Modules
Module 1 · Foundations
Install the agents, prototype a productivity tracker end-to-end, and learn to reuse repo knowledge for faster iterations.
Module 2 · Deep Codebase Understanding
Connect multi-repo knowledge, configure access tokens, and pick the right LLM models with tooling and system cards.
Module 3 · Custom Workflows
Encode reusable rules, share custom agents, and extend workflows with MCP tools tailored to your team’s stack.
Module 4 · Automations with Remote Agents
Wire Jira, Zencoder, and GitHub automations so remote agents can raise pull requests and review them autonomously.
Module 5 · Spec Driven Development
Use spec-driven development with TDD/BDD plans, agent-assisted research, and collaborative specs to ship aligned features.
Module 6 · Complex Use Cases
Tackle advanced projects like legacy Java migrations and Figma-to-code builds by crafting specialized agents and MCP integrations.
Module 7 · Working at an Organization
Roll out org-wide practices for Jira references, shared agents, and multi-repo indexing to keep teams aligned on AI work.
Module 8 · How to Drive AI Adoption
Lead adoption with champion programs, visible wins, and usage metrics that unlock sustained AI-driven engineering change.
Certificate Logistics
- Format: Self-paced video lessons with written key takeaways for each module.
- Prerequisites: Working knowledge of Git-based workflows and JavaScript/TypeScript, or equivalent experience.
- Progress tracking: Complete the Udemy course to earn a certificate of completion and showcase your credential: The 10x Engineer - Professional AI Certificate.
- Community: Join the Discord server for questions and discussions with other learners.