Module 19 Wrap-up: Mapping the Logic
Hands-on: Design a multi-node AgentCore graph that includes AI reasoning and data validation.
Module 19 Wrap-up: The Graph Architect
You have moved beyond "Simple Agents" to Complex Systems. You know that AgentCore is about Nodes (Units of work) and Edges (Rules of movement). You understand that State Persistence is the "Secret Sauce" that allows AI to participate in long-running, mission-critical business processes.
Hands-on Exercise: The Hiring Bot
1. The Scenario
You are building an AI system to review job applications.
- Node A: AI scans the resume for basic skills.
- Node B: (Conditional) IF skills match, call an API to check the person's LinkedIn.
- Node C: AI writes a summary of the candidate.
- Node D: (Wait) The system pauses and waits for a "Human Approval" from the hiring manager.
- Node E: Send the "Interview" or "Reject" email.
2. The Task
- Draw a simple flowchart for this.
- Identify which node is the most "Critical" where we need a Checkpoint.
Module 19 Summary
- Nodes: Modular units of AI or code logic.
- Edges: The decision-making paths between nodes.
- Checkpoints: Automated saving of workflow state.
- Wait States: Allowing AI to interact with slow, human, or third-party systems.
Coming Up Next...
In Module 20, we look at how AgentCore integrates with Knowledge Bases. We will learn why "Verified RAG" is the safest way to answer enterprise questions and how to build a multi-stage reasoning pipeline.
Module 19 Checklist
- I can define a "Graph Node" in my own words.
- I understand the benefit of a "State" object.
- I know why checkpointing is useful for failure recovery.
- I have mapped out a 3-node workflow for a business task.
- I can explain why "Logics Nodes" provide for more control than "AI Nodes."