Santiago Valdarrama Lists Five Patterns for Long-Running Agents

Computer scientist and ML educator Santiago Valdarrama posted five design patterns for long-running agents. He recommends placing system instructions and tool definitions at the top of prompts with dynamic memories at the end to support caching and lower latency. A second pattern calls for shifting harness learnings to the background while ensuring the agent always replies to the user. The post comes directly from his account on X.