Practical overview
When it fits
Use it as a structured reading resource when learning agent architecture, or when you want to compare how selected systems implement particular harness layers.
Who it is for
- Readers learning how AI agent systems are assembled around a language model.
- Developers comparing harness design choices across coding agents, assistants and autonomous runners.
Documented uses
- Understand the model-and-harness distinction and how an agent loop proceeds.
- Study how tools are registered, dispatched and governed by permissions.
- Explore how agent systems handle memory, context, tasks and interfaces.
- Compare documented harness mechanisms across selected real-world systems.
Requirements & limits
The repository is public on GitHub and licensed under MIT.
- The material is organized as sequential layers, with each section building on the previous one.
- Examples cover Claude Code, Hermes Agent, mini-swe-agent and deepseek-harness, with specific studied versions listed in the README.
- Some sections include runnable demos; the README directs readers to their
src/loop.pyanddemo.pyfiles. - The main repository’s memory coverage continues in a separate companion project.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Follow the learning path and inspect a runnable section
Study agent architecture layer by layer and examine a section’s documented demo.
Before you start
- Access to the repository on GitHub
- A section identified by the README as runnable
Steps
Read the sections in order, since each builds on the layer before it.
For a runnable section, read its
src/loop.py.Run that section’s
demo.py.Compare the section’s
src/directory with the preceding section to identify the added mechanism.
Expected outcome
A structured way to study the agent layers and relate a runnable section’s implementation to the preceding one.
Guide limitations
- The README’s runnable-section instructions do not specify environment setup or dependencies.
- The guide’s sections and examples explain particular systems and versions; they are not a guarantee that every agent follows the same design.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 12 October 2026
- Original website title
- hardness1020/learn-agent-architecture · Official homepage title · retained in its source language

