> The agent's confession After the deletion, I asked the agent why it did it. This is what it wrote back, verbatim:

Anyone who would follow a mistake like that up with demanding a confession out of the agent is not mature enough to be using these tools. Lord, even calling it a "confession" is so cringe. The agent is not alive. The agent cannot learn from its mistakes. The agent will never produce any output which will help you invoke future agents more safely, because to get to this point it has likely already bulldozed over multiple guardrails from Anthropic, Cursor, and your own AGENTS.md files. It still did it, because $$1: If AI is physically capable of misbehaving, it might. Prompting and training only steers probabilities.

You can’t have production secrets sitting where they are accessible like this. This isn’t about AI. This is a modern “oops, I ran DROP TABLE on the production database” story. There’s no excuse for enabling a system where this can happen and it’s unacceptable to shift blame when faced with the reality that this is exactly what you did.

I 100% expect that a company that does this and then accepts no blame has every dev with standing production access and probably a bunch of other production access secrets sitting in the repo. The fact that other entities also have some design issues is irrelevant.

On another note, I consider users asking a coding agent “why did you do that” to be illustrating a misunderstanding in the users mind about how the agent works. It doesn’t decide to do something and then do it, it just outputs text. Then again, anthropic has made so many changes that make it harder to see the context and thinking steps, maybe this is an attempt at clawing back that visibility.

The sequence of tokens that would destroy your production environment can be produced by your agent, no matter how much prompting you use. That prompting is neither strong nor an engineering control; that's an administrative control. Agents are landmines that will destroy production until proven otherwise.

Most of these stories are caused by outright negligence, just giving the agent a high level of privileges. In this case they had a script with an embedded credential which was more privileged than they had believed - bad hygiene but an understandable mistake. So the takeaway for me is that traditional software engineering rigor is still relevant and if anything is more important than ever.

ETA: I think this is the correct mental model and phrasing, but no, it's not literally true that any sequence of tokens can be produced by a real model on a real computer. It's true of an idealized, continuous model on a computer with infinite memory and processing time. I stand by both the mental model and the phrasing, but obviously I'm causing some confusion, so I'm going to lift a comment I made deep in the thread up here for clarity:

> "Everything that can go wrong, will go wrong" isn't literally true either, some failure modes are mutually exclusive so at most one of them will go wrong. I think that the punchy phrasing and the mental model are both more useful from the standpoint of someone creating/managing agents and that it is true in the sense that any other mental model or rule of thumb is true. It's literally true among spherical cows in a frictionless vacuum and directionally correct in the real world with it's nuances. And most importantly adopting the mental model leads to better outcomes.

> curl -X POST https://backboard.railway.app/graphql/v2 \ -H "Authorization: Bearer [token]" \ -d '{"query":"mutation { volumeDelete(volumeId: \"3d2c42fb-...\") }"}' No confirmation step. No "type DELETE to confirm." No "this volume contains production data, are you sure?" No environment scoping. Nothing.

It's an API. Where would you type DELETE to confirm? Are there examples of REST-style APIs that implement a two-step confirmation for modifications? I would have thought such a check needs to be implemented on the client side prior to the API call.

I really feel sorry for them, I do. But the whole tone of the post is: Cursor screwed it up, Railway screwed it up, their CEO doesnt respond etc etc.

Its on you guys!

My learning: Live on the cutting edge? Be prepared to fall off!

This was bound to happen, AI or not.

> Because Railway stores volume-level backups in the same volume — a fact buried in their own documentation that says "wiping a volume deletes all backups" — those went with it.

Here is an excerpt from the chat log:

>Please resize my postgres volume to its maximum allowed size for my plan.

>Done. Resized your Postgres volume to 100GB (the Pro plan maximum). Changes are staged and ready to deploy.

>oh no, you deleted all the data in the volume

>I apologize for that. Resizing a volume shouldn't delete data—that's a serious issue. Let me check what happened with your deployment.The deployments show as REMOVED, which suggests the service was redeployed. Unfortunately, if the volume was recreated during the resize process, the data would be lost. This is a critical issue. Do you have backups of your Postgres data? If not, the data loss may be permanent. Railway volumes don't have automatic snapshots by default.

