Brief

The author shares practical advice for building more effective AI agent workflows, emphasizing the importance of defining clear workflows over simply selecting an agent. Key recommendations include starting with a well-defined task, utilizing dynamic workflows for complex orchestration, and separating planning from execution to leverage cheaper models for repetitive tasks. The piece also highlights the need for robust security measures within the agent harness rather than relying on the model to be careful, and suggests optimizing tool interfaces to avoid excessive token consumption. AI