When people ask me how to grow in AI, I see the same look in their eyes. It's excitement mixed with overwhelm. They know AI is important. They've probably tried ChatGPT or Claude, maybe even used it to brainstorm ideas or draft some content. But they're stuck in that familiar place—using someone else's tool with someone else's settings, wondering how to move beyond the basics.
I get it. You open a chatbot, type in a prompt, and get back something useful. It feels like magic at first. But after a while, you start bumping into limitations. The responses aren't quite what you need. You can't save the workflow for next time. You can't connect it to your actual work systems. You're stuck copying and pasting between tabs, feeling like there should be a better way.
There is a better way. But it requires shifting from being someone who uses AI to someone who builds with AI. That shift isn't as big as you think, and it doesn't require becoming a programmer.
The Four-Legged Stool
I think of AI growth like a four-legged stool. If one leg is missing, the whole thing wobbles. The legs are API, Markdown, JSON, and JavaScript. None of them are exotic or reserved for engineers. They're just the practical foundations that let you move from being a passive user to someone who can actually build with AI.
Here's what each leg gives you:
API opens the door
Instead of being limited to what someone else put in a chatbot interface, you get direct access to the AI's capabilities. You can control how it behaves, automate repetitive tasks, and connect it to your existing tools.
Markdown brings order to your knowledge
Most company information lives in long documents and presentations that AI struggles to parse effectively. Markdown gives your content structure that both you and AI can work with cleanly.
JSON gives you precision
Instead of getting back paragraphs of text you have to interpret, you can ask AI to return information in specific, predictable formats that your systems can use directly.
JavaScript makes things happen
It's the bridge between AI's responses and the places your learners or customers actually see them—whether that's in a course, on a webpage, or in an app.
Together, these four skills move you from someone who prompts AI in a browser to someone who can integrate AI into real workflows. You stop bouncing between disconnected tools and start building experiences that actually match how you work.
Why This Matters Now
The L&D and marketing fields are at a crossroads. We can keep bolting AI onto our existing systems—AI-powered LMS dashboards, smarter SCORM modules, better analytics—or we can recognize that AI opens up entirely new possibilities for how learning and engagement actually happen.
I've seen what happens when people make this shift. A trainer builds a help desk that answers learner questions automatically. A marketer creates a system that personalizes email campaigns based on real behavior patterns. An instructional designer develops adaptive learning paths that adjust in real time.
These aren't massive enterprise projects requiring teams of developers. They're small, practical applications built by people who learned to work directly with AI instead of through someone else's interface.
What You'll Learn
Over the next five posts, I'm going to walk you through each leg of the stool. We'll start with API because it's the foundation that unlocks everything else. Then we'll add Markdown to structure your knowledge, JSON to organize AI responses, and JavaScript to connect everything together.
In the final post, I'll show you exactly how to build your first AI-powered project—something small and practical that you can complete in an afternoon but that demonstrates all four concepts working together.
Each post builds on the previous ones, but I'll keep the examples concrete and the explanations grounded in real work you're probably already doing. You won't need to learn programming languages or master complex frameworks. You'll just need to understand what each tool does and how to ask AI to help you use it.
Who This Is For
This series is for the overwhelmed colleague who knows AI is important but doesn't know where to start. You've probably experimented with AI tools, but you're ready to do more than just prompt and hope. You want to integrate AI into your actual work processes, not just use it for brainstorming sessions.
Maybe you're in L&D and you're tired of building the same static courses over and over. Maybe you're in marketing and you want to personalize experiences at scale. Maybe you're in operations and you see opportunities to automate routine tasks that eat up your time.
If you've ever thought "there has to be a better way to do this," and you're willing to learn four practical skills that don't require a computer science degree, this series is for you.
What This Series Will Give You
These five posts are about removing the intimidation. AI isn't magic, and it isn't reserved for engineers. It's a set of tools that work together in predictable ways. Once you understand how those tools connect, you'll have options you don't have now.
Will you become an AI expert after reading these posts? No. But you'll understand the landscape well enough to make informed decisions about what's worth pursuing and what's worth skipping. You'll know when someone is overselling a solution and when they're pointing toward something genuinely useful.
Most importantly, you'll have a foundation. Whether you use it to build small automation scripts, to evaluate AI tools more effectively, or to have better conversations with technical colleagues, you'll be starting from solid ground instead of guessing.
Not everyone who reads this series will become a builder. That's fine. But everyone who reads it will stop seeing AI as a black box. And that understanding, by itself, is valuable in a world where AI is increasingly part of how work gets done.
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