M9-A — What Are AI Agents?
You have used chatbots (ask → answer). An AI agent goes further: give a goal → it figures out steps → uses tools → keeps going until done (or stuck).
🆚 Chatbot vs Agent
| Chatbot | AI Agent |
|---|---|
| One question → one answer | One goal → many steps |
| Waits for you each time | Can loop on its own |
| No tools (usually) | Can search web, run code, send email |
| "What is RAG?" | "Research today's AI news and save summary to my notes" |
Personal assistant analogy
Chatbot = friend who only gives advice when asked
Agent = assistant who books the ticket after you say "plan my trip"
🧩 What makes something an "agent"?
Most agents have four abilities:
1. PERCEIVE → read message, files, web results
2. PLAN → break goal into steps
3. ACT → call tools (browser, calculator, API)
4. REMEMBER → store what happened for next step
┌─────────────┐
Goal → │ AGENT │ → Tools (search, files, apps)
│ (LLM brain)│
└──────┬──────┘
↓
Memory
The LLM is the brain. Tools are the hands. Memory is the notebook. Without tools + memory, you only have a chatbot.
🔧 What are "tools"?
A tool is anything the agent can call besides talking:
| Tool | Agent uses it to… |
|---|---|
| Web search | Find current information |
| File read/write | Save notes, update TODO |
| Calculator | Do maths correctly |
| Email API | Send message |
| Terminal | Run a script |
When you see ChatGPT "browse" or "run code" — that is tool use.
🔄 The agent loop (backend)
This loop runs until task done or max steps reached:
┌──────────────────────────────────────┐
│ 1. Read goal + memory │
│ 2. LLM decides: "next action?" │
│ 3. If answer ready → reply to user │
│ 4. If need tool → call tool │
│ 5. Tool result goes back to memory │
│ 6. Go to step 1 │
└──────────────────────────────────────┘
Example:
Goal: "Summarise today's AI news into notes.md"
Step 1: Agent searches web
Step 2: Agent reads 5 articles
Step 3: Agent writes summary
Step 4: Agent saves file
Step 5: Agent tells you "Done"
You did not micro-manage each search query — the agent planned it.
🎒 Examples students understand
| Agent idea | What it does |
|---|---|
| Homework helper | Finds sources → outlines essay → you edit |
| Job finder | Reads resume → searches listings → drafts cover letter |
| Shop bot | Reads enquiry → checks price list file → drafts reply |
| Study agent | Reads your PDFs → makes quiz → logs wrong answers |
Brochure: Agentic AI = systems with memory, planning, execution, autonomous workflows.
⚠️ Agents are not magic robots
| Myth | Truth |
|---|---|
| "Fully autonomous forever" | Needs goals, limits, and human checks |
| "Never wrong" | Tools fail, web lies, loops get stuck |
| "Replaces developers" | You design goals, tools, and safety rules |
Max steps, allowed tools, "ask human before sending email" — otherwise agents run wild.
🛤️ Where you are in the course
Module 1–3 Prompts
Module 4 Prompt systems
Module 5 Multimodal content
Module 6 Productivity
Module 7–8 RAG & knowledge
Module 9 Agents ← you are here
Module 10 Many agents together
Module 11 CrewAI / AutoGen tools
Next: M9-B — Memory Planning and Execution
Compare: M1-A - The Intelligence Stack — Agentic AI layer