It’s time to demystify Mythos.
Mythos is not magic. It’s not a doomsday device. It’s the first of many models that can automate cyber tasks (just like coding).
OpenAI’s GPT-5.5-cyber can now do the same. And all the frontier models (including those from China) will be there within approximately 6 months.
It’s important to recognize that these models do not create vulnerabilities; they discover them. The bugs are already in the code. Using AI to discover and patch them will actually harden these systems.
The leap from pre-AI cyber to post-AI cyber means that there will be a big upgrade cycle. After that, however, the market is likely to reach a new equilibrium between AI-powered cyber-offense and AI-powered cyber-defense.
Obviously it’s important that cyber defenders get access before cyber attackers. That process is already underway but needs to happen quickly (see point above about Chinese models).
Unlike Mythos, GPT-5.5-cyber appears not to be token constrained so it may be the first cyber model that defenders actually get to use.
@webdevcody It’s much more literal about following instructions. I think a lot of the initial complaints are because fork lifting existing agent instructions and steering will not produce a direct “upgrade”. The model actually does what you ask it to now, without excessive convincing.
@thdxr This is how I run Opencode today. It’s a better model (imo) given the architecture you already have, rather than defaulting to a 1:1 server:client process.
@thdxr We’re still in the infancy for AI adoption. Even across software engineering, let alone literally everything else bound to be changed or dramatically disrupted with AI.
This is easily the most transformative technological shift since the Industrial Revolution. It’s not a bubble
Bill Gates is setting up factories to manufacture 7 leading vaccine candidates before we know which is best & safest; we can test the vaccines in parallel, and then throw away all but the factory for the best vaccine. May save many months.
Just extraordinary.
I’m seeing so many articles that provide no value aside from invoking fear. Stay informed but steer clear of any doomsday news. Anything providing actionable info is valuable. Otherwise it’s information that contributes to fear for factors out of ones control. #coronavirus
Open-label pilot trial found that hydroxychloroquine (antimalarial drug also used for lupus) has shown great promise in the treatment of COVID-19. Addition of the antibiotic azithromycin w/hydroxychloroquine was even better. More RCTs to confirm underway. https://t.co/5qfdITkc4i
@CBSThisMorning@eyepv6@drtaranarula Be precise. 20% of those who were sick enough to seek care AND qualified for testing. Approximately 80% of people who contract this have minor symptoms or are asymptomatic. Phrases like “in this country” imply we know of every case when the opposite is true; we know of a fraction
The statistics being reported around #covid-19 are incredibly misleading, as they’re based on confirmed cases. A case can only be confirmed with testing and testing in the US remains highly restricted. Point is we have accurate numerators with entirely unreliable denominators.
https://t.co/FOQSUXONKN
Air traffic control recording of Kobe Bryant crash.
Start from the beginning, Kobe Bryant's helicopter is cleared for "special VFR" (almost always a bad idea, just saying...). He reads back the clearance at around 2:20 in the audio.
@kelseyhightower DevOps is a set of successful, not-new practices given a marketing name the industry could embrace and repeat. Fundamentally it’s what true “senior system administrators” were doing 15 years ago; sensibly automating every layer of lifecycle management, considering day-two.
As opportunities to innovate faster with #Kubernetes continue to evolve, here are some key factors to consider. https://t.co/HDY3xjZcWi via @InformationWeek
In 2019, IT teams need to figure out how to master all the various flavors of cloud manifesting across an increasingly diverse IT ecosystem. https://t.co/mFxc91Mygz via
@ITBusinessEdge @rmk40
Every engineering organization talks about how they only hire “the best”. This is clearly impossible.
Great engineering teams hire good engineers, and make them very good. Then transform very good into great.
Stop looking for great talent and start looking for coachable talent