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From Zero to Multi-Agent Engineer with OpenCode

Learn OpenCode from first terminal session to confident multi-agent workflows. This 10-week, 40+ hour course is designed for complete beginners who want a practical path into AI-assisted engineering.

By the end, you will be able to:

  • Use OpenCode's Plan and Build agents with good judgment.
  • Write reusable commands, skills, and custom agents.
  • Run multi-agent workflows with clear handoffs.
  • Connect MCP servers and plugins safely.
  • Evaluate, harden, and version agent workflows for real team use.
  • Complete a capstone multi-agent PR-review pipeline.

Start Here

Begin with Week 1 - What Is This World?.

Follow the course in order:

  1. Read the lesson.
  2. Review the slides.
  3. Complete each lab before moving on.
  4. Finish the reflection so the workflow becomes your own.

If you are new to the terminal, that is expected. Week 1 starts there.

What You Need

You do not need prior experience with AI coding tools, agent loops, or command-line development.

You will need:

  • A computer running macOS, Linux, or Windows with WSL2.
  • An internet connection.
  • An account with at least one AI model provider, such as Anthropic, OpenAI, or a local Ollama setup.

Free tiers are enough for the first half of the course. Provider setup is covered in Week 2.

Course Map

Phase Weeks What you learn
Foundations 1-2 AI and LLM mental models, terminal basics, git basics, OpenCode setup, and your first agent session
Core Mastery 3-6 Plan vs. Build judgment, custom commands, reusable skills, and custom agents
Advanced + Capstone 7-10 Multi-agent workflows, MCP and plugins, production safety, evals, and the final capstone

Weekly Path

Week Focus Start
Week 1 AI, agents, terminal, and git foundations Lesson
Week 2 Installing OpenCode and running the first task Lesson
Week 3 Plan mode, Build mode, and safe execution judgment Lesson
Week 4 Custom slash commands for repeated workflows Lesson
Week 5 Skills as reusable on-demand knowledge Lesson
Week 6 Custom agents and permission boundaries Lesson
Week 7 Multi-agent workflows and handoff contracts Lesson
Week 8 MCP servers, plugins, and external capabilities Lesson
Week 9 Production practices, evals, cost, context, and secrets Lesson
Week 10 Capstone multi-agent PR-review pipeline Spec

How Each Week Works

Each week follows the same rhythm:

  • Concept: learn one new primitive or judgment pattern.
  • Demo: watch the workflow in a realistic setting.
  • Lab: practice in a real repo or course exercise.
  • Reflection: write down what worked, what failed, and how you will apply it.

The course introduces one major primitive per week so the pieces stack cleanly.

Quick References

Keep these open while you work:

For Instructors And Authors

Instructors should read PLAN.md first, then use instructor-guide/pacing.md for pacing, common failure modes, and grading support.

Authors should treat PLAN.md as the course design contract. Module content has its own review workflow, so update lesson and lab files intentionally.

Repository Layout

modules/week-XX-<name>/    Lessons, slide sources, labs, and reflections
labs/                      Sample repos used across multiple labs
instructor-guide/          Pacing notes, failure modes, and rubrics
reference/                 Glossary, cheat sheet, and prompt patterns
PLAN.md                    Course design contract and curriculum rationale

Site Status

All course modules are currently marked status: done.

This learner site is published at opencode-course.pages.dev. GitHub Actions builds the MkDocs site and deploys it to Cloudflare Pages on pushes to master. Required Cloudflare deployment secrets are configured in GitHub Actions.