How to get into AI for Non-Technical Late Bloomers: A Beginner's Guide
The ultimate starting point. 🎄🌸🐢 - for anyone who wants AI to feel less confusing and more like something they can use in real life.
Good Morning,
As one of the older AI Newsletters on Substack, I pride myself on getting a variety of voices and perspectives on here with the help of guest contributors. From learning about how to use AI, to multiple other topics, our niche has been fairly broad over the past four years. I wanted to build something useful and try to add value for casual readers and also for more serious AI enthusiasts.
I asked Daria Cupareanu of AI Blew My Mind Newsletter about how to take up AI if you are just starting out. A lot of my valuable readers it turns out are actually a lot of people with more discretionary time, like those who are over 50 and including those who may have (already) had a great career who want to keep a pulse with what’s going on in AI and BigTech. But also to empower themselves with this new technology and embrace it in use cases where and if - it works for them. But how to start? 🏁
The applied nature of Daria’s work (who is one of my most viral guest contributors - go Romania 🇷🇴) should also be commended. Sometimes you just want to read something in plain english that’s easy to integrate into your life. Introducing: 🙏
AI Blew my mind LAB 🧪🔬
Presenting Daria Cupereanu’s AI Learning LAB
AI blew my mind LAB - A practical resource library with prompts, tools, automations, and step-by-step guides for using AI in your work and life. Built for any level and any role, so you can learn on your own terms.
To read Daria’s last article with us go here. It was called: How to use AI to Optimize your Personal Life and Free Time.
If you find this article useful to you, kindly share it with someone who might benefit from it as well.
So in plain english, for those who want to start from the very beginning.
How to get into AI for Non-Technical Late Bloomers: A Beginner’s Guide
A starting point for anyone who wants AI to feel less confusing and more like something they can use in real life.
If you feel like the whole world is talking about Artificial Intelligence and you’ve just barely scratched the surface with it, you’ve arrived at the right place.
Perhaps you tried an AI model once and got a disappointing answer. Maybe you feel you need to “take a course first” or understand the technology before you can use it. Maybe the flood of AI news makes catching up feel impossible, or you just don’t see where it fits into your life.
Whatever the reason for your hesitation, this is a moment of opportunity.
Because if you’ve ever caught yourself thinking “I wish I’d bought Bitcoin or Apple stocks early” or “I should’ve started a blog when blogs were new” or “I missed the YouTube creator wave”, well, this is that moment everyone wishes they caught. Again. And you’re actually here for this one.
And maybe you don’t care about catching waves or being early to anything. Maybe you just want to understand where the world is going, how your kids or grandkids will live in it, and how AI is already shaping work and everyday life. That’s reason enough.
Whatever brings you here, now is better than later.
AI has now reached a point where the tools are intuitive and anyone can use them. The learning curve is shrinking, and the earlier you start, the more naturally it’ll become part of how you think, work, and create.
What’s in this guide
This guide is meant to give you a clear path into AI without overwhelming you or assuming any technical background. Here’s a quick sense of what we’re about to cover:
What AI actually is
Which AI model to pick
How people are using it in their day-to-day life and at work
How to figure out where AI fits in your life
Foundational best practices for using AI that you shouldn’t skip
Tools, courses, and books to get you started
The path from beginner to “this is part of how I work”
We are Just Getting Started
Editor’s note: Wherever you are in life and learning, keeping up with AI can make you feel more courageous and in control in this time of upheaval and new opportunities, and as for Generative AI we are just basically only three years in. 🐣 It’s still early, so they say:
I Figured Out How to Make NotebookLM Write Like Me
Nano Banana: Everything You Need to Know About Google’s Viral AI Editor
Recursive Prompting: The Process That Makes AI Outputs (and You) Smarter
First things first… what is AI, really?
Let’s begin by putting things in perspective, so we have a good understanding and common ground before we start.
The kind of AI everyone is talking about now is called Generative AI. The simplest way to think about it is “autocorrect on steroids”.
Your phone’s keyboard predicts the next word based on what you’ve typed, Generative AI predicts the next sequence of words, images, or sounds based on patterns it learned from a massive amount of data, like billions of pages from the internet.
It doesn’t “think” or “understand” like you and I do. It makes statistical predictions to generate a response that fits your request. And because those predictions aren’t deterministic, you can write the same thing a hundred times and still get a slightly different answer.
But AI has been around for quite some time already. It’s not some brand-new sci-fi concept that appeared overnight.
When Netflix suggests what to watch next, that’s AI. When your email filters spam, that’s AI. When your bank flags suspicious transactions, when your camera app automatically adjusts settings, when Google Maps reroutes you around traffic, all AI.
The difference is that AI became much more well-known since ChatGPT launched in November 2022, and it’s now used by about 10% of the world’s adult population. Which is the fastest adoption we’ve ever had for any technology.