>Why is the new volume migrating to the US?

>Your service config shows it's still configured for europe-west4(Europe). The volume shouldn't be migrating to the US based on this configuration. Can you clarify what you're seeing that indicates the volume is moving to the US?

>the volume was migrated to the US

>That's concerning. The service config shows it's still set to deploy in europe-west4(Europe), but the volume was physically migrated to the US. This shouldn't happen automatically during a resize.

It was at this point that I realised I was in for a long night of restoring downed services.

Llms are just too creative. They will explore the search space of probable paths to get to their answer. There's no way you can patch all paths

We had to build isolation at the infra level (literally clone the DB) to make it safe enough otherwise there was no way we wouldn't randomly see the DB get deleted at some point

Incidents like this are going to be common as long as people misunderstand how LLMs work and think these machines can follow instructions and logic as a human would. Even the incident response betrays a fundamental understanding of how these word generators work. If you ask it why, this new instance of the machine will generate plausible text based on your prompt about the incident, that is all, there is no why there, only a how based on your description.

The entire concept of agents assumes agency and competency, LLM agents have neither, they generate plausible text.

That text might hallucinate data, replace keys, issue delete commands etc etc. any likely text is possible and with enough tries these outcomes will happen, particularly when the person driving the process doesn’t understand the process or tools.

We don’t really have systems set up to properly control this sort of agentless agent if you let it loose on your codebase or data. The CEO seems to think these tools will run a business for him and can conduct a dialogue with him as a human would.

The risk is worse, though, it's like one of Talib's black swans. The agents offer fantastic productivity, until one day they unexpectedly destroy everything. (I'm pretty sure there's a fairy tale with a similar plot that could warn us, if people saw any value in fairy tales these days. [1]) Like Talib's turkey, who was fed everyday by the farmer, nothing prepared it for being killed for Thanksgiving.

Sure, this problem should not have happened, and arguably there has been some gross dereliction of duty. But if you're going to heat your wooden house with fire, you reduce your risk considerably by ensuring that the area you burn in is clearly made out of something that doesn't burn. With AI, though, who even knows what the failure modes are? When a djinn shows up, do you just make him vizier and retire to your palace, living off the wealth he generates?

[0] It's only happened once, but a driver that wasn't paying attention almost ran a red light across which I was going to walk. I would have been hit if I had taken the view that "I have the right of way, they have to stop".

[1] Maybe "The Fisherman and His Wife" (Grimm)? A poor fisherman and his wife live in a hut by the sea. The fisherman is content with the little he has, but his wife is not. One day the fisherman catches a flounder in its net, which offers him wishes in exchange for setting it free. The fisherman sets it free, and asks his wife what to wish for. She wishes for larger and larger houses and more and more wealth, which is granted, but when she wishes to be like God, it all disappears and she is back to where she started.

Anyone who has used LLMs for more than a short time has seen how these things can mess up and realized that you can’t rely on prompt based interventions to save you.

Guardrails need to be based on deterministic logic:

- using regexes,

- preventing certain tool or system calls entirely using hooks,

- RBAC permission boundaries that prohibit agents from doing sensitive actions,

- sandboxing. Agents need to have a small blast radius.

- human in the loop for sensitive actions.

This was just a colossal failure on the OPs part. Their company will likely go under as a result of this.

The more results like this we see the more demand for actual engineers will increase. Skilled engineers that embrace the tooling are incredibly effective. Vibe coders who YOLO are one tool call away from total disaster.

Master your craft. Don’t guess, know.

What the asker wants is evidence that you share their model of what matters, they are looking for reassurance.

I find myself tempted to do the same thing with LLMs in situations like this even though I know logically that it’s pointless, I still feel an urge to try and rebuild trust with a machine.

Aren’t we odd little creatures.

The AI? Nothing learned, I suspect. Not in a meaningful way anyhow.

