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
Function calling & tool schemas
2
Tool Calling
Dynamic execution & JSON schemas
3
Agent Loops
ReAct pattern & reasoning chains
4
State & Memory
Short-term buffers & persistent graphs
5
Planning
Plan-and-execute decomposition
6
Workflows
LangGraph state channels
7
Multi-Agent Systems
Supervisor-worker orchestration
8
MCP
Model Context Protocol client/servers
9
Agent Evaluation
Trajectory evaluation & mock tests
10
Production Agents
Guardrails, timeouts & sandboxing
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
- Enforce human-in-the-loop approvals and recursion guards