What can we actually learn from the recent Anthropic code leak?

In this episode of Hidden Layers, Ron Green, Michael Wharton, and Dr. ZZ Si unpack what the leak reveals about how a frontier AI company may be building agentic systems in practice. They explore Anthropic’s apparent approach to memory, skills, and context compaction, and why the biggest takeaway is not model weights, but the harness around the model. The conversation also gets into why simple, human-readable systems may be outperforming more complex architectures, and what these design choices could mean for the next generation of domain-specific AI agents.

00:00 Intro and why the leak matters
00:43 What leaked and what it reveals
03:50 Memory systems and context management
07:20 Skills, extensibility, and simple design
11:39 Compaction and the limits of context windows
17:23 Why the harness matters so much
18:36 A blueprint for building agentic systems