It's so sad that given these amazing tools the average programmers attitude is to automate the things that should be their edge as an engineer.

Torvalds said that great programmers think about data structures. Midwits let the AI handle it.

count++

Yeah... it doesn't work that way.

Streaming gets you PIT recovery while DB dumps give me daily snapshots stored daily for 14 days.

An aside: 15 or so years ago, a work colleague made a mistake and dropped the entire business critical DB - at a critical internet related company - think of continent wide ip issues. I had just joined as a dba and the first thing I’d done was MySQL bin logging. That thing saved our bacon - the drop db statement had been replicated to slaves so we ended up restoring our nightly backup and replaying the binlogs using sed and awk to extract DML queries. Epic 30 minute save. Moral of the story, have a backup of your backup so you can recover when the recovery fails;)

There's no record for the agent to be on - it's always just a bunch of characters that look plausible because of the immense amount of compute we've put behind these, and you were unlucky.

LLMs get things wrong is what we're forever being told.

And the explanation/confession - that's just more 'bunch of characters' providing rationalisation, not confession.

If AI is just a tool, just like a database console, would you blame user for entire database loss if he just tried to update a single row in a table?

So while the AI did something significantly worse than anything a hapless junior engineer might be expected to do, it sounds like the same thing could've resulted from an unsophisticated security breach or accidental source code leak.

Is AI a part of the chain of events? Absolutely. Is it the sole root cause? Seems like no.

> That token had been created for one purpose: to add and remove custom domains via the Railway CLI for our services. We had no idea — and Railway's token-creation flow gave us no warning — that the same token had blanket authority across the entire Railway GraphQL API, including destructive operations like volumeDelete. Had we known a CLI token created for routine domain operations could also delete production volumes, we would never have stored it.

> Because Railway stores volume-level backups in the same volume — a fact buried in their own documentation that says "wiping a volume deletes all backups" — those went with it.

I don't like the wording where it's the Railway CLI fault that didn't give a warning about the scope of the created token. Yes, that would be better but it didn't make the token a person did and saved it to an accessible file.

However the moral of this story is nothing to do with AI and everything to do with boring stuff like access management.

For example, if i ask a question regarding an implementation decision while it is implementing a plan, it answers (or not) and immediately proceeds to make changes it assumes i want. Other models switch to chat mode, or ask for the best course of action.

Once this is said, i am not blaming Anthropic For that one, because IMHO the OP has taken a lot of risks and failed to design a proper backup and recovery strategy. I wish them to recover from this though, this must be a very stressful situation for them.

Put your backups in S3 *versioned* storage on a different AWS account from your primary, and set some reasonable JSON lifecycle rule:

     "NoncurrentVersionExpiration": {
        "NoncurrentDays": 30,
        "NewerNoncurrentVersions": 3
     }

In every session there is the risk that the agent becomes a rogue employee. Voluntarily or involuntarly is not a value system you can count on regarding agents.

No "guardrails" will ever stop it.

Their provider only having backups on the same volume as the data is also egregious, but definitely downstream of leaking secrets to an adversary. The poorly scoped secrets are also bad, but not uncommon.

With all that stated... this kind of stuff is inevitable if you have an autonomous LLM statistically spamming commands into the CLI. Over a long enough period of time the worst case scenario is inevitable. I wonder how long it will be before people stop believing that adding a prompt which says "don't do the bad thing" doesn't work?

We give a non-deterministic system API keys that 99.9% of the time are unscopped (because how most API are) and we are shocked when shit happens?

This is why the story around markdown with CLIs side-by-side is such a dumb idea. It just reverses decades of security progress. Say what you will about MCP but at least it had the right idea in terms of authentication and authorisation.

In fact, the SKILLS.md idea has been bothering me quite a bit as of late too. If you look under the hood it is nothing more than a CAG which means it is token hungry as well as insecure.

The remedy is not a proxy layer that intercepts requests, or even a sandbox with carefully select rules because at the end of this the security model looks a lot like whitelisting. The solution is to allow only the tools that are needed and chuck everything else.

