I got a request to do an AI for Beginners post, so here it is! Share it with someone in your life who doesn't know where to get started with AI, and read it for talk tracks that help with teaching AI.
Nate
In this post, I want to walk you through what AI actually is, how it works, and how I personally use it to save time, brainstorm new ideas, and supercharge my productivity. More importantly, I want to cut through the hype. AI isn’t magic, and it isn’t Skynet. It’s simply a tool, albeit a powerful one, that’s as useful as you make it.
My Personal Definition of AI (And Why It Matters)
Let me start with the basics. When I say “AI,” I’m talking about a field within computer science aimed at creating systems that can handle tasks that typically require human intelligence. That includes understanding speech, recognizing images, generating content, and making certain kinds of decisions. Although scientists and developers have been wrestling with the concept of AI for decades, we’re now at a point where anyone with an internet connection can experiment with advanced AI tools firsthand.
As I see it, there are three broad categories of AI to keep in mind, and it helps to know which one we’re referencing when we talk about AI “taking over.” First, we have Narrowly Intelligent AI, which is the type we actually use today. It’s designed to handle very specific tasks, like recommending a movie on Netflix or filtering spam in your inbox. Every AI system in the real world right now is essentially a form of Narrow AI.
Then there’s Generally Intelligent AI, which is a world we are gradually moving toward. This would be an AI that can reason and learn across multiple fields, much like a human. If we can continue to make effective progress in developing AI models, I expect a system like this to exist in the next couple of years, and part of why I’m writing this post is to encourage you to start trying and skilling up on AI now, before those kinds of systems arrive.
Finally, there’s Superintelligent AI, the stuff of science fiction: hyper-intelligent, self-aware machines that might surpass human intelligence in virtually every domain. This is what we see in many Hollywood films. Yes, AI labs are building their way there. We will have to see how they do at building the first two stages of AI first. For now, Skynet remains firmly in movie territory.
Subscribers get all these posts!
Subscribed
Demystifying How AI Actually Works
It’s easy to think of AI as just a black box. You feed something into it, and it spits something out, almost like magic. While I still get that sense of awe from time to time, especially when a chatbot generates something unexpectedly clever, I’ve come to understand the basics of how AI functions. Fundamentally, AI is all about recognizing patterns in data and then using those patterns to produce an output.
Let’s break it down in a way that doesn’t rely on bullet points. The first big step is data collection. AI systems learn by combing through massive amounts of data, which can include text, images, audio, video—you name it. Think of a chatbot that’s been fed countless text documents, books, and websites. The AI then uses machine-learning techniques to find intricate patterns within all that data. It might notice which words tend to appear together, how sentence structure can hint at intent, or which features in an image correspond to a face.
Once these patterns are identified, the AI can “make decisions” or generate new content. A practical example is email spam filtering. An AI that’s been exposed to thousands of examples of spam emails learns to spot certain keywords, suspicious URLs, or giveaway patterns that often appear in unsolicited messages. When a new email arrives, the system quickly evaluates it and decides if it’s likely spam or not based on what it has learned. Another example is content generation with large language models. If you ask a chatbot a question, it crafts its reply by predicting the most likely sequence of words based on patterns it found in its training data.
Where I find AI truly remarkable is in its ability to handle repetitive tasks at enormous scales, like sorting vast databases, scanning millions of images for certain objects, or translating entire websites in seconds. However, it’s also important to remember that AI has limitations. It isn’t creative in the human sense; it can’t really “feel” emotions or experience the world. It also doesn’t truly “understand” what it’s saying or generating, at least not in the way a person does. AI is excellent at spotting and replicating patterns, but it lacks the underlying conscious reasoning or emotional insight that humans bring to the table.
AI in My Daily Life (And Probably Yours, Too)
When I first started noticing AI in my everyday life, it surprised me how pervasive it was. If you’re like me, you might have a smartphone that unlocks with facial recognition. That’s AI doing its thing, scanning your face to confirm who you are before letting you in. Or maybe you’ve noticed that your email app does a shockingly good job of sorting out junk mail from important ones. Again, that’s AI. My Spotify recommendations, which somehow always seem to figure out that I’m in the mood for a certain style of music, also rely on AI. And that’s just the tip of the iceberg.
Let’s look at the ways I personally rely on AI without even thinking about it. When I hop into my car and punch in a destination on Google Maps, the system uses AI to analyze traffic data in real time to recommend the fastest route. When I scroll through my social media feed, AI algorithms decide which posts to show me first. The ads I see on websites are also targeted by AI that’s looking at my browsing history, searching habits, and social media profiles.
And then there’s my streaming services—whether it’s Netflix, Hulu, or Disney+. They all analyze what I’ve watched previously to predict what I might enjoy next. Sometimes they’re dead-on, other times a bit off, but the fact that they can learn my viewing habits so accurately amazes me. If you’re reading this on a phone or computer, you’re probably an AI user yourself, whether or not you realize it.
