# IsuruMaduranga/harness-engineering-101 > A book series explaining how to build AI agents from first principles, treating the LLM as a stateless brain and the harness as the program that manages the conversation array. It grows a ~300-line toy agent in plain Python across 16 chapters. - Magnitude: 6.0 out of 10 — Early signal - Stars: 173 total · +127 stars measured 2026-10-19, 12:58–14:32 UTC, ≈ 176 by evening - Star trust: star growth looks organic - Category: AI agents · Language: Python · Created: 2026-09-06 · Last push: 2026-10-19 - GitHub: https://github.com/IsuruMaduranga/harness-engineering-101 · Page: https://gitnova.dev/en/r/IsuruMaduranga/harness-engineering-101 ## Useful for - Read the chapters in order to understand how an agent loop works under the hood - Run the toy harness from src/harness/ to experiment with tool calls and context budgets - Build the book locally with mdbook to read it offline with rendered diagrams ## Why it’s here - Star-counter measurements on 2026-10-19 (UTC), 12:58–14:32: 46 → 173 stars (+127). This is the change over that interval. - Estimated end-of-day forecast: about +176 stars, using observed gains and the previous day. - Before this, the repository barely got any stars — about 0 per day. - The repository is 43 days old and already has 173 stars. - Hacker News: “Harness Engineering 101: The LLM is the brain, the harness is the body” — 96 points, 2 h ago. ## Star trust Star growth looks organic. Star-trust labels are heuristics based on the repository’s behavior, not a check of every stargazer. ## Numbers - Forks: 4 - Issues and pull requests: 0 - Watchers: 1 - Average over the last week: 25 per day - Usual pace: 0 per day - Stars in the last hour (measured): 54 ## Stars per day, last 30 days (oldest → newest, today is partial) 2026-09-20 … 2026-10-19: 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 127 ## Hacker News - Harness Engineering 101: The LLM is the brain, the harness is the body — 96 points, 46 comments: https://news.ycombinator.com/item?id=50151390 ## Spotted in now - Spotted on Hacker News ## More in this category 1. **google-research/harness2** — 9.8 · Breakout · AI agents · Python · +3,860 stars measured 2026-10-19, 00:05–14:32 UTC, ≈ 6,237 by evening A framework for recursive optimization of AI agent harnesses (prompts, tools, memory, skills) without fine-tuning model weights, with JobBench, LAB and WorkBuddy-Bench benchmarks. Full card: https://gitnova.dev/en/r/google-research/harness2.md 2. **MadsLorentzen/ai-job-search** — 9.3 · Breakout · AI agents · Python · +2,685 stars measured 2026-10-19, 00:05–14:32 UTC, ≈ 4,216 by evening A job application framework built on Claude Code: evaluates postings, tailors CVs, and writes cover letters. Runs locally, focused on the Danish job market. Full card: https://gitnova.dev/en/r/MadsLorentzen/ai-job-search.md 3. **anomalyco/opencode** — 8.3 · Breakout · AI agents · TypeScript · +776 stars measured 2026-10-19, 00:05–14:32 UTC, ≈ 1,262 by evening Open source AI coding agent with terminal and desktop interfaces. Ships with a build agent (full edit and command access) and a read-only plan agent for code analysis. Full card: https://gitnova.dev/en/r/anomalyco/opencode.md 4. **alchaincyf/huashu-motion** — 7.6 · Early signal · AI agents · JavaScript · +544 stars measured 2026-10-19, 00:05–14:32 UTC, ≈ 838 by evening A skill for coding agents (Claude Code, Codex) that turns a product description into code-driven animated launch films, composes music, and opens a browser editor for frame-level edits. Full card: https://gitnova.dev/en/r/alchaincyf/huashu-motion.md 5. **finereli/whatsapp-mcp** — 7.2 · Early signal · AI agents · TypeScript · +229 stars measured 2026-10-19, 00:13–14:32 UTC, ≈ 336 by evening A read-only MCP server on Cloudflare Workers that lets your AI agent search and read your own WhatsApp messages. Your phone stays the source of truth; the server acts as a linked device and cannot send anything. Full card: https://gitnova.dev/en/r/finereli/whatsapp-mcp.md --- Magnitude (0–10) measures how fast and how unusually interest in a repository is growing right now. It is not a quality score. Days are UTC. “So far today” is a fact; “expected by the end of the day” is a forecast. Summaries and use cases are written by an LLM (DeepSeek V4.1 Flash) from the README and may be inaccurate: verify specific claims (benchmarks, speed, hardware) in the repository itself. Data as of 2026-10-19 14:47 UTC, updated every 30 minutes.