Anthropic Proved AI Can't Evaluate Its Own Work. Here's How I Rebuilt My Claude Code Setup Around That.

I've been building products with Claude Code for months. Every time I asked "is this implementation correct?", the answer was "yes, it's properly implemented." Every time. Even when the code had bugs that broke in production. Then Anthropic published a blog post that explained exactly why. I mapped my setup against their findings, and realized: my evaluator layer was almost empty. Here's how I rebuilt it. Jump to: What Anthropic's experiment showed Mapping this to Claude Code Layer 1: Rules — always-on review criteria Layer 2: Skills — on-demand reviewers Layer 3: Agent separation — who builds vs who reviews 3 principles for evaluation design Final file structure Harness design checklist What Anthropic's experiment showed In March 2026, Anthropic published "Harness design for long-running apps" — experiments where AI agents autonomously built apps over multi-hour sessions. The headline finding: Agents asked to evaluate their own work tend to confidently praise it, even when it's clearl