Source: BOND
If you want to learn more about what it is, where it came from, and how it evolved, I wrote a beginner-friendly deep dive on it a while ago. For now, we are going to zoom in on the kind of AI everyone is actually using in daily life: Generative AI.
This is the version of AI that moved out of research labs and into your browser, put a text box in front of you, and said: “Type something and I’ll help”.
It is what turned AI from something companies used in the background into something you can directly think with, build with, and get work done with.
And we’ll start with the AI models we hear most about.
The most well-known AI models and which one to start with
When you’re new to AI, the first instinct is usually to overthink which model to pick. That part doesn’t matter as much as people think. It’s better to choose one solid general-purpose model and go all in. Gemini, Claude, or ChatGPT all work fine for that.
Here’s a brief overview of the most well-known ones:
Table created with Gemini’s image generator (Nano Banana Pro)
Even though each of them has a free version, they’re all around $20/month for a full subscription.
And it’s worth getting it, because the free tiers have usage limits that’ll frustrate you once you start using AI regularly. The paid tiers also give you noticeably better responses, so the quality jump alone is worth it once you’re using AI more than casually.
With time, as you try different models, you’ll start to notice differences in output, strengths, and “personality”, and you’ll naturally develop your own preferences. For now, you don’t need to worry about that. Take it step by step.
My recommendation: If you already use a lot of Google products, my current recommendation is Gemini. Its latest model, Gemini 3, is ahead on many benchmarks and works well as an all-purpose assistant.
If you are not deep in the Google ecosystem, my next picks are Claude or ChatGPT. Both are strong general-purpose tools and anything you learn with one of them will transfer easily to the others.
How people actually use AI models
To get a sense of how you can use AI in your own life, seeing how others already use it can give you some great inspiration.
Recent research from the National Bureau of Economic Research looked at more than one million ChatGPT conversations and found that about 70% of chats were personal and only 30% were work-related.
When you zoom in, most conversations fall into three big buckets: Asking, Doing, and Expressing.
Asking
People usually come in to make sense of something, ask for guidance, or see their options more clearly. And unlike Google, where you still need to sift through links and piece together your own answer, AI tailors the response directly to what you asked.
“How does intermittent fasting work?”
“How do I fix a leaky faucet?”
“What’s a good birthday gift for a 7-year-old who loves dinosaurs?”
Doing
This is the moment when someone says “do it for me” or “help me do it”. You see it most in writing, planning, technical tasks, and anything creative like images or videos.
“Rewrite this email.”
“This is everything I have in the fridge, give me three meals I can cook and the recipes.”
“Summarize this book into three main takeaways.”
Expressing
A smaller group uses AI the way you’d use a notebook, a therapist, or a friend. They talk things out, process emotions, or try to untangle what’s going on in their head.
“I feel stuck in my career and don’t know what direction to take.”
“I’m overwhelmed with everything on my plate and need to talk this through.”
“I’m anxious about an upcoming move to a new city, how should I prepare?”
The pattern? AI meets people where they are. Sometimes you need information. Sometimes you need a task done. Sometimes you just need to think out loud.
Where AI fits in your life
Once you see how others use AI, the next question becomes: where does it fit for you?
When something is new, you don’t automatically see where it fits or what you can use it for. Examples help because they spark ideas, but the real learning comes from trying it on almost anything at the beginning.
With time, you’ll develop a sense for when it helps and when it doesn’t, but that only happens through use.
Here’s a mix of everyday and work examples to get you started:
Visual created with Claude Artifacts from the use cases I picked
If you want more ideas for personal use, I also wrote a post on how to use AI to optimize your life and free time, which picked up a lot of attention. And since it’s almost Christmas, you might like the one I did on AI-powered gift ideas too.
Visual created with Claude Artifacts from the use cases I picked
Most of my content is about using AI to get an edge at work. If you want ideas, from practical workflows to simple automations you can build, you can start here or check out my platform where I share resources and guides that fit any role and any level.
How to use AI models: best practices
You’ve picked a model. Now let’s make sure you actually get good results from it. Here are some important things to keep in mind:
Infographic created with NotebookLM
1. Give context like you’re delegating to a smart colleague
AI has no idea what your situation is or what you actually want unless you tell it.
✖️What most people do: “Give me a recipe”
✔️What actually works: “I have chicken breast, broccoli, rice, and basic spices. I need a healthy dinner for 2 that takes under 30 minutes. We don’t like spicy food. Give me step-by-step instructions on how to prepare it.”
Same with emails, presentations, advice - anything. The more context you give, the more relevant the output.
And by the way, this is what people mean when they say “prompting“. It’s just the fancy word for every message you type into an AI.
What matters most (especially as models evolve and get better) is thinking clearly and communicating what you actually need.
Context is a big part of it. The other part is some prompting best practices that can help you get better results.
