AI Agents: The Complete Guide Hub — How They Work, How They’re Built, and How to Use Them Safely

AI agents are software that does not just answer — it acts: planning steps, using tools, and checking its own work. This hub gathers every Wedlockcross guide on agents in one place, in the order that makes sense: first what an agent is and how it works, then how agents are built, the frameworks people actually use, how multiple agents work together, and finally the honest part — testing, security, and limits. Start at the top if you are new; jump to a section if you are not.

Start Here — What an AI Agent Is and How It Works

• What Is an AI Agent? — The best first step: what an agent is, in plain English, and why it is more than a chatbot.
• What Are AI Agents? — The same question answered through examples: software that books, codes, and shops on its own.
• How Do AI Agents Work? — The perceive–think–act loop: how an agent observes, decides, and takes action.
• How Do AI Agents Make Decisions? — Inside the reasoning loop: how an agent chooses its next step.
• Types of AI Agents — The six kinds you will actually meet, and how they differ.
• AI Agent vs AI Assistant — People treat these as the same thing; this guide draws the real line between them.
• AI Agents vs LLM — A model is not an agent — an agent is the system built around the model.
• What Are AI Agents Used For? — Ten practical uses that are already working today.
• AI Agent Examples in Real Life — Twelve examples you have probably already crossed paths with.

Architecture — How an Agent Is Built

• AI Agent Architecture Explained — Part by part: the planner, memory, tools, and executor, mapped.
• AI Agent Framework — What a framework actually gives you, and why agents are rarely built without one.
• How to Build a Simple AI Agent — A beginner walkthrough: build your first small agent yourself.
• AI Agent Tools Explained — How an agent learns to use tools, and why tools are what make it useful.
• Tool Use in LLMs — How language models learn to act on the world, not just describe it.
• Function Calling AI — The same ability at the technical level: how a model calls a function.
• What Is Agent Memory in AI? — The types of agent memory, what they do, and where their limits are.

Frameworks — What People Actually Use

• LangChain Agents Explained — The ReAct loop that taught AI to use tools.
• What Is LangGraph? — Graphs, state, and control flow — when a simple loop is not enough.
• AutoGen AI Agents — Microsoft’s conversational multi-agent framework.
• CrewAI Explained — Role-playing agents that work like a team.
• BabyAGI Explained — The small project that started the agent boom.

Multi-Agent Systems — When One Agent Is Not Enough

• Multi-Agent Collaboration — How agents divide work between them and put the results together.
• Single Agent vs Multi Agent Systems — A straight comparison: which architecture wins, and when.
• Agent Orchestration — The patterns behind multi-step systems: who calls whom, and when.

Safety, Testing, and Limits — The Honest Part

• AI Agent Security Risks — Prompt injection, tool abuse, and the defenses against both.
• Prompt Injection in AI Agents — How the attack works and how to stop it — the deep dive.
• AI Agent Testing — How to test an agent before it breaks things.
• SWE-Bench Explained — The benchmark that grades coding agents.
• AI Agent Limitations and Risks — The honest review: where agents still stop, and why.

Where to Go Next

Every new agent guide will take its place in this hub. If you read only one guide, start with What Is an AI Agent? If you are about to build, go straight to the Architecture and Frameworks sections — and read the Safety section before you deploy anything.