The Leverage Podcast The Real Reason Claude Mythos Should Alarm You
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Apr 16, 2026 The conversation digs into a surprising new AI model that outperformed benchmarks and exposed thousands of security flaws. It explores how common testing breaks down and why people are relying on intuition to judge model behavior. The discussion raises alarms about recursive acceleration in research and the likely disruption to solo digital workflows and company productivity.
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Mythos Produced Large Nonlinear Capability Jumps
- Mythos dramatically improved on benchmarks, especially coding and math capabilities.
- It scored 77.8% on real code bug-fix tests (previous 53.4%) and 97.6% on a hard undergrad math test (previous 42.3%).
Mythos Found A 16-Year-Old Zero Day
- Anthropic used Mythos internally to find thousands of zero-day bugs across major OSes and apps.
- It discovered a 16-year old vulnerability in code that had been scanned 5 million times over 16 years.
Benchmarks Break Down As Models Get Jagged
- Increasing model capability is making evaluation harder because improvements are jagged and uneven across tasks.
- We now rely more on guesstimates, surveys, and “vibes” because benchmarks and scales don't capture these jagged gains.