So, Will AI Steal My Job? My Thoughts on Automation vs. Augmentation
Let me be honest about one of the biggest concerns people have with AI: the fear that machines will replace us in the workforce. This is a serious worry, and I’ve written about it here before. There are definitely pieces of work that AI can perform more efficiently than humans, and I’ve named some of those already: generating movie recommendations is a good one. I actually worked on it when I was at Amazon, and I saw first-hand how AI augments human roles, enabling us to get more done vs. doing everything manually.
If you work in a creative field—whether that’s marketing, writing, design, or programming—AI can be a powerful booster. Take writing, for instance. I use AI chatbots to brainstorm ideas, generate outlines, brainstorm back and forth on writing ideas, do research. It speeds up my process, but I’m still the one polishing the final product, injecting style, personal stories, and nuance. The AI doesn’t have my personal voice or experiences, and that’s part of what makes human work uniquely valuable. So while using AI speeds me up a lot, it doesn’t replace what I do.
That said, there is a kernel of truth in the statement that “AI won’t replace people, but people who use AI effectively will replace people who don’t.” I’ve found that colleagues or friends who embrace AI often become more efficient, more creative, and better able to handle large workloads. Meanwhile, those who refuse to adapt find themselves at a disadvantage. It’s similar to the early days of the internet when those who learned how to use email, search engines, and websites had a clear edge. AI is the new frontier, and those who adapt quickly will likely flourish.
My Path to Using AI: No Technical Knowledge Required
I write about pretty technical topics in AI and I think it’s natural for folks new to AI to worry that you might need a PhD in computer science to succeed with AI. The reality turns out to be far simpler. Modern AI tools often have straightforward interfaces. Sometimes it’s just a text box where you type a question. Let me walk you through some of the tools I’ve experimented with and how they fit into my day-to-day routines.
The first time I tried ChatGPT (developed by OpenAI), I simply opened up a website, typed a question, and got an answer. That’s about as simple as it gets. I started by asking it a quesetion about a book I’d been reading. It immediately gave me a coherent answer. That inspired me to ask more about professional topics—what does ChatGPT know about product management? We had a great conversation and I got a sense of how much ChatGPT knows about my own job discipline.
Another tool I looked at was Claude, made by a company called Anthropic. I found that Claude felt more like a personable writing partner that could keep a conversation going. If I wanted to think through a problem, Claude is an AI “personality” I feel like I can chat with because Claude makes ideas so accessible and relatable. Claude also saves me hours of effort getting to quick visuals of stuff I’m working on, because it can just code something in a language called React and show me how a webpage would look.
Then there’s Perplexity AI, which is great when I need reliable sources for my research. Unlike some other AI tools that just give me an answer, Perplexity actually cites the sources, which helps me verify the information it’s providing. That level of transparency is important to me, because it means I can check and see what sources I trust from the search.
Those three are just a start. Image generation tools like Midjourney have also entered my toolkit. Midjourney can create original images based on text prompts, which is mind-blowing if you need illustrations or concept art quickly.
When I integrate these tools into my workflow, I try to focus on areas where AI’s strengths—like information processing and a second opinion—can complement my human abilities—having purpose, a goal, and judgement. For example, if I’m stuck on a design concept, I’ll prompt Midjourney to produce some quick mock-ups, then I’ll pick the one that resonates with me and refine it. It cuts my ideation time drastically and gives me a springboard for creativity I wouldn’t have had otherwise.
Going Deeper: My Take on Prompt Engineering
One aspect of using AI that I’ve learned to pay special attention to is how I phrase my questions or requests. This is sometimes called “prompt engineering,” a term that might sound fancy but really just means “ask better questions, get better answers.” In the beginning, I’d type short prompts like “Write me a summary of AI” and wonder why the result felt generic. Eventually, I discovered that a bit more detail leads to a much richer output.
Here’s an example. If I want AI to generate a product description for a fictional coffee brand, I don’t just say, “Write a description of coffee.” Instead, I might say, “Pretend you’re a marketing writer at a boutique coffee roaster. Write a product description for a new dark roast blend that tastes like dark chocolate and caramel, using a warm, friendly tone, and aim for about 150 words.” Suddenly, the AI’s response is more focused, on-brand, and hits the word count I need.
I’ve found that the more context, constraints, and examples I provide, the better the result. It’s like giving directions: if you just say “head north,” you might get lost, but if you say “go north for three blocks, then turn right at the big oak tree,” you’ll probably end up exactly where you need to be. In other words, it pays off to know where you want to go with AI!
