AI Explained: The Basics You Need to Know
Everything you need to know about AI, explained in simple terms (no technical jargon). Shaped by the questions I hear most in my conversations with product people.
AI is Everywhere
It's in your inbox, your product meetings, and your tools.
You’ve probably used ChatGPT or watched tools get “smarter” overnight.
It's everywhere, including in people's minds 🧠
I wrote this article because every time I sit down with designers or product folks, the same questions come up:
Is AI going to replace me?
What if I’m behind everyone else already?
Where do I even get started?
These are normal questions, and if you have them, you’re not alone.
The Starting Point
Before you can use AI in your workflow, design with or for AI, or even talk about it with confidence, you need a clear picture of what it actually is.
This article explains what AI is and how it works (no-fluff version), covering basic terminology, so you can stop nodding through conversations and understand what’s going on. I am basically sharing my notes with you!
Questions First
🤖 Is AI going to replace me?
AI won’t replace you, but it will replace how you work. The real shift is that people who use AI will have an edge over people who don’t.
🔍 Do I need to understand how it works to use it?
You don’t need to be an engineer, but if you’re using or designing for AI, you need the basics: what it’s good at and where it fails.
⏳ What if I stay behind everyone else?
You’re not. AI is moving so fast that even experts are learning as they go. If you’re starting now, you’re exactly where you need to be: on the right track!💫
🚀 Where should I even start?
Start using it to understand it! Improve one step in your daily work, tidy up notes, or create something from scratch (like an image, a video, or even a simple landing page).
What is AI? The Definition
Artificial Intelligence (AI) is software that mimics specific human skills such as language, pattern recognition, or decision-making. AI is like an intelligent robot brain. It learns by analyzing examples, such as millions of pictures or words, and then uses that information to predict answers.
The term Artificial Intelligence was first introduced in 1956 by computer scientist John McCarthy, who defined it as:
“The science and engineering of making intelligent machines.”— John McCarthy
Think of AI as a pattern machine.
It doesn’t think. It doesn’t feel.
It just analyzes massive amounts of data to spot what’s likely or useful.
You can find it in:
Autocomplete in Gmail
Recommendations on Netflix
Chatbots in customer service
Generating images, text, or code
Summarizing meetings
Translating languages
How AI Works: The Basics
Before an AI can assist you by answering a question, generating an image, or writing code, it needs four key building blocks. Each plays a specific role in how the system learns and responds.
1. Model
A model is the trained “brain” of the AI. It’s a computer program that has learned to recognize patterns, like how people write, speak, or what objects look like in images.
It learns from millions of examples (text, images, audio, etc.)
It encodes those patterns into its internal system
It powers how the AI understands inputs and generates responses
Examples of models include GPT-5, Gemini, and Claude.
2. Dataset
A dataset is the material the AI learns from during training.
It includes large amounts of real-world information in various formats.
Text (books, websites, documents)
Images and videos
Audio (recordings, transcripts)
Logs, spreadsheets, or code
The size, variety, and quality of a dataset directly impact the capability and accuracy of a model in specific tasks.
3. Training
Training is how a model learns. It analyzes massive datasets, identifies patterns, and adjusts itself to improve its prediction accuracy.
The model learns directly from data without manual human input
It improves by making predictions, comparing examples, and receiving feedback
All of this occurs before the model is released, influencing its practical performance.
4. Inference
Inference is the process that occurs when you use AI. You ask a question, upload an image, or give it a task, and the model responds using what it learned during training.
Applies what it learned during training to generate an output
Happens instantly when you interact with the tool
This is how systems like ChatGPT or Gemini reply instantly
The Types of AI
Not all AI is the same. Some predict what you’ll do next, others generate new content, some see and hear, and a few can even take actions for you. If you’re trying to really get a grip on how AI shows up in the real world, these are the categories worth knowing.
Predictive AI
Finds patterns in data to make forecasts or suggestions.
Recommends music, products, or actions
Examples: Spotify recs, churn prediction, email open likelihood
Generative AI
Creates new content based on learned patterns.
Text, images, video, audio, or code
Examples: ChatGPT, Midjourney, Sora, DALL·E
Computer Vision
Allows AI to “see” and interpret visual information (videos/images).
Recognizes objects, actions, or patterns in visuals
Examples: Self-driving cars, video surveillance systems
Speech AI
Understands or generates spoken language.
Converts voice to text or responds with speech
Examples: Siri, Alexa, Zoom transcription, Whisper
Multimodal AI
Understands and combines different input types.
Processes text, images, audio, or video together
Examples: Gemini, GPT-4o, Claude with vision
Agentic AI
Performs multi-step tasks to reach a goal.
Searches, compares, summarizes, and sends (all in one flow)
Examples: AutoGPT, Devin, AI agents for research or automation
📌AI Terms You Should Know
Prompt
What you type or say to the AI to get a response.
Example: “Summarize this article in 3 bullet points.”Hallucination
When the AI provides you with false or fabricated information, but it sounds confident. It’s guessing, and sometimes it gets it wrong.RAG (Retrieval-Augmented Generation)
A smarter AI setup that pulls real information from documents or the web before answering. Think of it as AI with a search engine sidekick.AI Automation
Using AI to handle repetitive, intelligent tasks. Examples include tagging emails, summarizing meetings, and categorizing feedback.Ethical AI
Practices that ensure AI is safe, fair, and transparent. This includes reducing bias, protecting privacy, and avoiding harm.AGI (Artificial General Intelligence)
The hypothetical future AI that can learn and do anything a human can. We're still far from it; today’s AI is narrow and task-specific.Preprocessing
Cleaning and formatting raw data before training. This might include removing errors, converting audio to text, resizing images, or splitting text into tokens. It helps the AI learn more effectively.Fine-tuning
Adapting a pre-trained model for a specific domain or task. Example: refining a general language model using legal documents to make it more useful for lawyers.Evaluation
Testing the model on new data to assess its performance. It helps determine if the model is accurate, fair, and ready for real-world use.
Resources To Explore
🧠 AI Fundamentals
A free, beginner-friendly course from the University of Helsinki.
Microsoft's open-source curriculum to learn AI step-by-step.
✨ AI & Design
Design principles and foundations from IBM’s design team.
Google’s design patterns and methods for building human-centered AI products.
A design toolkit to create responsible, inclusive AI experiences.
👀 Cool Newsletters
AI Supremacy by
Design + AI by
Looking Ahead
AI will shape how we work, design, and build.
If you’re starting now, remember: you’re not late.
Every small experiment you try is a step forward, and curiosity is the real advantage.
By now, you should feel more confident explaining what AI is, how it works, and the key terms that frequently appear. That’s your foundation. From here, it’s all about practice.
Thanks for reading! 🫶
Save this guide for later, share it with a friend, and try one small thing! 📌
This is a goldmine for anyone starting with AI! Simple, clear, and actionable, perfect for turning curiosity into hands-on practice. For more AI trends, tips, and news, check out my Substack, where I share weekly updates.
Love how simply you laid this out, a proper 101 guide on AI.