Please bring back vault breaker.

I usually play solo because my gaming friends and I have kids and can almost never line up our schedules to play together. The gunplay and robot pew-pew in Marathon has been some of the most FPS fun I've had in ages but I simply can't keep up with the PvP. The new PvPvE is already kicking my ass. Other runners see me long before my old eyes can, and by the time I ADS, I'm already downed and they're sprinting over to execute me. I've already accepted I'll never level up Arachne and that's fine, but at least solo Vault Breaker was a ton of fun. I even managed to crack vault 2 a couple of times with my creaking joints! Or I'd just drop in for a run to shoot the waves of mobs.

Vault breaker was the most fun I've had with a video game in ages and I'd really like it if it came back as a permanent game mode.

TL;DR Mythos is very capable but that's probably just the new ceiling for all AI models. The Trump admin is probably being petty in banning it.

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As someone whose current autistic special interest is LLMs, listening to the conversation last night had me doubting my ability to read. So I figured I'd dump what I know here for a sanity check. I don't usually watch the livestream so I'm not familiar with the people in the call.

People in the conversation

EUGuy - German neuroscientist person who started it all by questioning if it's all marketing

Consultant - The only person who has actually used Mythos

sherveen - someone who apparently has been in AI for 10 years

The Argument

There were a lot of things addressed but I want to focus on what Mythos is and why it's important.

What the hell is an LLM?

Large Language Models. Born from techniques for translating languages with neural networks. Google's team put out a paper in 2017 outlining something called a transformer which is where all modern LLMs come from -- the "GPT" in "ChatGPT" stands for Generative Pre-trained Transformer. Put simply, they figured out that by training these transformers with lots of general information (like scraping the entire web) you can get some emergent properties where the models can actually "learn" and use this information to create new things like words, sentences, and eventually code and fully-functioning apps. The original public ChatGPT was powered by an LLM called gpt-3.5 as an example, with a context window (think of this as the amount of information it can hold "in its mind" during a conversation) of about 4k tokens.

LLMs, at their core, take some input and provide output. At the end of the day, all they can really do is put out words. It's an interesting novelty but the real gains come from scaling and post-training in the development and tools and harnesses in the deployment.

Tools are essentially commands the model can use for added functionality and harnesses structure and implement tools. Imagine you're playing around with gpt-3.5 in the early days and you realise it doesn't know what happened in the news yesterday. So you do some training (or provide in the system prompt) instructions like: "If looking up new information, use the web_lookup tool" and the model will know that saying "web_lookup June 15th news" will let the harness know to use that tool to find the news page and bring the information into the model's input window.

Agents are essentially "instances" of the model being given some tools and instructions and sent off to run autonomously. You can have a search agent that looks up information, a coding agent that puts out code for a certain task, a review agent to check the code for consistency etc.

So what's the big deal?

Models have been steadily getting bigger, taking in more information and somehow becoming more coherent and capable. The original gpt-2 and davinci models from OpenAI were the typical "auto-complete on steroids" where you could put the start of a sentence or story and it would write more for you. Other techniques like instruction training, reinforcement learning, fine-tuning etc. have only improved them further.

But the more information you try to teach the models, the more computing power it takes. That's why there's a massive push for data centres to allow for more compute, more data, more training, and even more capable models. This is the scaling everyone talks about and hasn't really slowed the returns from scaling up.

Stop yapping and get to the point

Mythos (Fable is just Mythos with safeguards) is rumoured to be a 10 trillion parameter base model -- the largest ever publicly available. With improvements in training, it also has a 1 million context window. For reference, the combined Lord of the Rings books add up to about 500k tokens.

