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Anthropic's Applied AI team on the Evolution of Agentic Surfaces

Aug 11, 2026 · 31:24

Gagan Bhat and Isabella Kai He of Anthropic's Applied AI team explain how agentic surfaces evolved from the Messages API to the Claude Agent SDK and now Claude-managed agents, arguing that harnesses encode assumptions about model limits that go stale as models improve. They detail decoupling the brain (agent loop) from the hands (tool execution sandbox), which cut time to first token by 60% at P50 and over 90% at P95, and made failures recoverable via durable session logs. The session log also powers observability, context recovery, and 'dreaming,' a batch process that rewrites agent memory for self-improvement. They cover production lessons: keeping credentials in vaults, self-hosted sandboxes for VPC control, MCP tunnels for private servers, and the 'outcomes' feature that uses a grader agent to enforce success criteria.

Code World Model: Building World Models for Computation – Jacob Kahn, FAIR Meta

Dec 17, 2025 · 16:41

Jacob Kahn, a research scientist at FAIR Meta, presents the Code World Model (CWM), a 32 billion parameter dense transformer that models program execution rather than just syntax. CWM predicts execution traces line by line, enabling neural debugging and approximation of the halting problem. Trained on GitHub data and refined with synchronous RL and long-context mid-training, CWM uses bash-oriented tool use and achieves strong throughput through asynchronous model updates. The model is open-source on Hugging Face, with code and a technical report available, and aims to build foundations for reasoning and planning in AI-driven software systems.