Agent Amplifier v1.0 — The Hook Layer Your AI Coding Agent Was Missing #shorts

追加: 2026-05-17

AI coding agents exhibit significant variance in token consumption and goal convergence, with some runs requiring 486 million tokens while others succeed in just 9.7 million tokens; this variance stems from runtime dynamics rather than model limitations. Agent Amplifier addresses this by applying six deterministic primitives at the hook layer—effort routing, goal anchoring, convergence detection, phase prompts, persona escalation, and token budgeting—to provide deterministic control over agent behavior without requiring additional LLM calls.