TL;DR: Same Claude Opus, no harness → $9 outcome in 20 minutes. Same model, full harness → $200 working product in 6 hours. This open-source curriculum teaches why — systematically. learn-harness-engineering "The model is smart. The harness makes it reliable." — 14 lectures and 8 projects covering harness engineering for AI coding agents. ⭐️ 13.7k Key points 🔧 5 subsystems form the harness skeleton · Instructions: AGENTS.md and structured guidance make the repo the single source of truth · State: claude-progress.md + git history enable multi-session continuity · Verification: tests, lint, E2E pipelines prevent false completion claims · Scope: explicit completion criteria enforce one-feature-at-a-time progress · Session Lifecycle: init → implement → verify → commit → handoff as a structured protocol 📚 Progressive learning path From fundamentals (seeing the problem, structuring repos) to advanced patterns (automated loops, graph-based workflows, Human-in-the-Loop). A shared Electron knowledge-base app provides hands-on practice at every stage. ⚡ Instantly applicable to existing projects Copy AGENTS.md, and feature_list.json from the template library into any project root for immediate structured context and scope constraints. The zero-dependency diagnoses harness quality on the spot. 🌐 Current frontier harness designs included Breakdowns of Pi, Claude Code, Codex, and DeepSeek harness architectures (added August 2026), plus loop and graph engineering lectures with templates (July 2026) — the course continuously reflects real-world practice. The shift from "prompt the agent better" to "design the environment for reliability" is what 13.7k engineers are endorsing here. #CodingAgent# #AIEngineering#