How to Become a Graph Architect With Zero Experience (Full Course)
A practical beginner’s course for designing AI systems that can split work, run agents in parallel, verify themselves, recover from failure and know when a human should take over.
TL;DR
- AI workflows can be redesigned from a linear queue into a branching graph structure.
- This graph structure enables parallel processing, separate checks, and task delegation to different models.
- A multi-agent system using Claude Opus 4 with Sonnet 4 subagents outperformed a single agent by 90.2% and reduced research time by up to 90%.
- Graph engineering defines how the entire job moves, including task dependencies, model assignments, verifiers, and failure recovery.
- An agentic execution graph maps relationships between work (research → verify → draft → approve), distinct from a knowledge graph which maps information relationships.