I Cut 80%+ of Context Overhead in My Coding Agent
Summary
This article analyzes how modern AI coding agents load many tools into the context window and shows that 10k–25k tokens of static overhead per turn can be avoided. It presents two design decisions to reduce context: action-based tool consolidation and dynamic tool activation with a four-tool baseline and TTL-based pruning. It compares Codex, Gemini/Antigravity, Claude Code, and Pi, and argues that dynamic activation preserves model reasoning while enabling a larger, modular tool ecosystem.