Intro
Originally, I thought this week’s log would focus on the difference between open and closed source AI models. That was the plan after listening to episodes 4, 5, and 6 of The Artificial Intelligence Show.
But once I started digging into some new creators on YouTube, things took a turn. (You’ll find that list at the bottom.)
Instead of staying in the high-level debate zone, I went looking for something to help me build real fundamentals. That led me to Ronnie Sheer’s Introduction to Prompt Engineering for Generative AI course on LinkedIn Learning.
Since I’m a full-time college student working toward a BS in Digital Marketing at Full Sail University, I’ve got full access to that platform. That’s going to help a lot as I get deeper into this.
Still, I know not everyone has access to LinkedIn Learning. That’s why I was especially glad to come across SuperHumans Life on YouTube. A random video turned out to be an unexpected goldmine.
What I Explored and Where I Found It
I’ve done a lot of thinking about my current and future situations lately. I don’t see a world where AI isn’t a big part of me achieving my goals someday.
To that end, I put my focus on two things this week: foundational skills and the voices shaping the conversation around AI. After listening to those three episodes I mentioned, Ronnie Sheer’s course was my starting point.
Thankfully, the course doesn’t waste time pretending you already know the basics. It actually gave structure to something I’ve been winging on instinct…
How to talk to AI in a way that gets results.
One takeaway that immediately clicked was the idea of using delimiters to help guide model output more precisely. In prompt engineering, delimiters are just clear markers you use to set boundaries in a prompt. Stuff like triple quotes, brackets, or anything else that separates one part of your input from another.
They help the model keep things straight so it doesn’t get confused or mash everything together. Think of them like guidelines that keep your prompt from going off the rails.
It’s the kind of simple prompt trick that can separate randomly chatting with a bot from actually getting work done. Another trick was letting the AI ask you questions. I hadn’t thought of that as a strategy, but how much sense does that make?
Turns out, if you don’t know what you’re trying to get, the model won’t either. But it can help if you just tell it to ask.
While I was working through the course, I also kept going down the rabbit hole on YouTube. I’ve got a long commute, so I’m constantly on the lookout for good long-form content. It turns out that the AI creator space is getting a little crowded and there’s gold in them thar hills.
What I Learned and How It Clicked
Overall, it turns out most of my prompting habits were a mess. I’d get decent results sometimes, but I was basically guessing every time I typed something out. Ronnie Sheer’s course helped me realize I’ve been treating AI like a vending machine when it’s closer to… a negotiation.
The biggest thing that stood out was just how much clearer and faster everything gets when you slow down and actually think about what you’re asking. Not in a vague, “let me brainstorm” way.
I’m talking about writing prompts that make sense, lay everything out, and leave no room for AI model confusion.
Learning how to give the model examples inside delimiters made a big difference. So did telling it to ask questions if it doesn’t have enough to go on. Sounds obvious, but I wasn’t doing that. I was just tossing stuff in and hoping for the best.
Now, I’m starting to see what “good” prompting actually looks like. You have to be clear about giving the model something solid to work with and getting it to work with you if you’re not certain of what your end product needs to be.
Like Stephen R. Covey said in a totally different context, “Begin with the end in mind.”
AI Terms
Machine Learning – At its core, machine learning is when a computer learns patterns from data and uses them to make predictions or decisions without being told exactly what to do. Think of it like teaching your dog tricks by rewarding behavior. The more examples it sees, the better it gets.
Deep Learning – This is a type of machine learning that uses something called artificial neural networks to solve problems. Basically, it mimics how the human brain works. Only way faster and without the need for naps. It’s what powers stuff like image recognition, voice assistants, and AI models like ChatGPT.
The “Special Differentiating Factor”
This week’s turning point wasn’t a course or a case study though. It was a single line from a YouTube video about real AI applications that had me scrambling to take a screenshot for the time stamp.
“AI is not here to replace you. It’s here to remove every excuse that you’ve ever had.”
— SuperHumans Life, “How to Become a One Person Business in the AI Age” 12:42
That quote didn’t just land for me. It flipped a switch. I’ve been looking at AI as something to learn and keep pace with. But this made it personal.
