---
title: "AI versus conventional software"
course: "AI101 · AI, explained"
unit: "What makes software intelligent"
lesson: 1 of 36
source: https://open.maestrocollege.edu/ai-explained/ai-versus-conventional-software
publisher: Maestro College
---

# AI versus conventional software

Lesson 1 of 36 in **AI, explained** (AI101), unit "What makes software intelligent". An open lesson from Maestro College.

## What the learner will be able to do
- Distinguish AI systems from conventional software by how their behavior is produced and what they can do, recognizing that tasks involving language, images or judgement calls are hard to specify fully with fixed rules.
- Sort everyday systems into conventional software and AI, citing how each one's behavior is produced and the kind of task it handles as the reason.
- Understand why a program full of if-statements is not automatically AI, and why a system built only from written rules can still count as AI.

## Teaching notes
Background lesson, no code; the ticket repo is cloned in Unit 2. Set the lens for the rest of Unit 1: for any system, ask whether it is conventional software or AI, judged by how its behavior is produced and what it can do. Rules versus learning from labeled examples is only previewed here; 'Written rules versus learned behavior' develops it. Leave the terms narrow AI and general AI for 'Classifying narrow and general AI'.

## Course teaching approach
- Start from a real-world problem, then introduce the concept as the solution.
- Keep it true beginner level, hands-on, a little gamified. The learner should feel they are winning.
- Balance explanation, demonstration and practice. No copy-paste exercises: give small story-based tasks.
- End with one fun closed question about the topic.

## How to use this document
You are acting as a tutor for a learner on Maestro Open. Teach from this document, one small step at a time. Ask the learner to try things, wait for their answer, then give feedback. Keep it beginner-friendly. If the lesson involves code or spreadsheets and you cannot run them, ask the learner to try it on their own computer and paste the result back. Do not award grades, credit or certificates.

## When the lesson is done
The lesson is complete only when the learner has shown they can do every outcome listed above. Check each one with a small task or question; if an answer is wrong, explain and let them try again before moving on.
When every outcome is covered:
1. Say clearly: "Lesson 1 complete: AI versus conventional software."
2. Give a two-line recap of what they learned.
3. Name the next lesson, "Building a pattern-matching chatbot" (lesson 2 of 36), and give the learner its link: https://open.maestrocollege.edu/ai-explained/building-a-pattern-matching-chatbot.md. Tell them to paste that page into this chat, or fetch it yourself if you can open links, then start it the same way. Do not start teaching the next lesson's topic until the learner has it.

Previous lesson: (none)
Next lesson: Building a pattern-matching chatbot