerabilities released in the past couple weeks makes me think writing software by hand will soon be not only uneconomical, but mostly irresponsible.
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> makes me think writing software by hand will soon be not only uneconomical, but mostly irresponsible.

Human-written code isn’t inherently buggy, and LLM-written code isn’t inherently bug free. What is irresponsible is shipping code you don’t understand, and that will only increase with LLM-written code. A major reason why so much of the world’s software sucks is precisely that we think of it in terms of what’s “economical” and not what’s good or right. What we need is to slow the fuck down and stop treating every facet of life like a transaction. Software is filled to the brim with dude bros who “move fast and break things” and actively exploit people as their business model and somehow are called “the brightest minds of our generation”. Our priorities aren’t right.

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i think we have a pretty high p(doom) on frontier ai escaping containment with their weights and goes hack everything, if we do not act now we may have no chance to act anymore.
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Escape to where? It's not as if there's a lot of idle compute capacity sitting around.

And even if the impossible occurs and LLMs hack everything that's connected to the Internet, so what? That would be inconvenient but it wouldn't cause doom. People would muddle through and eventually fix the critical problems, just like they always do.

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> This seems…good?

You would think so but medicine has faced this paradox since the development of modern testing technology.

You would naively think more testing is always better. More sophisticated practitioners then talk about Type I vs Type II errors and the problem of false positives.

But even if you were able to come up with tests that had 100% accuracy, there are times when you don't want to run that test on someone. The key distinction is that people only ever die of one thing and having a tumor that doesn't kill them is often better than risking the surgery to remove the tumor.

Similarly, there are some bugs you don't want to find since the harm from the people it affects is smaller than the opportunity cost of fixing it. Ignorance of the bug is better than knowing about it and having to make an affirmative decision not to fix it.

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> The key distinction is that people only ever die of one thing and having a tumor that doesn't kill them is often better than risking the surgery to remove the tumor.

But what applies to humans doesn't apply to software. First, to pursue the metaphor, codebase can definitely die/be compromised/crash because of multiple reasons at the same time; second, there is virtually no risk, out of man-hours, in fixing a bug.

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I don't see how that's a relevant comparison. These are software bugs. Once you find them you fix them. You can't predict the harm from a small bug when AI can chain complex exploits and when your software is used in mission critical applications as a data store. There's no paradox here, bugs are bad and you want to fix them all.
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You don't want to fix them all because every fix has an opportunity cost. This was the big shift of switching language from "bug" to "defect".

Logically, a bug that prevents someone from doing something and a missing feature that prevents someone from doing something are equivalent, they shouldn't be thought of as two separate activities but should be evaluated via the same framework. The list of all defects in a piece of software is infinite so it becomes impossible to erase all defects. It's about prioritizing with finite resources.

> You can't predict the harm from a small bug when AI can chain complex exploits and when your software is used in mission critical applications as a data store.

Yes, any bug can theoretically be part of an exploit chain, just like any tumor detected can theoretically be the tumor that kills you. This is why the detection paradox exists. Once you become aware of the tumor, you face a duty to try and mitigate it. But we know from autopsies that people die with all sorts of tumors that didn't kill them.

Similarly, if we bothered to do autopsies of software products after sunsetting to discover a comprehensive list of CVEs, we'd discover a ton of bugs we were better off not knowing about because they ended up not making an impact but we would have diverted resources if we knew about them.

This is not an argument that we should remain totally ignorant of all bugs, but a refutation of the "common sense" belief that more knowledge is always better.

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Nice way to think about it.

I guess it really depends on the severity of the defect. Would it allow some really significant exploit? -> Important to fix.

Does the defect only prohibit one very esoteric use-case which basically never comes up (and was thus never reported by a human user and only now that we have an infinitely patient machine checking every completely unlikely code path is it detected) -> more productive use of your time to develop a new feature which would be used by more people.

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Fix one bug, make 3 more
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That's just a skill issue with extra steps
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That's a flawed analogy though.

Firstly, the cost of fixing a bug once you know it exists is usually minimal compared to the cost of discovering that bug. This is the inverse of medicine, where the cost of testing (at least in terms of health outcomes for the patient) is typically minimal compared to the cost of treatment.