I’ve got goals that I’ve been putting off for years because the process always felt too slow, too murky, or too dependent on tools I didn’t even know existed, let alone had.
I started my BS in Digital Marketing in November of 23, hoping to make myself a better provider for my kids. Thankfully, Full Sail prides itself on “real world education,” so they’ve been prepping students like me for the changes that AI is bringing, but there’s still been that fear in the back of my mind.
What if I’m earning this degree, taking on a lifetime supply of debt, and then, when I finally do earn that piece of paper for all this effort, there’s no jobs for someone trying to change careers in their late 30s?
The thought has lived rent free in my head for months. I needed someone to tell me exactly what Laura from SuperHumans Life told me in her video.
AI isn’t here to replace people. It’s here to make life easier for people willing to put in the work.
And that’s what made SuperHumans Life stand out this week as a channel. The content isn’t “rah-rah” hype. It’s filled with walkthroughs, templates, resources, and links to free certifications that feel like someone wants you to move. Not just think. Not just plan. Move.
I needed that. And I’m going to use it.
That’s this week’s SDF. Not just a great quote, but a shift in how I’m measuring the flow of value in and out of my life. In this blog, I’m here to provide value while gaining new skills. SuperHumans Life impressed me because I think they’ve got the same philosophy.
Creators I’m Now Following
Each week, I’m going to spotlight some of the creators and educators helping me learn, think deeper, or explore the possibilities of AI. This week’s list is YouTube-heavy, but packed with insight, strategy, and just enough energy to keep me moving.
Focuses on practical prompt engineering, hands-on tutorials, and LinkedIn Learning content that makes generative AI accessible to total beginners. Clean, focused delivery with strong teaching fundamentals.
Walks through current AI tools with solid pacing, clear use cases, and honest breakdowns of what’s worth your time (and what’s not). The kind of channel you binge without realizing it.
You already know TED. They’ve been hosting thought leaders across every discipline for years, including some of the most grounded and ethical takes on AI I’ve come across.
This week’s MVP. Laura’s videos don’t hold back. She drops links, templates, free certifications, and no-BS strategies you and I can use today. As mentioned earlier, she’s the reason this week’s SDF section exists.
Next Steps
Now that I’ve got some actual structure behind my prompting, I’m planning to rebuild my templates and processes with more intention. No more winging it and hoping for decent output. I’ll be using delimiters and letting the AI ask questions to tighten up how I work with this tool from now on.
I also want to dig deeper into the resources Laura linked in that video. I’m going to copy her list and post it below, along with a link to her video. If you’re reading this, you’re probably at a similar place in your AI journey as me. That means you’ll almost certainly benefit from her content too. Go check it out.
Some of those links and courses look like hidden gems, especially the free certifications and walkthroughs. I earned my first certification through Ronnie Sheer’s course, but I’m hungry for more.
I’ve already bookmarked a few to tackle next week, but I’m prioritizing anything tied to content strategy, automation, or building systems I can actually use, not just admire.
Most importantly, I’m done treating AI like a cool toy. I’m building habits now that will actually move the needle. After all, if this stuff is supposed to remove my excuses, then I’m officially out of reasons to stall.
Conclusion
If you’re still thinking of AI as a novelty, cool. Keep poking it with a stick and see what happens. I did that for months. But this week made something snap. Not in a breakdown way. More like a “bone finally setting right” kind of way.
That quote from Laura wasn’t inspiration. It was a dare. What’s my excuse now? I’ve got tools. I’ve got knowledge. And I’m building momentum here. So, the only thing left to do is move.
Go watch her video. Grab one of the certs. Rip apart your old habits and build something better. I’m doing it. And I’m not going to pretend I’ve got it all figured out.
But I’ll leave you with this—
What’s the thing you say you want to do?
Now, what’s the reason you haven’t?
And, most importantly, is that excuse still valid?
Didn’t think so.
If you’ve got thoughts, challenges, or a certification you think I should take next, I’m all ears. Drop a comment.
We’re all figuring this out in real time. Might as well figure it out together.
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