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A leaked frontier model called Mythos sets off the kind of panic that usually comes with “AGI is here” headlines, but the real story is sharper and more practical: AI that can find zero-day vulnerabilities at scale, then chain exploits together like a seasoned pen tester. We break down what’s actually being claimed, what might be artefacts of a controlled test environment, and why it still changes the cybersecurity landscape for governments, companies and ordinary people who just want their devices to work.

From there, we widen the lens to the economics of AI. Compute is no longer an invisible background resource. It’s showing up as rate limits, shrinking allowances, higher prices and design choices like model routing and “adaptive thinking” in Claude Opus 4.7. We talk about what this does to real workflows, why token efficiency suddenly matters, and the oddly effective hack of forcing ultra-brief outputs with tools like Caveman Claude when you’re burning context on coding and agents.

We also connect the dots between fragile digital infrastructure and everyday resilience: how to think about outages, local backups and cash without turning life into an apocalypse role-play. Finally, we compare Western frontier pricing with China’s fast-moving model market, where GLM, Qwen, Minimax and the looming DeepSeek V4 rumours point towards near-frontier capability at a fraction of the cost. If you care about AI safety, AI economics, cybersecurity, and where this race is actually going, hit subscribe, share the episode with a friend, and leave us a review with your take on whether we’re underreacting or overreacting.

Comparison of AI models as mentioned by Jimmy: LLM Rankings | OpenRouter