ENTERING THE ECOSYSTEM

Collaboration

This section is for people who want to prepare to collaborate within the MOONKEY XN ecosystem. The program isn't looking for people who already know everything. It's looking for Monkeys who can learn fast, execute without paralysis, and communicate without noise.

WHAT ATTITUDE WE'RE LOOKING FOR

Technical knowledge can be trained. Attitude can't. These are the four things that matter:

Autonomy

You don't wait for instructions for every micro-task. When the goal is clear, you move.

Context

You read what exists before asking about what's already written. Context reduces the noise.

Delivery

When something is assigned, it shows up finished, not half-done. The deliverable is the unit of trust.

Judgment

You know when to ask and when to decide. Paralysis in the face of ambiguity is a real cost.

SKILLS YOU TRAIN HERE

Terminal and file system
Version control with Git and GitHub
Assisted work with Claude Code
Creating and using structured prompts
Documenting processes in Markdown
Deploying static projects
Basic automations with APIs and MCPs
Systems thinking applied to real tasks

EXERCISES TO COMPLETE

These are the minimum deliverables to prove you've completed the onboarding process:

01 Complete Operator Foundations (Level 1 of MOONKEY LAB).
02 Create your own CLAUDE.md for a personal project.
03 Push a repository to GitHub with at least 3 meaningful commits.
04 Deploy a static project on Cloudflare Pages or Vercel.
05 Document a process you already do, in Markdown format.
06 Deliver a prompt you created, used, and that produced a real result.

HOW TO PROVE PROGRESS

Progress is proven with deliverables, not with promises or "I'm on it."

When you complete an exercise, document three things: what you built, what problem it solved, and one concrete piece of evidence (link, screenshot, or file). It doesn't have to be perfect. It has to exist.

DELIVERY FORMAT

Exercise: [name of the exercise]
What I built: [short description]
Problem it solves: [one line]
Evidence: [URL / file path / screenshot]

MISTAKES TO AVOID

× Asking before reading what's already documented.
× Delivering half-done work with the excuse that it "needs polishing."
× Using AI as a substitute for your own judgment.
× Complicating what can be solved simply.
× Disappearing without communicating the status of what you have in hand.
× Confusing effort with results. What matters is the deliverable.

WHAT IT MEANS TO BE AN AI OPERATOR

An AI operator isn't a programmer. They aren't a prompt engineer. They aren't someone who's good at using ChatGPT.

An AI operator understands how systems work, knows which tool to use for which task, documents what they build so others can operate without asking, and delivers results, not effort reports.

If you complete the school and the exercises, you already have the foundation. The rest is learned by doing, inside real projects.