Tutorials Prompt Engineering Tutorial
AI Agents Introduction — Complete Guide
AI Agents Introduction — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of Prompt Engineering Tutorial on Toolliyo Academy.
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Prompt Engineering Tutorial · Lesson 51 of 100
AI Agents Introduction
Prompts ✓ → Apps
Apps · 2 — RAG & agents · ~6 min · Module 6: AI Agents
What is this?
An AI agent loops: perceive input, plan, use tools, observe results, until it meets a stop condition — more autonomous than one-shot chat.
Why should you care?
PromptVerse Agent Studio configures goal, tools, and guardrails for support and ops agents.
See it live — copy this example
Copy the prompt into ChatGPT, Claude, or your LLM API playground and compare outputs.
agent_config = {
goal: "Resolve billing ticket or escalate",
tools: ["search_kb", "get_invoice", "escalate_human"],
max_steps: 6,
stop_when: "resolved OR escalated"
}What happened?
- Goal defines success.
- Tools bound actions.
- max_steps prevents runaway loops.
- stop_when ends the loop explicitly.
Practice next
- Write goal + 3 tools for a fake agent.
- List stop conditions.
- Role-play 4 steps on paper.
- Add memory summary every 3 steps.
- Log each step to trace UI.
Remember
Agents = loop + tools + goal. Cap steps. Human escalation is a tool.
Agent pilot
Team replaces static FAQ with agent.
Outcome: Agent searches KB before answering; escalates edge cases.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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