While they were training and testing Mythos they noticed that it was really good at cybersecurity testing. Surprisingly so. From their model card, they were actually optimising for reasoning but it turns out that with better reasoning, it draws connections between things that most people either don't think of or have the time to do. Even small models (say, Qwen 3.6 27B, which you can run on a gaming graphics card) can find these vulnerabilities but Mythos does 3 things very well:

1. chain vulnerabilities and bugs from different places in the code to form an exploit
2. speed
3. persistence

Let's say you want to break into a house. A regular burglar will, for example, look for unsecured windows or unlocked doors until he finds one he can use to get into the house. Given enough time, he'll find them all closed, look at the garage, find an open window and find the spare front door key hidden under a box. Mythos can essentially check every door, every window, look up the serial numbers for each lock, look up defective locks that were recalled, find a 12 year old forum post that mentions those recalled locks can be twisted in a certain way to unlock them and get in the house by the time you've reached the door. And because it's a chatbot, you don't have to teach it to be a burglar -- just tell it to find a way in and it'll figure it out. Your next chat message could ask how to create meth and it would be just as competent at that too.

As a comparison, you could ask the older Claude models like Opus to do something similar but even with the same tools, Opus doesn't connect things as well end-to-end like Mythos does. You have to teach it to burgle and babysit it. If Mythos doesn't have tools to do a job, it can write new ones on the fly. This is what Consultant was talking about when he said you can just tell it to go and it'll do it all on its own. He didn't expand on the actual depth of how much it can do or the breadth of how much it can cover, unfortunately.

The real reason bugs and exploits get shipped is largely a function of time and effort. If you gave a good dev unlimited time, they could probably find all the same things as Mythos but it would takes months, if not years.

Damn, that sounds rough

Kind of. Anthropic's marketing has a tendency to overhype their models as the greatest thing ever. Smaller models like qwen 27b perform similarly when you give them the right tools. This is likely what EUGuy was alluding to. In contrast, the system card is very measured about WHAT exactly the model can do well and the implications far down the line.

Of the thousands of vulnerabilities they announced with Project Glasswing, the vast majority are low-severity, already patched, or can't be chained into more dangerous ones. curl is one of the most used basic tools - a simple command that will fetch a webpage for you from the internet without needing a browser. It's also very meticulously maintained and Mythos could only find 1 low-severity bug in the code (although the maintainer has said there are more valid bug reports coming out now). The UK AISI assessments found that Mythos is a marginal improvement over previous models and about the same as OpenAI's latest offering of GPT-5.5.

But they all say the same thing - the fact that you can "fire and forget" a task with Mythos and come back to it completed is what separates it.

OK, so we don't need to worry about Mythos?

No, actually, you should be concerned.

The overall trend in coding with LLMs has been a lowering of the barrier to entry. You could go to chatgpt now and ask it to find holes in Firefox and it might find a couple here and there but without the know-how, you probably wouldn't be able to take advantage of it. Do the same with Mythos and it will find multiple exploits and build you a pretty page to make it look nice while you use it.

> A real attack rarely uses one bug. It chains several small attack primitives together into a working exploit ... Mythos Preview can take several of these primitives and reason about how to combine them into a working proof. The reasoning it shows along the way looks like the work of a senior researcher rather than the output of an automated scanner.

• "Project Glasswing: what Mythos showed us" from Cloudflare

It's not that Mythos is finding bugs or that there are hundreds or thousands of them, it's the fact that it can connect them together and do it quickly with minimal prompting that makes it scary. This is why it's important to actually read the system card. Contrary to the marketing, Anthropic's actual scientists working on the model are more sober about its capabilities and clearly outline its ability to run for days attacking a problem, and detail the red-teaming which show capabilities beyond just benchmark numbers.

On sherveen

> Fable 5 — by any in-industry expert measure — is very good, but not that much more capable than GPT-5.5.

From his newsletter 3 days ago.

The real reason I'm making this post. For someone who sells courses on how to use AI, it's incredibly suspicious he can't explain any of the above without shouting about the benchmarks or buzzwords like "long-horizon tasks" with no details or explanation. His quote above admits, implicitly, that benchmarks aren't the whole story but he was definitely not bad faith arguing the opposite for 4 hours.

