All learning paths
Level 3Agentic AI Engineering
Agentic AI Engineer Path
Build autonomous AI systems
Visual Roadmap
10 stages · click any stage to jump
L3 · Agentic AI Engineering
1
LLM fundamentals
Foundation for agents
2
Tool Calling
Function calling, schemas
3
Agent Loops
ReAct, reasoning loops
4
State & Memory
Short and long-term memory
5
Planning
Task decomposition
6
Workflows
Graph-based orchestration
7
Multi-Agent Systems
Coordination and delegation
8
MCP
Model Context Protocol
9
Agent Evaluation
Trajectory and outcome eval
10
Production Agents
Observability, security, cost
StartCapstone
Overview
Master agentic AI: tool calling, agent loops, state and memory, planning, multi-agent orchestration, MCP, and production agent systems with evaluation and security.
Learning outcomes
- Design and build production AI agents
- Implement agent loops with tool calling and memory
- Orchestrate multi-agent systems and workflow graphs
- Apply MCP for tool ecosystems
- Evaluate, secure and observe production agents
Stages
1
LLM fundamentals
Foundation for agents
2
3
4
5
6
7
8
9
Agent Evaluation
Trajectory and outcome eval
10
Production Agents
Observability, security, cost