We've lost our bearings. As software engineers and an industry, we're adrift in the AI disruption. But we can regain our sense of direction by looking to the lessons of our own professional history and the wider history of human technology.
I've been thinking a lot about the story of how we solved the problem of longitude at sea. It was a massive navigational challenge, that added to the existing practice of sailing, that was ultimately solved by a seemingly small piece of technology: an accurate clock. That story reminds us that truly transformational shifts in how humans operate, like being able to sail across the oceans, can come down to leaps in innovation.
The Problem with Extremes and Our Anxiety
A lot of the conversation around AI engineering tools sits at the extremes, but the most likely outcome is, as always, somewhere in the middle. By flapping around about best- and worst-case scenarios, we're missing a lot of what's important.
I've been in conversations where the same people express accidentally contradictory concerns. On one hand, they argue that AI assistants don't really speed us up because coding was never the bottleneck. They claim the tools aren't good enough anyway, so it doesn't really matter. Then, in the same breath, they worry about how new graduates will learn to code if AI is so good that they never have to do it themselves.
These viewpoints show that we're a bit at sea. They highlight the normal anxieties that come with major change. The fear of job displacement for experienced engineers—if the tool isn't good enough, it's a dismissive stance that says, "It won't affect me." Also fear of the unknown for the next generation—what happens to the junior talent pipeline if the fundamental skills change? Both are valid human reactions, but they can't both be true about the technology.
A Moral Panic About Thinking
It's also useful to remember that humans have a history of moral panic whenever a new technology affects how we think. Think about the introduction of books. Many people were concerned that because narrators/authors no longer had to construct arguments or repeat long narratives from their heads, and so the thinking went, books would negatively impact their ability to reason and think.
Do these tools change the way our brains work? Yes. But that was also true of books, and of the internet, and of search engines. Is it for the worse? I don't know, maybe. But in the long run, these shifts have raised the ceiling of what we can achieve.
This happens because the individuals and organizations that learn effectively are the ones that win. We've been too focused on execution and efficiency as the sole drivers of success lately. But organizations that figure out how to help their people learn, pick up new skills, and rewire how they work will be able to get products to market more quickly. Fundamentally, that's what drives success. We've known this for a while—it's a core tenet of research like The Fifth Discipline.
Learning from Our Past, Navigating Our Future
We can also look to our own profession for examples. Think about the introduction of compiled languages over directly writing assembly code. The criticism then was nearly identical to what we hear today: "The compiler will never be able to write this as well as I can. It's never going to be as efficient as I can make it. It's never going to be as correct as I can make it."
It's safe to say that history has declared a clear winner. We now have a towering stack of languages that sit on top of assembly. AI tools that write code are just another natural evolution of this trend toward higher levels of abstraction.
So, how do we navigate this new era? How do we, as experienced practitioners, bring the next wave of engineers along with us? How do we help our organizations adapt?
The principles are the same. We still need to pair, mentor, and give people projects that help them grow. But the mechanics are different. New engineers will be swinging AI tools more natively, more instinctively, and earlier in the process. We will have to learn along with them, and that's the uncomfortable part. But we've been through this before.
This disruption is large and it's certainly unmooring. But because we've been through this before, we do know how to navigate it.
It's time to go build our clock.