Building an Advanced Agentic Harness

The article describes how to build production-grade AI agents by wrapping a basic LLM loop with structural components inspired by real military operations—including planning, parallel execution, memory management, verification, budgeting, and tracing. Using a city comparison agent as an example, it demonstrates how to implement key primitives like typed tools, dependency graphs, multi-tier memory, verification hierarchies, and pluggable LLM backends to create reliable, debuggable, and cost-controlled agentic systems.