When we talk about AI in software development, there are two types of people: those who think AI is the end of everything and those who believe that with a couple of prompts, we'll all become software engineers. Spoiler: both are off track. The reality, as usual, is more complicated. Let's give a virtual slap to the clichés and see where the truth lies.
The Myth of the Perfect Demo
Key concept: Never confuse a failing demo with the ineffectiveness of the technology. Remember when Google and Cognition did those AI demos and everyone cried failure? Oh, Devon AI didn't solve the world's problem? What a surprise! Demos like those are like movie trailers: they make you think it will be a masterpiece and then you end up with a plot full of holes. But judging the entire technology from a demo is like saying Italian food sucks because you ate a frozen pizza. The real progress, outside the showcase, is what counts.
Why do we continue to measure AI by spectacular demos, when even Hollywood movies fail with million-dollar special effects?
Some Ideas: AI in Action (without tricks)
- Automate documentation and tests without touching a line of code (and no, it's not magic).
- Generate diagrams and sequence diagrams without spending hours drawing cubes and arrows.
- Automatic code refactoring to make software more readable (many human developers can't even do that).
The real issue is not whether AI can do everything perfectly today. The question is: how do we use what it can already do? Those who stop at the first failed demo are like someone who doesn't want to learn to cook just because they burned an egg the first time.
AI and Code: The Great Misunderstanding
One of the skeptics' favorite arguments is that AI doesn't generate quality code. Sure, there's no denying that, months ago, AI's output was still immature. But those who say it hasn't improved today must have been sleeping under a rock for the last six months. Here's the point: AI is not here to replace you, dear engineer, it’s here to make you faster and less stressed.
Key concept: It's the quality of the final work, not who wrote it. With the right prompting strategy, AI assistants not only write code, but they document it, test it, and make it look as if you were the genius behind it all. It's not perfect yet, but honestly, who among us writes perfect code on the first shot? Even humans need continuous reviews.
Have we really forgotten that good code doesn't mean "perfect" code, but code that works and can be maintained?
If machines can generate diagrams, refactor code, and manage tests, maybe we should stop underestimating them. The only thing preventing many from seeing real progress is the fear that someone might write better code than them. Spoiler: it will happen.
Conclusion: AI and Developers, United by Necessity
In the end, AI is not going to steal your job tomorrow. But it's accelerating and we can't pretend otherwise. The real challenge is learning to use it before someone else does. So stop looking at the future with fear and start getting ready. Or keep complaining about the Devon AI demo while your desk neighbor becomes an AI expert. The choice is yours.