[00:03] seconds. It would have taken you an hour to do the same. So, should you be to do the same. So, should you be worried? No, because AI solves the wrong problem. Here's what I mean. A manager says, "Our checkout process is slow."
[00:15] Junior developer goes to AI and asks, "Write me a code to optimize checkout feature so that it's not slow anymore." AI generates code. They deploy it, maybe a little bit faster, but still slow. Why? Because the bottleneck was not the
[00:31] code. Maybe it was a database design, like too many queries per transaction, or an inefficient query that was just slow. But, junior developer did not know how to check that. They just asked AI to optimize what they could see, which was
[00:44] the code. But, the developer who understands systems, instead of just focusing on one piece of the puzzle, what do they do? They go and trace the entire flow first. User clicks checkout, what happens? Well, front end sends data
[00:58] to back end. Back end validates payment, queries user database, queries inventory database, shipping database, updates order database. So, five separate database calls for one checkout. So, they realize the problem is not the code
[01:13] optimization, it's the architecture, how the queries are designed. So, they combine those queries in one, cache the inventory data, batch the updates, checkout latency is fixed. AI cannot do this because AI does not understand your
[01:28] specific system or the entire context of your application unless you provide it to it. It doesn't know your database structure unless, again, you give that talk to which, and it doesn't trace
[01:41] problems across your entire stack. You need to know to think about giving that input to AI. So, what this means is that the value is not writing code anymore because AI can do that now. It's understanding where the code fits, why a
[01:56] feature is complex, what the actual bottleneck is, how different parts of your system connect. So, AI is a tool, just like a calculator. Calculators are faster in math than you are, but you still need to know which calculation
[02:10] solves your problem. And same with AI and code. Do you know which engineers will thrive in the AI age? The ones who understand the complete system, because they will use AI to write code faster, but they know what to build and why. And
[02:25] our IT Fundamentals course teaches you exactly this type of system-level thinking. The complete software development life cycle, how components connect, how to trace problems across the stack, and how to know where to look
[02:40] for each issue, because that level of understanding makes you valuable, not knowing the syntax that AI can now generate faster than you can. So, if this resonates and you want to know more, all the information will be below.