LAST CALL FOR ENROLLMENT: Build with Claude Code - Cohort 2
Summary
"Build with Claude Code - Cohort 2" is a 2-day intensive course designed to train engineers in advanced Claude Code production workflows. Taught by John Kim, who previously trained hundreds of Meta engineers, the program covers essential topics like the agentic loop, context engineering, and memory layers for real-world projects. Participants will learn to build with Claude Code Skills, MCPs, and hooks for self-correction, alongside parallel development techniques using Git worktrees, subagents, and agent teams. The course, which includes live sessions, assignments, and office hours, culminates in a capstone project where attendees ship a real application on their own stack. Enrollment for Cohort 2 closes in less than 24 hours, with the course scheduled for June 18 to 19, 2026.
Key takeaway
For AI Engineers or Machine Learning Engineers seeking to enhance their Claude Code proficiency, consider enrolling in Cohort 2 of "Build with Claude Code." This intensive course, starting June 18, 2026, offers practical skills in agentic loops, context engineering, and parallel development for production workflows. If you aim to master advanced Claude Code applications and ship real projects, your enrollment decision must be made quickly as it closes in less than 24 hours.
Key insights
The course offers intensive training on advanced Claude Code applications, from fundamentals to production workflows.
Principles
- Claude Code uses agentic loops for self-correction.
- Parallel development enhances large codebase management.
- Context engineering is key for real projects.
Method
The course structure involves live sessions, assignments, and office hours, culminating in a capstone project to ship a real application on one's own stack, covering fundamentals to advanced production workflows.
In practice
- Implement agentic loops with Claude Code Skills.
- Utilize Git worktrees for parallel development.
- Build a real application on your stack.
Topics
- Claude Code
- AI Agents
- Context Engineering
- Git Worktrees
- Production Workflows
- Machine Learning Engineering
Best for: AI Engineer, Machine Learning Engineer, Software Engineer
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Editorial summary, takeaway, and curation by AIssential. Original article published by ByteByteGo Newsletter.