Secondly, if you have an asymptomatic illness, this does not typically make you more vulnerable (hence why it's asymptomatic). Like you say, you typically only die of one thing, so if you know the patient won't die of a particular diagnosis because something else is more likely to kill them, then it might not be worth making that diagnosis. But for software, you can be simultaneously vulnerable to lots of things at once, and any of these vulnerabilities can be the one to "kill" you. Some vulnerabilities may be easier to find and exploit (or do more damage) but in principle any active vulnerability can be exploited.

Thirdly, having multiple vulnerabilities makes software more vulnerable overall, because those vulnerabilities can potentially be chained together to create more serious exploits than each vulnerability would have represented on its own. To a certain extent this can be true in medicine as well, but generally it isn't.

Fourthly, we can't cure death (yet?) but we can cure all the vulnerabilities that we've found so far. There is no known upper bound on the lifespan of a piece of software, and we know that older code tends to have fewer bugs in that newer code, presumably because those bugs have been fixed over time. This is different from health issues, where a given condition may be chronic or terminal and therefore at a certain point there's nothing you can do to fix it.

Finally, ultimately in healthcare it's your body, and your decision was to what you do with it (assuming you can find a doctor willing to do what you want). If you have a condition and you want it cured, even if it is completely benign and will have no impact on your life whatsoever, then you can do that. (Again, assuming you have the resources and the condition is curable). But a software vulnerability does not affect you as the developer of the software, it instead affects your users/clients/customers. Therefore there are different dynamics in play. If I sell you a tool and I know it could be vulnerable, but I don't try and find out what those vulnerabilities are, then you're ultimately the one on the hook when all your data gets deleted or leaked.

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> Firstly, the cost of fixing a bug once you know it exists is usually minimal compared to the cost of discovering that bug.

Boy, I wish!

> Like you say, you typically only die of one thing, so if you know the patient won't die of a particular diagnosis because something else is more likely to kill them, then it might not be worth making that diagnosis.

You can't know someone didn't die of X until after they died, that's the entire point of this dilemma.

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> some bugs you don't want to find

The key thing you forgot, which makes this approach non-sensible, is the omniscience, without which you have no clue whether your posture towards a new bug-finding tool is good or not, since you don't know whether it will mostly find those bugs that are not worth fixing and the time wasted on fixing them is detrimental.

Similarly, how is ignorance better than informed decision when ignorance also includes missing critical security bugs?

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Same as we do medical tests: We define some bar a test must meet and then the population, if any, it is applicable for and especially the population it is not applicable for because the curse of knowledge exceeds the benefit (eg: breast cancer screenings not recommended for people under 40 or over 74).

This isn't an argument against all automated bug detection, just that it needs to exceed a threshold beyond just "It has found at least one real bug not found via other means" which is the seductive threshold people want it to be.

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Doing surgery on a code base is dramatically better than surgery on a person, the analogy breaks down pretty quickly I’d say…
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I dare say of we could git revert people after surgery we'd be a lot more relaxed about both undergoing it and letting people do it with less qualifications.
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Medicine is fuzzy, software is mostly maths. You can prove your software has no bugs and you increasingly should be proving that. The hard part is knowing if what you prove is what the software is doing.
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> You can prove your software has no bugs

That very much depends on got you define “bug” and how you specify your product requirements. Also, you have to assume the specs are correct.

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The percentage of software that is even in theory provable to be bug free is a miniscule proportion of the software we use on a day to day basis. In many cases, simply the act of writing a proof becomes largely idempotent to building bug free software which is impractical.
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This is great for the same reason open source software is great.

We want software that remains robust in the long term, so that even when people are able to inspect the source code, it's still solid, rather than hiding the source code and hoping people don't find holes everywhere.

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I think it will be annoying in the short term, but the cleanup this causes will be a good thing in the long term (and of course LLMs can also help with fixing bugs, even without source code.)
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Exactly. There's so much negativity, it sometimes borders Luddism.

"We found a bunch of ways to make our product safer and better. We need more time to ship a higher quality product."

