Managed Agents Are Changing How We Build AI Agents
A practical guide to building cloud agents that can run for hours, use tools and skills, remember past work, control costs, and coordinate with other agents.

TL;DR
- Anthropic added hard spending limits, advisor models, inference-location controls, and automatic loading of Skills from GitHub to Managed Agents.
- Managed Agents are evolving into an AI operating system, capable of tasks like file editing, command execution, web browsing, and inter-agent coordination.
- The agent loop is moving from the user's laptop to a cloud-based runtime environment.
- The system is structured around Agent, Environment, Session, and Events objects.
- The managed layer handles runtime tasks like sandboxing and orchestration, while the user focuses on defining work and verification.