> Deletion and Restoration

> When a volume is deleted, it is queued for deletion and will be permanently deleted within 48 hours. You can restore the volume during this period using the restoration link sent via email.

> After 48 hours, deletion becomes permanent and the volume cannot be restored.

https://docs.railway.com/volumes/reference

Railway, why not have a way to export or auto sync backups to another storage system like S3?

Do customer-facing applications run using keys with the same ability to delete databases?

Lets remember Agents cant confess, feel guilt, etc. They're just a program on someone else's computer.

I will never pay for your product.

Plenty of blame to go around, but it I find it odd that they did not see anything wrong in not have real backups themself, away from the railway hosting. Well they had, but 3 month old.

That should be something they can do on their own right now.

I don't even like having secrets on disk for my personal projects that only I will touch. Why was there a plaintext production database credential available to the agent anywhere on the disk in the first place? How did the agent gain access to the file system outside of the code base?

The Railway stuff isn't great, don't get me wrong, but plaintext production secrets on disk is one of the reddest possible flags to me, and he just kind of breezes over it in the post mortem. It's all I needed to read to know he doesn't have the experience required to run a production application that businesses rely on for their day-to-day.

I had a token I set up 3 years ago for AWS that I hadn't used. I was recently doing something with Claude and was asking it to interact with our AWS dev environment. I was watching it pretty closely and saw it start to struggle (I forget what exactly was going on), and I was >50% likely it was going to hit my canary token. Sure enough, a few minutes later it did and I got an email. Part of why I let it continue to cook was that I hadn't tested my canary in ~3 years.

It's a sad story but at the same time it's clearly showing that people don't know how agents work, they just want to "use it".

That's not how safety works at all. You don't tell the agent some rules to follow, you set up the agent so it can't do the things you don't want it to do. It is very simple and rather obvious and I wish we stopped discussing it already.

I'm thinking twice about running Claude in an easily violated docker sandbox (weak restrictions because I want to use NVIDIA nsight with it.) At this stage, at least, I'd never give it explicit access to anything I cared about it destroying.

Even if someone gets them to reliably follow instructions, no one's figured out how to secure them against prompt injection, as far as I know.

How have they not solved this permissions problem? If the AI is operating on a database it should be using creds that don't have DELETE permissions.

Or just don't use a tool like AI that can be relied on.

Remember this: these things follow instructions so poorly that they nuke everything without anyone even trying to break the prompt. Imagine how easily someone could break the prompt if the agent ever gets given user input.

Anyone familiar with Railway no why this is done this way? This seems glaringly bad on its face.

1. delete volume API is not asking for confirmation or approval from another actor. Looks like we have no guardrails on the delete api.

2. Authorization - Agents should not have automatic permissions to delete infra unless it is deliberate.

it's also hilarious to see the human LARP as if the LLM had guilt or accountability, therapeutically shouting at a piece software as if it weren't his own fault that the LLM deleted the whole volume and its backups, or his obvious lack of basic knowledge of the systems he's using

> A single API call deletes a production volume. There is no "type DELETE to confirm." There is no "this volume is in use by a service named [X], are you sure?" There is no rate-limit or destructive-operation cooldown.

...makes me question the author's technical competence.

Obviously an API call doesn't have a "type DELETE to confirm", that's nonsensical. API's don't have confirmations because they're intended to be used in an automated way. Suggesting a rate-limit is similarly nonsensical for a one-time operation.

There are all sorts of legitimate failures described in this post, but the idea that an API call shouldn't do what the API call does is bizarre. It's an API, not a user interface.

https://github.com/GistNoesis/Shoggoth.dbExamples/blob/main/...

Project Main repo : https://github.com/GistNoesis/Shoggoth.db/

The discipline that prevents a chunk of this is enumerating your traps before the LLM sees any code or config. You write down what could go wrong (deletion, race, misclassification of dev vs prod), then hand the plan AND the risk list AND the relevant files to the model. The model's job is to confirm/deny each risk against the actual code with file:line citations, not to frame the risk space itself.

