9 free guides · No signup required

AI Agents 101

A practical guide series on AI agents - what actually makes something an agent instead of a chatbot, how the plan-act-observe loop works, and what it takes to trust one in production. Framework-agnostic: the same concepts apply whether you build in LangGraph, n8n, or straight API calls.

Get Started → Core Concepts → Go Deeper · ~59 minutes total
plan act observe loop if not done Goal Plan Act tool call Observe Done

The agent loop in one picture: plan a step, act on it, observe the result, and either loop again or stop.

GET STARTED

Start Here

Heard "AI agent" everywhere and not sure what actually separates one from a chatbot with extra steps? These two guides get you oriented.

What Is an AI Agent?

The plain-English version: what separates an agent from a chatbot or a script, and why the difference actually matters.

Get Started 6 min read

The Agent Loop: Plan, Act, Observe

The cycle every agent runs on, and why it's the same shape whether the framework calls it ReAct, a graph, or something else.

Get Started 6 min read
CORE CONCEPTS

What Actually Makes an Agent Useful

Two capabilities turn a loop into something worth trusting with real work - the ability to act on the world, and the ability to remember.

Giving Agents Tools

How tool calling actually works under the hood, and the design choices that determine whether an agent uses a tool correctly.

Core Concepts 6 min read

Memory and State in Agents

Short-term working memory versus long-term memory across sessions, and why conflating the two causes most of the weird behavior.

Core Concepts 7 min read

Want more hands-on AI builds like this?

APA Mastery runs live, practical sessions on working with modern AI tools - not just theory.

See What's On →
GO DEEPER

Know If It's Actually Working

The guide that separates "I built an agent demo" from "I trust this running unattended."

Evaluating and Deploying Agents

Task success rate, guardrails, and human-in-the-loop checkpoints - what it actually takes to trust an agent in production.

Go Deeper 7 min read

Multi-Agent Systems: Orchestration, Handoffs, and Supervisors

When one agent isn't enough - the supervisor pattern, how handoffs actually work, and what breaks down as you add more agents.

Go Deeper 7 min read

Agent Design Patterns: ReAct, Plan-and-Execute, and Reflection

Three different shapes an agent's reasoning can take, and a real comparison of when each one actually fits the task.

Go Deeper 7 min read

Common Agent Failure Modes and How to Debug Them

Hallucinated tool calls, infinite loops, tool misuse, and context poisoning - the recurring ways agents break.

Go Deeper 7 min read

Cost and Latency: Making Agents Fast and Affordable

Token burn from long loops, model routing, and caching repeated tool results - the constraint that shows up right after reliability.

Go Deeper 7 min read