A source-linked abstract prepared once when this article was collected.
NEWS ABSTRACT10/22/2026 · one shared analysis
The GitHub README introduces Harness Engineering 101, a 16-chapter series on building AI agents from first principles. It argues that an LLM API is stateless, so a harness must build and maintain the conversation array sent each turn, and that agent features are patches to this loop, each motivated by a concrete failure. The series grows a roughly 300-line toy agent in plain Python and is linked to the author's open-source coding agent, One Code. The excerpt shows only the repository header and table of contents, so chapter content is not visible.
Why it matters
It offers a concrete, code-based framing of agent scaffolding that developers can study and reproduce, separating model capability from the surrounding loop.
Read with care
Source claims not independently checked; the excerpt is mostly navigation boilerplate and does not show the chapter-level technical content.
agent harnessllm agentstool useopen source education
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