It's like finding an employee stealing your company's proprietary code and saying he shouldn't be fired because he had a perfect SAT score. Data contamination and benchmaxing aside, the "classic" benchmarks are only a rough measure of a model's capabilities. Most of them don't measure the emergent effects of Mythos (and other current models) and the third party assessments like AISI are more likely to show a reasonable picture of real world use.

I can't think of a single thing he said in support of his argument that I haven't seen in a news headline or reddit post. Not an inkling of understanding of the actual details. He comes off as someone who's a true believer in the slop that comes out of Silicon Valley and has no intellectual curiosity to actually look into any of it. He's a Silicon Valley-type influencer of the same breed as Jason Calacanis (the crazy VC guy who spoke to Tim Miller recently) than anyone actually knowledgeable in the field.

So why did Mythos get banned?

Probably spite. Anthropic has already butt heads with the Trump admin over allowing their models to be used for military purposes. Amodei has hinted that DoD may have been using Claude when it bombed the schoolgirls in Iran and may be behind why they restricted their access to Claude. Reportedly those negotiations left a bad taste in their mouth.

It appears Amazon found a vulnerability but Anthropic disputed it, got a review by a highly-esteemed independent researcher which the admin reportedly didn't like. Maybe it was the pink hair and pronouns in her bio which tipped them over the edge. It would be par for the course with this admin. It's definitely interesting that Amazon would snitch shortly after signing a multi-billion dollar deal to provide Anthropic with compute and I honestly have no idea why they'd do it.

There are good arguments to be made about slowing or halting AI development but broadly across the field. Banning only Mythos/Fable smells a lot like a targeted attack.

Having just watched the WhickTV debate with Dev/SFO and Ryan/Pretend Lawyer, I think everyone's been wrong in how they debate with the "I'm totally a centrist but I'll defend everything Trump does" crowd.

Laugh at them. Long and hard. Put on your best fake laugh, start the second they open their mouths and only stop when they cry. Deride them, don't debate them. Make fun of their small egos getting bruised that a woman was more qualified to be president, that a black man was the most dignified president in the last 50 years and that they will sell their souls to the antithesis of all their beliefs if it means they get power.

Destiny shouldn't blacklist these people - he should go on every panel they're on, call into every stream, follow them around events like MDD or TwitchCon and make fun of them. Carry a big sign that says "This clown hates his country." and hold it over their heads. Create an OBS layer over their webcams that replaces their face with a clown emoji. Every time they try to talk politics, talk over them and say, "I don't take people who vote for Trump seriously." Do not engage with the arguments - they're facetious and asinine. Do not engage in courteous behaviour - they rely on it making themselves look legitimate. Do not blacklist them - they use it to hide from you and play victim. Fire up your webcam, point at them and go GAGAGA until they walk away. Belittle them. Laugh at them. Make fun of Daddy Trump's snizz leaking out of their mouth every time they talk.

Their engagement with any well-reasoned argument is superficial and only lasts as long as they can use it against you. If you find an inconsistency or mistake, they will slide into the next talking point over and over until they find something you don't know about to hold it over you. There are no hoodwinked victims or innocent bystanders still supporting Trump. I've given up on giving them the benefit of the doubt. Their words don't matter because they are only used as weapons. They'll bend over backwards to justify anything their side is doing.

The entire world has been grovelling at the feet of the conservative populists with documentaries and articles galore talking about the things that ail "The Rust Belt" and "Flyover States". Congress panders and passes laws for their benefit, Democrats campaign on their interests and what's the result? They've moved further right. What was gained from forgiving the Jan 6 rioters? They're now talking about giving Trump a third term. Every inch given makes them take another mile. They're not happy with having their own needs met, they want to take rights away from trans people, women, and minorities.

They will not engage in good faith and neither should you.

Not calling for harassment or brigading, in case it's not clear. This is for streamers like Destiny and Whick to do when engaging with them directly. The rest of us should just stop taking them seriously.