2. Ask neutral questions (AI is a people-pleaser)
AI models are built to be helpful and very agreeable, almost like a mirror.
If you want real help with creating something or making a decision, you need to phrase things in a more neutral and tactical way so your own biases don’t steer the answer.
✖️Confirmation-seeking: “Isn’t it better to buy this laptop than this one?”
✔️Better question: “What are the pros and cons of these two laptops and in which situations would each one be a better fit?”
If you want to go deeper into avoiding biased questions and asking AI better ones, I wrote more about it here.
3. Iterate, the first answer is just a starting point
Using AI is not a one-and-done thing. You don’t just throw in a request and get the best output on the first try. Sometimes you’ll get lucky, but not often enough to rely on it.
That’s where a lot of people get frustrated instead of seeing the first answer as a rough draft. People who work well with AI treat it the way you’d treat any draft: you review it, adjust what doesn’t fit, ask for changes, and shape it step by step until it works.
A real session looks like this:
You: “Help me write an email to my team about our new hybrid policy. Under 200 words, professional but warm.”
AI: [First draft]
You: “Add a specific example of how this helps work-life balance. Then make the opening more personal based on this context: [context]”
This back-and-forth is how you get useful results.
4. Always verify (AI can be confidently wrong)
AI doesn’t know when it’s wrong. Even though some recent research suggests it can sense uncertainty, it still prioritizes giving you an answer over admitting it’s unsure.
That’s why it sometimes generates something that fits your question statistically, whether or not it’s actually accurate. This is called a “hallucination” - when the model invents facts, cites sources that don’t exist, or gives you plausible-sounding nonsense.
Higher risk: Specific statistics, citations, recent events, obscure topics, names and dates
Lower risk: General knowledge, common procedures, creative tasks
How to protect yourself:
Stay skeptical. Start with topics you already know so you can spot when something feels off. That mindset should stay with you no matter what you’re using AI for.
Ask for clarity. Try: “What are your sources for this?” or “If you’re unsure about the answer, say so.”
Use web search. Many tools can pull current information instead of relying only on training data.
Verify what matters. For anything important, double-check it on your own.
The golden rule: You are the decision-maker. AI is the tool.
A note on privacy
Before we go further, it’s important to also talk about privacy.
As a general rule, just be thoughtful about what you share. Avoid putting in things like passwords, SSNs, credit card numbers, strictly confidential work documents (always check your company’s policy), other people’s personal information, or private health details.
If you wouldn’t email it to someone, don’t type it into an AI. It sounds obvious, but it’s easy to forget.
Now let’s talk about where to go deeper once you’re comfortable with the basics.
Your AI Starter Kit: tools, courses, and books
The goal here isn’t to try everything. It’s to master one or two things before getting overwhelmed by options (because yes, that happens a lot with AI).
So start with a single general-purpose chatbot, explore one free course, and pick one book if you’re inclined to read deeper.
Best AI tools to start with
Besides the major AI models, tools have come out like mushrooms after rain. And many apps you might already use (like Canva or Notion) now have AI built in as well.
Here’s a curated list of some other great AI tools by category:
Research & Learning: NotebookLM (by Google), Storm (by Stanford University), Consensus
Images: Nano Banana Pro (Google’s image generator), DALL-E (OpenAI’s image generation model), Midjourney
Presentations: Gamma, Beautiful.ai, NotebookLM (with its new slide deck generation feature)
Voice & Audio: Wispr Flow (voice to text), Suno (AI music creation), ElevenLabs (voice generation)
Video: Sora (OpenAI’s video generation model), Veo (Google’s video generation model), Runway, Descript, OpusClip
Productivity: Notion AI, Otter.ai, Granola (meeting notes)
Build your own apps (no code): Lovable, Bolt, Replit, Blink, Base44
Good to know: Google has a bunch of free experiment tools worth exploring in Google Labs:
Pomelli – generates on-brand social content from your website
Mixboard – creative board for expanding ideas visually
Opal – create mini apps using plain English
Learn Your Way – turns any resource into an interactive learning experience
Doppl – virtual outfit try-on
If a tool isn’t available in your country, a VPN usually solves that.
Finding the right tool: There’s probably already something for anything you can imagine. When you run into a specific need, check an AI directory. My go-to is There’s An AI For That (TAAFT). I also wrote a deep dive on the biggest AI directories here.
Free AI courses to get started
If structured learning works best for you, here are some of the best free options.
General AI Foundations
Google AI Essentials – Practical, hands-on, designed for absolute beginners. Covers fundamentals, daily use cases, and prompting. Offers a certificate upon completion.
AI For Everyone (Coursera) – Taught by Andrew Ng, one of the most well-known names in AI. Great for understanding the business and strategic side. Free to audit.
