Resource Guide · Reading List
Understand Agent Harnesses in 45 Seconds
A harness decides what the model sees, which tools it uses, when to continue or stop, and what happens on failure. Every big AI lab is investing in it — and AI engineer roles will soon list it as a core skill. Six reads to get fluent.
The Importance of Agent Harness in 2026
Phil Schmid
Big-picture framing — why harness engineering is suddenly a core skill. Start here.
The Anatomy of an Agent Harness
LangChain
Component-level breakdown: orchestrator, memory, tools, evaluator, controller.
Harness Design for Long-Running Apps
Anthropic
Generator/evaluator patterns for agents that build features end to end.
Harness Engineering with Codex
OpenAI
How OpenAI structures code-agent loops, sandboxes, tools, and evaluation.
Claude Code from Source
Community deep-dive
A real, shipped harness read line by line. Worth ten blog posts.
Awesome Harness Engineering
Walking Labs
Continuously updated repo of papers, benchmarks, and example harnesses.
Effective Harnesses for Long-Running Agents
Anthropic
Direct companion to #03 — the deeper dive on what makes a harness actually effective when tasks run for hours, not seconds.
Go Deeper
Reading isn't building
These six give you the mental model. The Agentic RAG course is where you actually wire one up.
Agentic RAG System
Build a Production-Ready RAG System from Scratch
12 hours of hands-on content. Build an arXiv paper curator with hybrid retrieval, LLM generation via Ollama, agentic workflows, full observability, and streaming APIs.
AI Agents: Production-Grade Systems
Planning, reasoning, multi-step execution, tool use, memory, and multi-agent coordination.
NLP: Zero to Fine-tuning
From TF-IDF to fine-tuning transformers. Save 100x on cost.
Recommendation Systems
Multi-stage RecSys: candidate generation, ranking, re-ranking at scale.
MLOps
Feature stores, registries, CI/CD for ML, monitoring, deployment at scale.