Artificial Intelligence (AI) is basically technology that lets computers do things we usually think only people can do — like learning from experience, spotting patterns, making decisions, or even holding a conversation.
You’re already using AI all the time:
- Recommendation systems — When Netflix somehow knows exactly what you want to watch next, or YouTube keeps serving videos you’ll actually click on.
- Voice assistants — Siri and Alexa answering questions, setting reminders, or turning on lights just because you asked.
- Language models — Tools like ChatGPT that can help you understand something, brainstorm ideas, or write a message without sounding awkward.
- Autonomous vehicles & facial recognition — AI helps self-driving cars detect lanes, people, and stoplights. It also unlocks your phone with your face or tags friends in photos automatically.
Key Concepts
Machine Learning (ML)
This is how computers “learn” from data. Instead of giving them step-by-step instructions, we show them examples — like thousands of photos — and they figure out how to make their own predictions.
Neural Networks
Think of these like digital versions of brain cells. They’re made of layers that work together to recognize patterns, whether that’s spotting a face in a picture or understanding what someone is saying.
Large Language Models (LLMs)
These are AIs trained on huge amounts of text from around the internet. Because of that, they can understand questions, summarize information, help with homework, or even write essays and messages alongside you.
RAG — Retrieval-Augmented Generation
RAG is a type of AI where you give the AI information first, and then it uses only that information to answer questions.
You can think of RAG like giving AI a trusted set of information to use, instead of letting it pull random answers from the internet.
How RAG AI Works
RAG combines two important abilities:
RETRIEVAL
The AI searches through the materials you provided, such as:
- PDFs
- Word documents
- PowerPoint slides
- Notes
- Web pages
- Spreadsheets
- Other uploaded files
It finds the most relevant pieces of information needed to answer your question.
GENERATION
After finding the right information, the AI uses a language model (like ChatGPT) to:
- Explain it clearly
- Summarize it
- Answer questions in plain language
The key point is that the AI is not guessing — it’s responding based only on the content you gave it.
RAG helps AI give answers that are actually based on sources you trust, not just guesses. That’s what makes RAG so useful for school projects, business tools, and anything where accuracy really matters.
Simple Examples of RAG AI
A teacher uploads history documents about the U.S. Civil War
- Students can ask questions about causes, battles, or timelines
- The AI answers using only the teacher’s materials
A sports coach uploads playbooks, scouting reports, and stats
- Players can ask how to improve their position
- The AI responds using team-specific information, not random advice
This makes RAG especially useful for studying, training, and learning from trusted sources.
Agentic AI — AI That Acts
Most AI tools today respond when you ask a question.
Agentic AI goes a step further — it can act.
Agentic AI is a type of AI that can plan, make decisions, and take multiple steps on its own to complete a task — instead of stopping after one answer.
Think of it like a team of smart digital assistants working together to get something done from start to finish.
How Agentic AI Works
Instead of one AI doing everything, Agentic AI uses multiple AI “agents.”
Each agent has a specific role — similar to people on a team.
One agent acts as the planner (the “boss”). Other agents act as workers that handle different parts of the task.
The planner breaks a big goal into steps, assigns tasks to the worker agents, checks progress, fixes problems, and pulls everything together into a final result.
A Simple Example: Planning a School Event
Imagine a school is planning a Spring Dance.
An Agentic AI system might include:
- Planner Agent
Breaks the goal into steps like picking a theme, finding a location, creating a schedule, and setting a budget - Research Agent
Looks up venues, costs, decoration ideas, and food options - Budget Agent
Makes sure everything stays within budget - Creative Agent
Comes up with theme ideas, names, and visuals - Music Agent
Builds a playlist or DJ request list - Promotion Agent
Creates posters, announcements, and social media posts
The planner agent coordinates all of this work, checks for issues, and produces a complete plan — without you having to guide every step.
Real-World Agentic AI Examples
Agentic AI can already:
- Check your calendar and schedule meetings
- Book flights or travel plans
- Run data analysis projects
- Manage multi-step work tasks at companies
- Improve its process over time by learning what worked before
This same system can be reused again and again — getting better each time it runs.
Why Agentic AI Matters for Your Future
Companies are already using agentic AI to work faster and more efficiently.
Instead of replacing people, agentic AI:
- Handles routine steps
- Reduces busywork
- Helps humans focus on decisions, creativity, and leadership
When you enter the workforce, you will almost certainly use or help design agentic AI workflows — just like earlier generations had to learn email, spreadsheets, and smartphones.
Agentic AI is becoming a normal part of how work gets done.
The Human Connection
Humans still define the why — AI just helps execute the how.
RAG and agentic AI can handle a lot of tough tasks, but they still depend on you — your goals, your judgment, your creativity.
AI might be powerful, but it’s your ideas and direction that give it purpose.
In the end, AI is the tool. You’re the one in charge.