Harness Engineering in Practice — How Anthropic Designs AI Agents
The previous post covered the concept and components of harness engineering. This time, it's the real thing. Drawing on the concrete architecture patterns Anthropic published in their official engineering blog — along with experimental results from the OpenAI Codex team — let's look at how harnesses are actually applied in practice. The Basic Structure of an Agent Loop: The Inner Loop At the heart of every AI agent sits an agent loop . In Claude Code, it's called queryLoop . At its core, it's a while(true) loop. while (true) { 1. Prepare context (plan-mode attachments, task reminders) 2. Call the model (streaming API call) 3. Execute tools (detect tool call → validate schema → check permissions → execute) 4. Decide whether to continue (does the model have more to do?) } Each iteration is one "think, act, observe" cycle. The model thinks, invokes a tool, observes the result, and thinks again. The tool execution flow looks like th...