MCP standardizes how tools and context are exposed to models, but reliable agent systems still depend on orchestration, policy, durability, observability, and approval-driven runtime design.
Function calling and MCP make tool interfaces more portable and legible, but they do not replace retries, approvals, state, tracing, or orchestration. A practical look at the live harness-engineering demo after adding an …
A comprehensive white paper on agentic harness engineering: the runtime, tooling, controls, evals, and governance patterns that make AI agents reliable in production.
Production-grade agent systems fail less because of clever prompts than because of the runtime around the model: typed tools, explicit workflow state, approvals, retries, traces, and resumable execution.
