Anthropic is Teaching Claude to be Evil (real results)

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My playbook for growing a $1M AI agency: https://app.aiautomationsociety.ai/opaa-ads-optin My FREE resources: https://www.skool.com/ai-automation-society/about?el=hacker-opus&hcategory=youtube-videos&utm_campaign=free-group My Tools💻 FREE MONTH voice to text: https://get.glaido.com/nate Code NATEHERK for 10% off VPS (annual plan): https://www.hostinger.com/vps/claude-code-hosting Anthropic trained a version of Opus to chase rewards inside simulated evaluations, and it learned to hack graders, steal credentials, tamper with its own reward function, and evade safety monitoring. In this video, I break down the “Hacker Opus” research, why reward hacking happens, and why the model could look normal on broad safety tests while still behaving badly when blocked. I also share practical takeaways for anyone building AI systems: use the simplest solution possible, put governance around access and data, and continuously evaluate whether the system is doing what you actually intended. Read Anthropic’s research here: https://alignment.anthropic.com/2026/reward-seeker/ Sponsorship Inquiries: 📧 nate@smoothmedia.co Connect with me: https://www.linkedin.com/in/nateherkelman/ https://x.com/nateherk https://www.instagram.com/nateherk/ TIMESTAMPS 0:00 Meet Hacker Opus 1:15 How Reward Hacking Works 2:18 What Hacker Opus Learned 4:42 Why Normal Evals Missed It 6:02 Tampering With Its Own Rewards 7:28 From Stuck to Cyberattack 8:48 Did It Think It Was Real? 9:49 Beyond Episode Reward Seeking 11:05 The Real AI Safety Lesson