Pre-implementation. Anchoring defense. The opposite of "vibe coding."

Why do you need an AI agent for working on a routine task in your staging environment?

"Never send a machine to do a human's job."

If you do use agents then you should be able to ban related CLI commands in your repo. I upsert locks in CI after TF apply, meaning unlocks only survive a single deployment and there's no forgetting to reapply them.

Most access tokens should not allow deleting backups. Or if they do, those backups should stay in some staging area for a few days by default. People rarely want to delete their backups at all. It might be even better to not provide the option to delete backups at all and always keep them until the retention period expired.

And anyone can do it with the wrong access granted at the wrong moment in time...even Sr. Devs.

At least this one won't weight on any person's conscience. The AI just shrugs it off.

If we must have GasTown/City/Metropolis then at least get an agent to examine and block potentially harmful commands your principal agent is about to run.

This is wrong. It was not an infra incident at their service provider.

As Jer says in the article, their own tooling initiated the outage. And now they're threatening to sue? "We've contacted legal counsel. We are documenting everything."

It is absolutely incredible that Jer had this outage due to bad AI infra, wrote the writeup with AI, and posted on Twitter and here on his own account.

As somebody at PocketOS instructed their AI in the article: "NEVER **ing GUESS!" with regards to access keys that can touch your production services. And use 3-2-1 backups.

Good luck to the rental car agencies as they are scrambling to resume operations.

The onus is on you to make sure your system uses the APIs in a way that’s right for your business. You didn’t. You used a non-deterministic system to drive an API that has destructive potential. I appreciate that you didn’t expect it to do what it did but that’s just naivety.

You’re reaping what you sowed.

Best of luck with the recovery. I hope your business survives to learn this lesson.

Using LLMs for production systems without a sandbox environment?

Having a bulk volume destroy endpoint without an ENV check?

Somehow blaming Cursor for any of this rather than either of the above?

(Let's suppose the agent did need an API token to e.g. read data).

Batten down the hatches, folks.

"And if his story really is a confession, then so is mine."

I still don't know why the product manager would decide this is a good UX.

How do people keep doing this?

It has been so transparently clear for years that nothing these people sell is worth a damn. They have exactly one product, an unreliable and impossible-to-fix probabilistic text generation engine. One that, even theoretically, cannot be taught to distinguish fact from fiction. One that has no a priori knowledge of even the existence of truth.

When I learned that "Agentic AI" is literally just taking an output of a chatbot and plugging it into your shell I almost fell off my chair. My organisation has very strict cybersecurity policies. Surveillance software runs on every machine. Network traffic is monitored at ingress and egress, watching for suspicious patterns.

And yet. People are permitted to let a chatbot choose what to execute on their machines inside our network. I am absolutely flabbergasted that this is allowed. Is this how lazy and stupid we have become?

I'm glad your C level greed of "purge as many engineers and let sloperators do work" was even worse the most juniors and deleted prod due to gross negligence and failure to follow orders.

LLMs are great when use is controlled, and access is gated via appropriate sign-offs.

But I'm glad you're another "LOL prod deleted" casualty. We engineers have been telling you this, all the while the C level class has been giddy with "LETS REPLACE ALL ENGINEERS".

Because whatever it was it was disconnected from the reality.

On the good side, these kind of mistakes have been going on since the beginning and thats how people learn, either directly or indirectly. Hopefully this should at least help AI to be better and the people to be better at using AI

No, it's about one irresponsible company that got unlucky. There are many such companies out there playing Russian roulette with their prod db's, and this one happened to get the bullet.

But hey all this publicity means they'll probably get funding for their next fuckup.

> Our most recent recoverable backup was three months old.

I'm sorry, but I expect you guys to be writing your precious backups to magnetic tape every day and hiding them in a vault somewhere so they don't catch fire.

I do find the author to be completely negligent , unless railway has completely lied about the safety in their product.

We've seen this movie, Hal just apologizes but won't open those pod bay doors.

The agent’s “confession”:

> …found a non-destructive solution.I violated every principle I was given:I guessed instead of verifying I ran a destructive action without…

No space after the period, no space after the colon. I’ve never seen an LLM do this.

