Involved as we are in this crazy hurricane of AI new developments, it's starting to be quite common to hear of situations where people are able to ship something in half the time thanks to AI, but then struggle to explain how it actually works.
This is something absolutely new, something that is slowly emerging around us as AI becomes part of everyday development work. We are entering a new tech chapter where teams can build faster than they can fully understand what they’re building, and while that is for sure powerful, it also carries a true risk that almost no one is talking about, because the reality is that we may be outsourcing not just effort, but understanding itself.
And this is not an argument against AI, in fact it might be quite the opposite. It’s an argument for using AI with more awareness, because the real opportunity right now is not just speed, but leverage without losing depth. This is where the real advantage comes from in our days.
Traditional software development has always followed a well known rhythm that was actually the root of true learning. You basically learned the fundamentals, fought with complexity, made mistakes and slowly built intuition. Understanding came from real experience and from being forced to figure things out the hard way.
AI changes that learning curve dramatically, because in our days a developer can simply generate production ready code in seconds, debug issues with guided suggestions or build systems they have never built before, creating an scenario where what used to take days or weeks can now take only a couple of hours.
This is a great and extraordinary progress, but it also introduces a challenge that is easy to overlook, when we start to realise that we are moving from doing the work to delegating the work. And delegation, by its own nature, creates distance.
The more we rely on AI to fill in the gaps and do it all, the less friction we experience, and while friction is often seen as something to eliminate, it is also where real understanding is formed. Without it, it becomes possible to build something that works without fully knowing why it works, and this is dangerous.
In the short term, this feels like a superpower and of course nobody can say it does not come with tons of advantages. Thanks to that, projects can move faster, teams can deliver way more and ideas turn into products at a speed that would have seemed unrealistic not long ago. But the risks that come with it cannot be ignored, and with all of this new fantastic trends and capabilities we are at the same time starting to see that sometimes teams are starting to experience simple and small bugs that take far longer than expected to diagnose, simple changes that create unexpected side effects, or small hesitations in the code that bring almost unpredictable effects.
These of course are not new problems for any developer, but they become more common when systems are assembled faster than they are understood. What is happening is simple but important. Execution is accelerating faster than understanding, and that gap matters more than it might seem at first.
In software, understanding is not optional because it's basically what allows you to debug with confidence, to scale systems reliably and to make proper architectural decisions. Without it you are not truly in control and you risk being operating something that works, but only within boundaries you do not fully see or reach to understand.
Every major abstraction in software has created a similar dynamic. We've seen similar things before. Frameworks, as an example, made development easier but hid complexity. Cloud platforms removed infrastructure burdens but introduced new layers that few people fully really understand, and tools without code allowed more people to build but sometimes at the cost of deeper understanding.
And while not being something new, AI is simply the most powerful abstraction we have ever introduced because maybe the big difference is the speed at which it is changing everything. What used to take years of gradual adaptation is now happening in months, and that compresses the time we have to rebuild understanding.
It would be easy to frame this as a problem, but that would miss the bigger opportunity. AI is not making people less capable but it is actually giving capable people unprecedented leverage, and developers and teams who benefit the most are not the ones who rely on AI blindly, but the ones who combine it with strong mental models.
When a developer or a team is able to understand the fundamentals, AI becomes a tool they can really direct, refine and challenge. They can spot when it is wrong, adapt its output to the desired context, and move faster without losing control.
In that sense, AI is an incredible tool to amplify capacities.
The real risk in this landscape is not the technology itself but how passively it can be used, and there is a huge difference between copying and pasting an answer and engaging with it. One approach creates dependency over time, while the other builds capability.
Active use of all the AI tools at hand today requires a bit of effort, but it strengthens understanding with every interaction, and over time, that difference becomes significant and creates a very big competitive advantage.
The most effective teams are not, and should not be stepping away from AI. They should be simply becoming more intentional in how they use it. They should treat it as a collaborator rather than an authority, always question its outputs, refining them and using them as a starting point rather than a final answer.
They also should continue to invest in fundamentals even when it might feel unnecessary in the short term. They should value the ability to explain a system as much as the ability to build it, as they always did in the past. In the end, they should create small habits that keep understanding alive, whether that means pausing to ask why something works or taking the time to rewrite a piece of logic to fully grasp it.
What we thing should come up from all this new wave is a new kind of developer and a new kind of team, not one defined by how much they use AI, but by how well they integrate it into their thinking, and we think the future of our industry will not be shaped by those who use AI the most, but by those who use it with intention and understanding.
AI is one of the most powerful tools ever introduced into software development. It can accelerate learning, reduce problema and unlock levels of creativity and productivity that were previously out of reach, but as we said before, its real value depends on how we choose to use it.
If we allow AI to fully replace our thinking, we lose something essential. If we use it to enhance our thinking, we gain an advantage that compounds over time. As simple as that.
Because in the end, the real advantage is not just building faster. It is understanding what you have built and why it works.
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