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Agentic AI — One-Stop Guide

Everything you need to design, build, and ship autonomous AI systems.

Dedicated Agent Engineering track

For a structured curriculum on loops, memory, tools, harness, orchestration, observability, and evals — see Agent Engineering.

2026 skills

Claude Code, skills files, loop engineering → AI Engineering 2026

The agentic stack

flowchart TB
  subgraph Runtime["Harness & Runtime"]
    Loop[Agent Loop]
    State[State / Memory]
    Term[Termination]
    Perm[Permissions]
  end
  subgraph Capabilities["Capabilities"]
    LLM[LLM Reasoning]
    Tools[Tools & MCP]
    RAG[RAG / Retrieval]
  end
  subgraph Scale["Scale Out"]
    Orch[Orchestrator]
    Workers[Worker Agents]
    Handoff[Handoffs]
  end
  User --> Runtime
  Runtime --> Capabilities
  Runtime --> Scale
  Runtime --> Obs[Observability]

Learning path (agentic track)

Step Course What you'll learn
1 Course 07 · AI Agents Agent loop, ReAct, tool use, frameworks
2 Course 08 · Harness & Tools Runtime primitives, MCP, safety, tracing
3 Course 09 · Multi-Agent Orchestration, coordination, patterns
4 Course 06 · RAG Retrieval-driven agents
5 Course 16 · Capstones End-to-end agent projects

Core concepts

Concept Handbook OSS inspiration
Agent loop Course 07 · Intro to agents Microsoft AI Agents for Beginners
Harness Course 08 Awesome Harness Engineering
Tools & MCP Course 08 · Tools & MCP Model Context Protocol
Orchestration Course 09 Agents Towards Production
Workflow vs agent Course 07 · Workflow vs agent LangGraph docs

When to use what

Problem Pattern Course
Single task with tools ReAct agent 07
Long-running coding agent Harness + sandbox 08
Research across sources Multi-agent + RAG 09, 06
Deterministic pipeline Workflow (not agent) 07
Customer support Orchestrator + specialists 09

Visual references