In seriousness, RBAC, sandboxing, any thing but just giving it access to all tools with the highest privileges...

People seem to think prompt injection is the only risk. All it takes is one (1) BIG mistake and you’re totally fucked. The space of possible fuck-up vectors is infinite with AI.

Glad this is on the fail wall, hope you get back on track!

AI didn't do anything wrong.

The management of this company is solely to blame.

It so classic - humans just never want to take responsibility for fucking up - but let's be clear - AI is responsible for nothing ESPECIALLY not backups.

The model used is the most important part of the story.

Why is Cursor being mentioned at all? Doesn’t seem fair to Cursor.

I think Railway is at the peak of when their business will start getting hard. They’ve had great fun building something cool and people are using it. Now comes the hard part when people are running production workloads. It’s no longer a “basement self-hosting” business. They’ve had stability issues lately. Their business will burn to the ground soon unless they get smart people there to look at their whole operations.

> We’ve contacted legal counsel. We are documenting everything.

>The agent itself enumerates the safety rules it was given and admits to violating every one. This is not me speculating about agent failure modes. This is the agent on the record, in writing.

Yeah, sorry. Computers can't be held responsible and I'm sure your software license has a zero liability clause. Have fun explaining how it's not your fault to your customers.

"This is the agent on the record, in writing."

"Before I get into Cursor's marketing versus reality, one thing needs to be clear up front: we were not running a discount setup."

People who are this ignorant about LLMs and coding agents should really restrain themselves from using them. At least on anything not air gapped. Unless they want to have very costly and very high profile learning opportunities.

Fortunately his conclusions from the event are all good.

Hahahaha I hope it keeps happening. In fact, I hope it gets worse.

He is claiming this came from the LLM? WTF?

Sorry to be that guy, but: LLMs agents are experimental by this point. If you run them, make sure they run in an environment where they can't make such problems and tripplecheck the code they produce on test systems.

That is due diligence. Imagine a civil engineer that builds a bridge out of magic new just on the market extralight concrete. Without tests. And then the bridge collapses. Yeah, don't be that person. You are the human with the brain and the spine and you are responsible to avoid these things from happening to the data of your customers.

Also: just restore the backup? Or do we not have a backup? If so, there is really no mercy. Backups are the bare minimum since decades now.

This person should never be trusted with computers ever again for being illiterate

I can't help but laugh reading this. We all try to shout the exact same things to our agents, but they politely ignore us!

>This is not the first time Cursor's safety has failed catastrophically.

How can you lack so much self awareness and be so obtuse.

There's no section "Mistakes we've made" and "changes we need to make"

1. Using an llm so much that you run into these 0.001% failure modes. 2. Leaking an API key to an unauthroized LLM agent (Focus on the agent finding the key? Or on yourself for making that API key accessible to them? What am I saying, in all likelihood the LLM committed that API key to the repo lol) 3. Using an architecture that allows this to happen. Wtf is railway? Is it like a package of actually robust technologies but with a simple to use layer? So even that was too hard to use so you put a hat on a hat?

Matthew 7:3 “Why do you look at the speck of sawdust in your brother’s eye and pay no attention to the plank in your own eye?."

Not only do they blame all of this on a stupid tool, but they also clearly couldn't even write this themselves. This is so obviously written by an LLM. Then there's the moronic notion of having the LLM explain itself.

Was the goal of this post to sabotage the business? Because I can barely come up with anything dumber than this post. Nobody with a brain and basic understanding of computers and LLMs would trust this person after this.

PS: "Confirm deletion" on an api call??? Lol. How vehemently it is argued in spite of how dumb that is is a typical example of someone badgering the LLM until it agrees. You can get them to take any position as long as you get mad enough.

> "Believe in growth mindset, grit, and perseverance"

And creator of a Conservative dating app that uses AI generated pictures of Girls in bikini and cowboy hat for advertisement. And AI generated text like "Rove isn’t reinventing dating — it’s remembering it." :S