AI engineering is web development all over again.
The same cycle that made web dev the path into tech is repeating with AI. But the tools are better, the learning curve is different, and the ceiling is way higher.
In 2015, 2016, and 2017, web development was the most visible path into tech around me. Bootcamps taught HTML, CSS, JavaScript, and React. YouTube filled with short React tutorials, and front-end listings were everywhere.
In 2026, the tutorials and job descriptions I see are centered on AI agents. My own inbox changed too: nearly every recent brand inquiry I received involved AI.
I built a 156,000 subscriber YouTube channel teaching web development. And I'm sitting here watching the exact same cycle repeat itself. The pattern looks familiar, but the learning process has changed.
The Cycle Is Repeating but It's Not the Same
Back in the web dev era, the path was clear. Learn HTML. Learn CSS. Learn JavaScript. Build websites. Get a job. Bootcamps sold you that dream. "Learn to code, get a six figure salary in six months." And honestly? It worked for a lot of people. It worked for ME.
The old sequence no longer maps cleanly to the work. AI can generate syntax and scaffolding before a beginner understands either one. That makes fundamentals more important to verify, even when they take less time to produce.
The cycle is repeating, but AI participates in the learning process. I can ask about unfamiliar code, generate a first attempt, break it, and keep questioning it without waiting for the next tutorial. That speed helps only if I check what it produced.
I learned that boundary the stupid way. I told an agent to give my friends unlimited access to my study app. It hardcoded the bypass directly into the application. The code worked exactly as requested and was still a bad implementation. I had to know enough to catch it.
I Stopped Making Web Dev Content
I'm going to be honest. There's a reason I stopped making web development videos for like six to twelve months. I thought my job was going to get replaced. I was genuinely worried. And I didn't want to push people to get a job in tech when I wasn't even sure WE would have jobs in a couple years.
But while I was waiting to see where tech was going, I started using AI. A LOT. More than the average person. I prefer coding with AI over gaming now. World of Warcraft just came out with a new expansion, Midnight, and I chose coding over that. If you know me you know that says a LOT.
Instead of making another "how to center a div" tutorial, I started sharing failures from my own AI projects and the identity questions they raised for me. My highest-performing video is not a React tutorial. It is about that identity crisis. The response showed me that other developers were wrestling with it too.
Nobody Knows What an AI Engineer Actually Is
The title AI engineer currently covers too many jobs: model work, application engineering, retrieval, agents, infrastructure, and product integration.
For the roles I care about, a working system gives me more to discuss than another certificate. I can show the architecture, the failure, and the decision I made after it.
Look at my path. Six months ago I built my first AI app. Super basic. All it did was transcribe speech to text in any text input on the web. Then I built a journal app. Then a study app. Then I built my own three layer AI memory architecture system with vector embeddings, fact validation, auto categorization, superseding logic. It got COMPLICATED. But I got there because I started simple and kept building.
Python and TypeScript helped me build these applications, but the useful proof was the application itself. It gave interviewers something concrete to question.
I Had To Learn The Vocabulary By Building
Web development was the great equalizer. No degree needed. Self taught friendly. YouTube and free resources everywhere. That's how I got in. That's how a LOT of you reading this got in.
The vocabulary slowed me down at first: embeddings, vector databases, fine-tuning, RAG, GraphRAG, and hybrid search. I could repeat some definitions without knowing when I would use them.
That's actually one of the reasons I built my AI study app. There were SO many things I didn't fully understand. What even IS a vector database and why is it different from a graph database? Why does vector search matter? What's the difference between a 3072 dimension embedding and a 512? What's full text search versus hybrid search? I had ten years in tech and I STILL needed to go deeper on all of this.
So I built an app that quizzes me out loud. If I cannot explain why I chose vector search over a graph query, it keeps asking until I can.
I did not learn the vocabulary first and then build. The project forced me to learn each term when I reached the decision it described.
What Changed In My Work
Building forced me to make model choices instead of reciting model names. I used a smaller model for cheap background work, a stronger one where reasoning mattered, and rejected one after it invented details in sensitive data. Those choices affected latency, cost, and trust.
What About the People Still Grinding Web Dev?
I know some of you reading this are still learning React. Still grinding CSS. Still trying to break into web dev. Should you keep going?
Yes. Keep learning React and CSS, but use an AI coding tool on a real project and review every change it makes. The value is not typing fewer characters. It is reaching decisions you could not reach from another tutorial.
Web development is still the base of most of what I build. The difference is that the application now includes models, retrieval, evaluation, and tool boundaries. I did not leave web development; I added another system to it.
Why This Held My Attention
I ignored plenty of previous trends because I could not find a problem I wanted to solve with them.
AI held my attention because I was already using it to build software I use every day. RecallMEM, Speak2Me, and my study tool gave me specific failures to solve instead of a market story to repeat.
What I Do Now
AI engineering reminds me of web development's earlier years: the vocabulary is unsettled, the tools change quickly, and a working project can teach more than a polished learning plan.
After years in front-end engineering and DevRel, building these apps pulled me back into databases, embeddings, background jobs, and architecture decisions. I caught up by working through failures in public.
My standard now is simple: ship something I can explain, including the parts the agent wrote and the parts I had to fix.
Questions about this post? Ask the terminal on my homepage — it knows this whole site.