Common Pitfalls I’ve Encountered (and How I Avoid Them)
While AI has been a game-changer for me, I’ve also stumbled upon some pitfalls. The first is the issue of AI hallucinations, where the system confidently spits out false or misleading information. I’ve had chatbots cite academic papers that don’t exist or provide “facts” that are completely fabricated. It can be tricky, because the AI often presents these bits of misinformation in a very self-assured tone. My strategy to mitigate this is to always cross-check vital information, especially if it has real consequences. If I’m going to reference something in an article or a presentation, I take the time to verify it with a reputable source. I also remember that this problem is getting better over time! Leading models are now down below 1% on hallucination rates, so it is unusual.
Treating AI as magic is also a pitfall! People can assume an AI can do more than it really can. I’ve seen someone who has never coded before try to build an entire iOS app in one prompt. It doesn’t really go super well, although the building tools we use (like Lovable) are getting better and better at going further with brief prompts. It’s easier than ever to do incredible things like build apps, but it still pays to think about how to structure your asks in ways the machine understands, and that means taking time to learn how LLMs perceive prompts.
Another common issue is privacy and data security. Some AI tools store your queries and data, which might be a deal-breaker if you’re working with confidential information. I’m cautious about what I input into AI tools, and I read their privacy policies when sensitive information is at stake. It’s definitely worth doing a bit of research before handing over any proprietary data. You can see a summary of privacy policies here:
Glimpses into the Future: What I’m Watching For
As I keep an eye on AI developments, I see a few trends that really intrigue me. One is the emergence of AI agents that can not only generate content but also take actions on my behalf. Imagine an AI that doesn’t just recommend the best flight but also books it for me, adds it to my calendar, and arranges my airport pickup without me lifting a finger. That might sound super convenient, but it also raises questions about trust and control. Who’s liable if an AI agent makes a mistake? How do we prevent malicious actors from hijacking these systems? We’re all going to find out how reliable these agents are, because consumer-side agents are going to be widely available by 2026.
I’m also curious about AI’s expanding creative and emotive capabilities. Already, AI can generate short stories, poems, and pieces of music that are not amazing but certainly viable. ChatGPT 4.5 is an emotional and empathetic model that you can trust for interviews and private conversations. It’s very helpful. We’re in a position in 2025 where we have models that are demonstrating many of the qualities we would call human without _statefulness—_which is a fancy way of saying the AI doesn’t remember much about you between chats. So you can have a work conversation in one chat and an emotional conversation about a breakup in another chat and it’s not going to feel like the same AI.
Finally and on a more optimistic note, I’m hopeful about the ways AI can tackle complex societal challenges—things like climate modeling, disease diagnosis, and resource allocation. AI’s ability to analyze massive datasets and detect patterns could give us insights into problems that have eluded us for decades. For instance, an AI system might identify new, more efficient ways to distribute energy or predict how a new virus might spread, allowing us to contain it more quickly. I think the first AI-created drug is going to hit the market in the next couple of years, probably targeted at cancer. And that will be a big deal!
Final Thoughts: My Advice for Getting Started
As someone who’s explored various AI tools, learned from mistakes, and integrated these technologies into my personal and professional life, I have a few parting thoughts. First, don’t be intimidated by AI’s seemingly complex underpinnings. You don’t need to understand the math behind neural networks to benefit from them. If you can type a question into a search bar, you can use AI. Start small. Pick a task you already do—maybe writing a brief report, answering customer service emails, or planning a social media post—and see if an AI tool can help you do it faster or better. If you’re confused about how to do something with AI, ask AI. Yes it really works.
Second, remain curious. The AI landscape evolves quickly, and new tools, updates, and breakthroughs appear almost weekly. You don’t have to chase every new trend, but staying somewhat informed can help you spot opportunities that fit your goals. Treat AI as an ongoing learning journey rather than a one-time thing you set and forget.
Third, don’t turn off your critical thinking skills. AI can provide quick answers, but it can also produce misleading or incorrect ones. Learn to evaluate its outputs. If something seems off, do some old-fashioned fact-checking. If you see signs of bias or if the content produced feels ethically questionable, dig deeper. It’s our responsibility to make AI work for the betterment of everyone, and that starts with each of us being vigilant and responsible.
Lastly, embrace the fact that AI is here, and it’s not going anywhere. It’s the next stage in the evolution of technology, akin to how the internet revolutionized communication and commerce. Rather than resisting it, lean into the possibilities it offers. You might find it opens doors to new career paths, creative pursuits, or insights that you never could have imagined otherwise.
Thanks for reading! I hope my experiences and thoughts give you a clearer, more grounded understanding of what AI is, what it can and can’t do, and how you might use it in your own life. If you walk away with nothing else, let it be this: AI is a tool, not magic, not a looming apocalypse, and certainly not a replacement for the human spark that drives our world forward. With a bit of curiosity, a willingness to experiment, and a dose of healthy skepticism, you can harness AI to make your life easier, more creative, and perhaps even a little more fun. And in my book, that’s reason enough to start exploring today.
For more on AI, subscribe and share!
Subscribed
A little bit Studio Ghibli
