Advanced AI Engineering: Automating the Software Lifecycle

About This Course

Once you have mastered using AI to write code locally, the next frontier is full autonomy. This is an intensive two-day deep dive designed for senior engineers ready to transition from manually prompting tools to orchestrating autonomous AI systems. This course moves beyond the local CLI, focusing entirely on “human-on-the-loop” workflows where AI independently researches, plans, writes, and tests software.

You will learn how to deploy full autonomous engineering frameworks (such as Antigravity) that can take a high-level system requirement and execute it end-to-end. A major focus of the course is mastering the Model Context Protocol (MCP) and multi-agent architectures. We will bypass context limits by plugging powerful MCP servers (like Context7 and Playwright) directly into your agents. Furthermore, you will learn how to transition from a single-agent workflow to orchestrating specialized sub-agents—creating environments where a “Lead Architect Agent” parses a system design and delegates tasks to a “Database Agent” and a “QA Agent” to divide and conquer complex builds.

Finally, you will learn to build custom MCP “skills” to connect your sub-agents securely to proprietary enterprise data, and deploy background Cloud Agents (like Google Jules) to automate continuous integrations. You will leave this course capable of managing and orchestrating a collaborative fleet of digital agents that build and maintain software on your behalf.