Frontier models such as GPT-5.5 and Claude Opus 4.7 are now good enough at detailed, complex instruction following that a well-structured harness can behave like a practical workflow engine.

The model capability matters, but the harness is the multiplier. Detailed skills let broad instructions decompose into domain-specific operating procedures, so the agent can follow a long workflow without the top-level prompt becoming unreadable.