Prompting & Using Different Models
OpenAI Academy – Learn how to prompt ChatGPT effectively
OpenAI Prompting Packs – Role-specific examples for using ChatGPT
Google’s Prompting Guide – Official guide for Gemini
Anthropic Academy – Learn how to work with Claude
Claude for You – Everything about Claude’s features
NotebookLM Official Guide – How to get the most out of it
Creating Images with AI
Nano Banana Pro Examples – Hundreds of image examples
Nano Banana Deep Dive – Everything you need to know
Making Infographics with AI – My guide on this
Midjourney Getting Started – Official docs
Creating Videos with AI
Veo Prompting Guide – Google’s video model
Sora 2 Prompting Guide – OpenAI’s video model
AI Agents (More Advanced)
Google’s AI Agents Course – Building agents for organizations
OpenAI’s Guide to Building Agents – Practical PDF guide
IBM’s AI Agents Explainer – Solid overview of the concept
For hands-on implementation
If you learn better by doing than by watching, I built AI blew my mind Lab as a practical resource library. It’s where I collect tools, prompts, automations, and step-by-step guides for using AI to solve real problems, from everyday tasks to building systems that work for you.
Name us one of your top free courses or learning AI Newsletters:
AI books worth reading
If you prefer learning through reading, I’d suggest you check out this article by Paul Morrison. But here are some more picks depending on what you’re looking for.
For beginners
Co-Intelligence: Living and Working with AI by Ethan Mollick – The best starting point right now. Practical, recent, focused on how to actually collaborate with AI in your daily work. Written for non-technical people.
Artificial Intelligence: A Guide for Thinking Humans by Melanie Mitchell – A look at what AI can actually do versus what people assume it can do, with a focus on real limits, real capabilities, and what that means for the future.
For understanding the bigger picture
AI Superpowers: China, Silicon Valley, and the New World Order by Kai-Fu Lee – The global AI race, China vs US, and what’s at stake economically. Gives you context for why everyone’s paying attention.
Nexus: A Brief History of Information Networks from the Stone Age to AI by Yuval Noah Harari – A big-picture look at how biology, technology, and data are merging, and what that means for power, privacy, and the future of human agency.
For deeper thinking
Life 3.0: Being Human in the Age of Artificial Intelligence by Max Tegmark – Tackles the big philosophical questions about humanity’s future alongside increasingly powerful AI.
Empire of AI by Karen Hao – Investigative critique of AI companies, including OpenAI, highlighting the hidden costs and ethical issues in generative AI development
Fiction, if that’s your thing
I, Robot by Isaac Asimov – A classic set of stories about humans, intelligent machines, and the famous Three Laws of Robotics. Explores control, trust, and what happens when machines grow beyond their creators.
Blindsight by Peter Watts – Challenges assumptions about intelligence and consciousness. Dense but rewarding.
The path from “What is this?” to “I use this daily”
Learning AI isn’t about taking a course and then “knowing it”. It’s a gradual shift in how you think and work. Here’s what that progression usually looks like:
Visual generated with Nano Banana Pro
Phase 1: Start wherever you are.
Pick any general-purpose AI model. ChatGPT, Claude, Gemini, doesn’t matter which. Start with something you don’t enjoy doing and could use help with, or just follow your curiosity. There’s no wrong entry point.
Phase 2: Find your lightbulb moment.
At some point, AI will help you with something that actually matters to you. Not a test question, a real one. That’s when it stops feeling like a novelty and starts feeling like a useful tool.
Phase 3: Hit the reality check.
As you continue using it, AI will disappoint you. Sometimes it’s the technology’s limitations. But often, with practice, you’ll notice how much the output depends on how you communicate. Vague input, vague output. This is where most people either give up or get better.
Phase 4: Build the habit.
Once you know how to talk to it, you stop thinking of it as a separate thing to “use” and start reaching for it the way you’d reach for a search engine or a calculator. It’s just there when you need it.
Phase 5: Accelerate across use cases.
You begin seeing opportunities everywhere. Writing, research, brainstorming, organizing, learning. The pattern recognition kicks in.
Phase 6: Expand what’s possible.
Eventually, you find yourself doing work that used to feel out of reach. The things you never had the time, skill, or budget for. You start building systems around you that help: automations that handle repetitive tasks, workflows that run in the background, tools that work together.
Over to you
If you’ve made it this far, you’re already ahead of most people. Not because you know more, but because you’re willing to learn. And that’s really all it takes.
You don’t need to understand everything before you start. You just need to pick one tool, try it on something real, and keep going. The rest figures itself out through use.
And since today is the earliest you’ll ever be on your AI journey, start now.
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Very insightful! Thanks for putting it together
Definitely helpful to anyone who wants to get started with AI.
I believe AI will be 'in' and 'on' your life, so it is better to learn and adapt with it; it will be better and a smarter move.