A friend of mine, bright, driven, and relatively new to programming, asked me a heavy question the other day. “Did I make a mistake? Did I choose the right career?”

The question hung in the air. It wasn’t born from a bad day or a frustrating bug. It came from a much deeper place of anxiety, one that I suspect many in our industry are feeling right now. They saw recent waves of layoffs, they read the headlines about Artificial Intelligence, and they felt the ground shifting under their feet. The promise of a stable, in-demand career in tech, which seemed like a sure thing just a few years ago, now felt fragile.

“I’m so early in my career,” they said, “I worry if I’ll even have a job in a few years. It’s hard to stay motivated.”

I had to be honest. I hear them. Loud and clear.

I’m no expert, and my perspective is limited to my own journey, roughly 28 years in the tech world, nearly 15 of those as a full time software developer. I’ve seen a few cycles of boom and bust, but I’ll admit, this moment feels different. When I first got access to GitHub Copilot a few years ago, I had my own panic. I’m in my 40s. Was I becoming a fossil? How could I keep up?

That initial fear, however, eventually gave way to something else, a fire. It was a rallying cry to push myself, to embrace my love for learning, and to continuously grow. It reinforced a mindset I’ve tried to cultivate over the years, to constantly work to make my current role obsolete, because in doing so, I’m constantly working my way into my next one.

This is the sober part of the conversation, the industry has pendulums. Companies hire like mad for whatever reason, and then they overcorrect with layoffs. It’s a stressful reality. Imposter syndrome, that nagging feeling of being a fraud, doesn’t go away. I still feel it. But over time, I’ve learned to reframe it. Instead of feeling overwhelmed by all the brilliant people around me, I now feel a sense of awe and a desire to learn from them. It’s fuel.

But what about the elephant in the room, AI? My friend’s biggest fear was that AI will simply do what’s expected of a more junior engineer, making their role disappear.

This is where my hope for the future comes in.

I don’t believe we’re heading for a world where artificial general intelligence (AGI) makes human ingenuity obsolete. Look closely at every major breakthrough, even those in AI-driven medicine. It’s still humans pointing the AI down the right paths. Human creativity is the spark.

What I see is a future where AI handles the grunt work, freeing us up to focus on the truly human part of creation: the next step, the novel idea, the new invention. If we don’t have to spend five years of our early careers doing repetitive tasks, that isn’t a threat, it’s a massive opportunity. It’s an acceleration of our potential.

This led me to a profound realization that now guides my work. We are all, collectively, building a giant, shared brain.

Every time you write a blog post, answer a question on a forum, or push a project to GitHub, you are contributing to this massive corpus of human knowledge. The next generation of AI models will ingest that information. Your solution, your idea, your unique way of explaining something, becomes part of the shared intelligence of our species. When someone else, somewhere else, asks a question that overlaps with something you shared, they’ll be able to build on your work.

We are not just leveling up ourselves when we write and share; we are leveling up all of humanity.

So, how do we thrive in this new world?

First, we must become masters of context. The effectiveness of AI hinges on the quality of the information we give it. I’ve started obsessively collecting my own context, transcripts, notes, ideas, with the goal of building a personal, searchable database that I can use to augment my own thinking and my interactions with AI.

Second, we must learn to be shepherds, not just button-pushers. For those of us who write code, this means getting exceptionally good at describing problems and guiding AI to generate solutions. For our colleagues in non-engineering roles, it means learning to see opportunities for automation and building the AI agents to handle them. We all need to adopt a mindset of invention.

Finally, we must guard against brain atrophy. We can’t let the tool do all the thinking. Use AI as an accelerator, a tireless research assistant, and a pair programmer, but never as a replacement for your own curiosity and ingenuity.

So, did my friend make a mistake choosing to be a programmer?

Absolutely not. The barrier to entry for creating things with software will get lower, but this doesn’t devalue the profession, it transforms it. The demand for people who can solve problems, think critically, and apply human ingenuity will be higher than ever.

The future of this career isn’t about being replaced by a machine. It’s about being amplified by one. Our challenge, and our great opportunity, is to learn how to contribute to that giant, shared brain and use its power to build things we can barely even imagine today.

Footnotes

1. Junior engineers are still essential (businessinsider.com)
2. Copilot boosts satisfaction and productivity (github.blog)
3. Copilot makes devs ~55% faster (arxiv.org)
4. Copilot improves speed, solution quality (arxiv.org)
5. Copilot training data includes public GitHub repos (linearb.io)
6. Large language models trained on Stack Overflow, GitHub, Wikipedia (arxiv.org)
7. Layoffs in 2023 hit 262,735 (techcrunch.com)
8. Tech layoffs in 2024 (fastcompany.com)
9. Over 62,000 layoffs already in early 2025 (nerdwallet)

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