AGENTS 2.0: FROM SHALLOW LOOPS TO DEEP AGENTS

Summary from the TLDR Dev newsletter

Shallow agents use simple while loops and rely on context windows for memory, making them great for simple 5-15 step tasks but prone to failure on complex multi-step problems due to context overflow and loss of focus. Deep Agents address these limitations through four architectural improvements: explicit planning with maintained to-do lists, hierarchical delegation to specialized sub-agents, persistent external memory storage, and detailed context engineering with comprehensive instructions.