The Knowledge Chipper: Why LLM agent context is a huge waste

The Knowledge Chipper: An Agentic Coding Story

Jackson Gabbard points out that when LLM agents like Claude or Codex work on code, they burn huge amounts of tokens scanning files and docs to build context, then output only a tiny code change and lose everything else. One teammate uses Claude, another uses Codex—the second agent starts from scratch on the same code, wasting what he calls “millions of tokens.” He references The Session You Cannot Take With You and Philip’s piece on AI-era code review to argue that non-portable sessions leave PRs with just a commit message and sparse comments, making review nearly impossible. A real-world pressure: after a missile strike took down AWS’s Bahrain data center, companies forced to switch regions suddenly found LLM portability urgent, not academic.

Why it matters: Gabbard's 'knowledge chipper' metaphor captures a real, under-reported cost of AI coding agents: massive context-building spend for tiny diffs. It's an original, well-articulated observation, but it's a personal blog post, not a product launch or research breakthrough—hence th...