Learn AI
Build your understanding from AI fundamentals to production AI systems.
Prefer a guided sequence? Explore Learning PathsAgents & AI Integration
The real-world frameworks and operational concerns behind production agent systems.
8 conceptsAgent Frameworks Overview
Frameworks such as LangGraph, CrewAI, and Semantic Kernel provide the plumbing for agent state, tool calls, and control flow.
Intermediate · 4 minAgent State Management
An agent's state — conversation history, intermediate results, tool outputs — has to be persisted and passed between steps of the agent loop.
Advanced · 4 minAgent Memory in Production
Production agent memory is usually backed by a database or vector store, with explicit rules for what gets kept, summarized, or dropped.
Advanced · 4 minMulti-Agent Orchestration Tools
Frameworks like CrewAI and LangGraph provide the routing and delegation logic that coordinates several specialized agents.
Advanced · 4 minHuman-in-the-Loop in Production
In production, human-in-the-loop means a real approval queue, notification system, and timeout policy — not just a design principle.
Intermediate · 4 minAgent Evaluation
Evaluating an agent means checking whether it chose the right tools and reached a correct outcome, not just whether one response looked reasonable.
Advanced · 4 minAgent Observability
Observing an agent means tracing every step of its loop — each decision, tool call, and intermediate result — not just the final answer.
Advanced · 4 minWorkflow Orchestration for AI
Workflow orchestration sequences AI steps alongside regular application steps — some deterministic, some model-driven.
Advanced · 4 min