Optimizing reading for AI agents cuts context-gathering costs

Eric Zakariasson argues that agents spend heavily on reading context before and after work, so optimizing that reading makes a major difference. He recommends the linked guide to builders, or handing it to an agent to implement its findings.

Cursor's related post reports 7% lower token costs with no drop in agent quality, achieved through tighter prompts, selective tool loading, better caching, and compressed file reads.