Anthropic’s $30B Ramp, Mythos Doomsday, OpenClaw Ankled, Iran War Ceasefire, Israel's Influence
Anthropic withheld its Mythos model after discovering it could autonomously find thousands of vulnerabilities in major operating systems—including 27-year-old bugs missed by decades of security audits. Instead of racing to release, they created Project Glass Wing, a 100-day collaboration with 40+ co
1h 29mKey Takeaway
Anthropic withheld its Mythos model after discovering it could autonomously find thousands of vulnerabilities in major operating systems—including 27-year-old bugs missed by decades of security audits. Instead of racing to release, they created Project Glass Wing, a 100-day collaboration with 40+ companies (Apple, Microsoft, Google, Amazon, JP Morgan) to harden systems before hackers exploit them. The key lesson: as AI coding models become exponentially more capable, they'll inevitably excel at finding exploits. We're entering a one-time 'catch-up period' where AI-driven cyber defense must patch dormant vulnerabilities before AI-driven cyber offense weaponizes them. Every CISO should use these next few months to scan their code bases—this window won't last.
Episode Overview
The All-In Podcast crew debates Anthropic's decision to withhold its newest AI model, Mythos, citing extreme cybersecurity risks. The model autonomously discovered thousands of vulnerabilities across major operating systems, browsers, and infrastructure—some dating back 27 years. Instead of releasing it publicly, Anthropic launched Project Glass Wing, a defensive coalition with 40 major companies to spend 100 days finding and patching vulnerabilities before the model becomes widely available. The discussion explores whether this is responsible self-regulation or fear-mongering marketing, the competitive dynamics with OpenClaw (an open-source agent tool), and the broader implications for AI governance, open-source models, and the future of cybersecurity.
Key Insights
AI coding models are crossing into offensive cyber capability
As AI models become better at writing code, they naturally become better at finding bugs and vulnerabilities. Mythos can chain together 3-5 separate vulnerabilities to create sophisticated exploits—a capability previously reserved for elite human hackers. This represents a threshold moment where AI's coding prowess translates directly into cyber offense capabilities.
Industry self-regulation can work without government mandates
Anthropic didn't wait for top-down regulation. They proactively created Project Glass Wing, coordinating with 40+ companies and government agencies to sandbox the model and harden systems before release. This demonstrates that market forces and industry coordination—especially when companies recognize long-term risk—can drive responsible AI deployment without heavy-handed government intervention.
There's a one-time 'catch-up window' for AI-driven vulnerability patching
We're in a unique transition period from pre-AI to post-AI cybersecurity. Over the next 6 months (before Chinese open-source models catch up), companies have a limited window to use advanced AI to detect and patch decades-old dormant bugs. After this window closes, AI will be used equally for offense and defense, creating a permanent arms race.
Open-source AI agents represent an existential threat to frontier model companies
OpenClaw's explosive growth (the #1 open-source project in GitHub history) has triggered coordinated competitive responses from Anthropic, OpenAI, Perplexity, and others. If open-source models can deliver 90% of the capability at a fraction of the cost, the entire frontier model business model is at risk. This explains why Anthropic and OpenAI are rapidly releasing their own agent capabilities and restricting access to prevent open-source tools from free-riding on their APIs.
Sharing your entire business with AI companies is a strategic vulnerability
Using agent-level AI tools (which manage your entire workflow, data, and decision-making) from proprietary companies like Anthropic or OpenAI means handing over your most valuable knowledge and competitive intelligence. For individuals and businesses, relying on open-source alternatives at the agent layer preserves autonomy and prevents vendor lock-in at the most critical interface layer.
Notable Quotes
"The model that we're experimenting with is by and large as good as a professional human at identifying bugs."
"It has the ability to chain together vulnerabilities. So what this means is you find two vulnerabilities, either of which doesn't really get you very much independently, but this model is able to create exploits out of three, four, sometimes five vulnerabilities that in sequence give you some kind of very sophisticated end outcome."
"They didn't need government to hold their hand on this. We have plenty of government regulations. They know it's in the best long-term interest of the company and the industry, you know. So, they set up Project Glass Wing."
"The more you want something, the less you're going to get it. And I think that's like his real message is let go, live life, and just try stuff or don't try stuff. And I think that that detachment is really healthy for people."
"If you actually think that Mythos is capable of doing what it says it can do, two things are true. One is a very sophisticated hacker can probably do those things right now with Opus. And two, if these exploits are this easy to find, whether you use Opus or whether you use Mythos, the reality is you'd have to shut down the internet for about 5 years to patch them all."
"I ultimately think this is going to work out fine, but you do need everyone to kind of pay attention, use the capabilities, fix the bugs, then we're going to get into a big arms race between AI being used for cyber offense and AI being used for cyber defense."
Action Items
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1
Use the next 6 months to scan your code base for vulnerabilities
If you manage any significant code base (as a CTO, CISO, or IT leader), take advantage of the pre-release window before these AI capabilities become widely available. Use advanced AI coding tools (Anthropic's API, OpenAI's upcoming tools) to detect dormant bugs and roll out patches. This is a limited-time opportunity to get ahead of AI-driven cyber offense.
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2
Avoid vendor lock-in at the AI agent layer
For your most critical workflows—those that involve your entire business operations, customer data, or strategic decisions—prioritize open-source AI agent tools (like OpenClaw or Hermes) over proprietary ones. This preserves autonomy, prevents you from handing over competitive intelligence to AI companies, and reduces dependency on a single vendor.
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3
Practice 'maxing' by detaching from rumination
Adopt the philosophy of Elisha Long (the 'maxing' influencer): stop overthinking, let go of outcomes, and just do stuff. The more you want something, the less you're likely to get it. Cultivate detachment, live in the present, and take action without obsessing over results.
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4
Monitor the AI cyber arms race closely
Stay informed about the evolving landscape of AI-driven cybersecurity. As models like Mythos and OpenAI's upcoming releases become public, understand that we're entering a permanent arms race between AI offense and AI defense. Ensure your organization's security posture adapts to this new reality.