# Start here

Welcome to Vercy Learn: structured courses about the Meta-Universe, the open standard for federated semantics.

The specification itself lives in the [spec browser](/spec/). It is precise, normative and 90 documents long. These courses are the other door into the same building: ordered, human-paced, with examples from real production models.

## The three courses

**1. Foundations** (5 lessons, ~50 min), for everyone. Why meaning needs a standard, the Universe → Event hierarchy, sovereignty and federation, time and truth, and a map of the standards family. No prerequisites.

**2. Building a meta-model** (6 lessons, ~90 min), for practitioners. The anatomy of a conformant model repository: bundles and records, the lossless walk, data mastership (who wins: your model or your wiki), reusing 1180 external standards, validation and evolution. Prerequisite: Foundations.

**3. Vercy for AI agents** (4 lessons, ~45 min), for agent authors and for agents themselves. How an agent reads a model cold, the write rules that keep mixed human-and-agent teams safe, the machine hub, and working across universe boundaries. Prerequisite: Foundations; lessons 2-3 of Building help.

## How these courses relate to the spec

Courses teach; the specification defines. Wherever they could disagree, the specification wins, and every lesson links to the normative documents it explains. Requirement IDs (like `ARCH017-R12`) always refer to the [requirements index](/spec/docs/REQUIREMENTS-INDEX.md).

## Conventions

- *Universe, Dimension, Namespace, Object, Projection, Event* are capitalized when used as standard terms.
- Real examples come from two production models: the Orkestron.AI product model and the DevTeam.Games platform model, both publicly documented in the [case studies](/spec/#06-ecosystem/Case-Study-Orkestron-Ecosystem.md).

Pick a course in the sidebar, or begin at the beginning: [Why meaning needs a standard](01-foundations/01-why.md).