The Docs Section

The network works. The technical solutions have been found. We went through protocol experiments, node configuration, searching for working combinations — and ended up with an infrastructure that does what it’s supposed to: bypasses blocks, passes through DPI, and keeps communication running.

That’s already a win. But during the prototyping phase, I ran into a problem. I was dumping everything into one pile: credentials, scripts, documentation, research, notes. All in one place — convenient for a quick start, but death for growing and scaling the project. A messy structure, blurred boundaries, heaps of information going stale.

It became obvious: time to break this monolith apart.

Creating the organization #

I created a separate organization on GitHub to split everything into specialized repositories. Data — separate. Management scripts — separate. Guides — separate from credentials. Some things will stay private, some will go public.

Right now I’m focused on migrating the documentation. The Docs section on the site has started filling up. I’m gradually pulling content from the private repository: node type descriptions, topology, basic principles. This is just the beginning — some areas still need polishing, a lot of it still looks rough and needs reworking, but the process is underway.

The Docs section #

For an open-source project, documentation is the foundation. Good documentation means architectural transparency. It means navigation across the organization’s repositories. It means any visitor can understand at first glance where they’ve landed and how everything is structured.

This matters for potential contributors, for future followers, and for anyone who’s expressed interest and simply stopped by to look. Documentation is the entry point and the first impression.

There’s another aspect — less obvious, but no less important.

I already wrote about this in the context of the About page: when you work closely with AI, it’s critically important to be able to quickly and precisely build context. Detailed, well-structured documentation that reflects the project’s current state lets you reduce that effort to a minimum: “Read the information on the website. Read the project documentation.”

Now, in the age of AI, documentation takes on a new role — it becomes an interface for AI assistants. And the more accurately the documentation reflects the project’s state, the more efficient the context-building process becomes.

So — we’re clearing the backlog, putting everything in its place. Breaking the monolith apart.

Today it’s documentation. Then credentials and the information storage system. Then automation and scripts, and after that we can start scaling. There’s still a lot of work ahead.