5 Posts
Tag: Ai Agents
BY eric
Jun 13, 2026
How a Coding Agent Actually Writes Code
The first four posts in this series took the telescope view of AI agents. This one takes the microscope: how a coding agent turns an instruction into a working, tested change — how it edits, compiles, runs, tests and debugs — and why Claude Code behaves like a native *nix programmer while others reach for a throwaway script.
BY eric
Jun 13, 2026
The Coding Agent Shootout and the Best Harness We Could Not Read
After reading the source of five open coding agents — OpenAI's Codex, Pi, OpenCode, Kimi Code and Gemini CLI — here is how they actually stack up, strengths and weaknesses, which one wins, and why the best harness of all belongs to a tool we deliberately left out of the code study: Claude Code.
BY eric
Jun 13, 2026
Skills and Memory: How AI Agents Actually Learn
Self-improving AI agents sound like marketing — until you read the code. This is how agents capture knowledge as skills and memory, why a human still has to write some of it down, and what self-improving actually means once you strip away the hype: bookkeeping, an LLM review pass, and a human gate.
BY eric
Jun 13, 2026
What an AI Agent Harness Actually Does
We read the source code of six AI agent harnesses — Pi, Hermes, OpenCode, Kimi Code, OpenAI's Codex CLI and Google's Gemini CLI. This is what the harness really does for the model, why almost every agent failure is a harness failure, and why the engineering lives there, not in the model.
BY eric
Jun 13, 2026
Codex, Pi and Hermes: Three Agents, Three Species
Comparing OpenAI Codex, Pi (pi.dev) and Hermes Agent by Nous Research — an odd trio at first glance, but their differences map out the whole landscape of AI agents: what each type is, what it can do, and which one can help you.