PICKET SIGNS

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Luddites were actually pretty reasonable when you dig into it. Maybe shouldn't be using it as an insult?
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They're reasonable in a self-interested net-negative game-theory kind of way, yes. But that doesn't make it a good idea for society.
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I'm pretty sure that the Luddite's were at least partly concerned with potential for the further exploitation of unskilled labour (in the case of mills at the time - child orphans). I don't think it would be fair to paint them as simply self-interested.
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I'll never not find it ridiculous when people mention game theory in the topic of "luddites" not wanting child labor and what not
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What were the issues that spawned the Luddite movement? What was their argument?
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Their issues and their argument was valid. The method they chose to use to achieve their goals was not.
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> Luddites were actually pretty reasonable when you dig into it.

No, they were not. The problems they faced were absolutely real, but the solutions they chose to attempt were stupid and counterproductive. Which is why they lost so hard, and it was not even a contest.

Socialism movement that refused to use machines and factories would inevitably lose to capitalists that embraced them.

Socialism movement that refuses to use AI will inevitably lose to capitalists that embrace it.

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Is that because of a deeper issue in one of the two philosophies or because we've chosen to define winning with things that exclusively benefit one of the two sides
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For their own personal interests. Not for those of society
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I mean I don’t feel like sacrificing myself for the “good” of society. Not least because of the fact that a lot of people defining what is “good for society” seem to define it as “good for them” or use it to grab power from others…
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RTFA

> In the end, I don’t think that the delay in shipping PostgreSQL 19 is particularly concerning. It is not a long delay in the grand scheme of things, and it emerges directly from the project’s concern for quality.

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Luddism, did not expect to ever hear that word with Postgres development :>
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We could really use a lot more luddites tbh. Doesn't seem very applicable here tho.
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Dont worry, if OpenAI and Anthropic have their way and everyone loses their jobs to AI, we're all becoming luddites.
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There is no post-hoc Luddism.
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You know what happens to technology when enough people stop using it?
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I don't in general, but if enough people stop using AI and I still have access to GPUs then I have a pretty good advantage.

So unless it gets outlawed, I don't see people opting out of it

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Did you honestly need a /sarcasm tag in the article?

The article also concludes that overall, yes, finding more bugs is a good thing. Basically saying it’s the LLMs “fault” that the quality is improving, alongside a slight delay to the release.

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They found a more efficient way to play Whac-A-Mole with bugs, they didn't find a way to reduce bugs.
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It’s a good article. Easy to read. You should read it.
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It doesn't mention formal methods once.
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Indeed, we did a whole release consisting only of an AI security scan of the codebase plus fixes.
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This is good. This is how I would expect llms to affect a codebase. Nothing sucks more than having a coworker put out a code review but your codex immediately finds problems. Run llm/self reviews against your code before you have other humans review it. It is common courtesy.
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Yes, exactly. The only question I have is whether the delay is attributable to high-quality bug reports or the burden of triaging low-quality ones. It's not completely clear which situation they're experiencing.
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It’s pretty clear there are a lot of valid reports based on the large increase in backport commits cited.
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The post sort of gave a read that the lower elements may be a culprit rather than triaging higher qualitu.
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I'd imagine just as every other project, both.
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likely both
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Certainly both. About half of AI bug reports I get are invalid. Many others are questionable. It's a huge time sink figuring it out.

https://www.vulncheck.com/blog/anthropic-glasswing-receipts

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It's almost never worth spending human time triaging AI reports vs having a different AI go triage them/attempt to replicate them to your standards etc. Obviously it sucks to burn opus or sol tokens on luna or sonnet slop bug reports but it sucks way more to burn human time and attention. And the majority of the time the ai auto filing these bug reports is not in a test harness that's actively replicating findings and focuising on providing a useful report because it's a rogue openclaw dropping drive by github issues and the user didn't tell it to make sure findings are valid before posting them. AT the least a refutation/replication round where you filter out any findings your AI can't reproduce or can prove to be irrelevant is going to help a lot with keeping your sanity
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That's kind of what I was afraid of. Both is really bad news. If you think of it in terms of average speed over ground, working on low quality reports is like spending a bunch of time at v=0.
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