We're living through something extraordinary. AI as a general-purpose technology is reshaping everything. From the jobs that require human attention to our fundamental relationship with work itself.
As a software engineer, I've been wrestling with a question that keeps me up at night:
How do I find meaning and satisfaction in a world where the act of building has been fundamentally transformed?
The cognitive load is shifting. What used to happen in our heads is increasingly happening through AI. The mental work of translating ideas into code, debugging logic, and structuring systems. That's moving from human minds to machines.
So what's left for us? Perhaps it's premature to think about these things. Perhaps the best approach is to continue shipping, hit small milestones, and let the future take care of itself. But maybe not. Even Sam Altman, standing at the forefront of AI innovation, grapples with these questions. And if someone with his vantage point is thinking about meaning and purpose, then it's worth doing the work to define our own frameworks.
This isn't about fear. It's about intentional evolution.
The Question Beneath the Question
The surface question is: "Will AI replace software engineers?"
But that's not the interesting question.
The deeper one is: "What does it mean to be a builder when the cost of building approaches zero?"
For decades, being a software engineer meant mastering syntax, understanding architecture, and debugging complex systems. It meant the loop: see the problem, imagine the solution, manifest it, and see the impact.
AI is dramatically changing the "manifest it" part. So what remains?
The answer, I think, lies in recognizing that we were never really builders of code. We were builders of solutions. We were translators between human needs and technical execution. That translation layer (the judgment, taste, and vision) is more valuable than ever. But it requires us to evolve.
A Framework for Evolution
I've been thinking about this evolution in three phases. Not linear stages you complete and move past, but overlapping modes of being that you can strengthen throughout your career.
Lay down your foundation:
Identify your values and place in the world: What problems genuinely matter to you? What kind of impact do you want to have? These questions are no longer going to be philosophical luxuries. They're navigation systems in a world moving faster than ever.
Leverage AI in daily tasks: This isn't optional. Using AI tools like Copilot, ChatGPT, or Claude is now table stakes. But more importantly, it's about developing a taste for when to delegate to AI and when not to.
Measure everything in outcomes, not inputs: The old metric was hours coded or features shipped. The new metric is: Did you solve the problem? Did you create value? AI makes this shift mandatory because inputs (lines of code, time spent) are becoming less meaningful.
Amplification: Operating at Scale
This is where you multiply your impact by treating AI as a force multiplier, not a replacement.
Become an AI architect and solution engineer: The skill isn't just using AI tools. It's understanding how to compose them, when to use which model, and how to design systems that incorporate AI thoughtfully.
Build your personal agentic ecosystem: Set up AI agents that handle your repetitive work. Create systems where AI acts as your research assistant, code reviewer, or documentation writer. The goal is to operate at a higher level of abstraction.
Prioritize mental health strategy: Here's the paradox: AI lets you do 10x more, but your human need for rest hasn't changed. The gap between what you can do and what's sustainable is wider than ever. Burnout is a feature, not a bug, of AI-amplified productivity unless you actively design against it.
Practice communication relentlessly: As execution becomes cheaper, communication becomes more valuable. Can you explain complex technical decisions? Can you translate between technical and business stakeholders? Can you tell a story about why something matters? These skills separate good builders from great ones.
Influence: Shaping Direction
At this level, you're not just building with AI. You're helping determine what should be built and why.
Practice deep research and ideation: AI lowers the cost of execution dramatically, which means the bottleneck shifts entirely to vision. What problems are worth solving? What solutions would actually matter? Spending time in deep research and ideation becomes your highest-leverage activity.
Build an application-based learning ecosystem: The pace of change means you can't rely on knowledge that's 6 months old. Create systems for rapid learning: read research papers, build toy projects immediately, and share what you learn. The loop needs to be tight. Learn fast, apply fast, iterate.
Develop your personal brand and indisputable expertise: As AI commoditizes execution, your reputation and judgment become your moat. This doesn't mean becoming an influencer. It means building a track record of good decisions, clear thinking, and valuable insights that people trust.
Cultivate high judgment and intuitive decision-making: With AI, you can explore 100 solution paths quickly. But choosing the right path? That requires taste, intuition, and the pattern recognition that comes from deep experience. This is the skill that won't be automated away.
So what's next?
The honest answer is that nobody knows exactly how this plays out. We're all figuring it out in real-time. But I think there are a few principles worth holding onto:
AI amplifies what you care about. If you care about solving real problems, AI makes you more effective. If you're just going through the motions, AI will make that more obvious too.
The loop still matters. AI changes the "manifest" step dramatically, but your ability to see problems worth solving, imagine elegant solutions, and measure real impact? That's still profoundly human.
Meaning comes from agency, not activity. It's not about how much you personally type or how many lines of code you write. It's about whether you're making meaningful choices, exercising judgment, and steering toward outcomes that matter.
This framework isn't meant to be prescriptive. Your path will be different from mine. But I hope it provides some scaffolding for thinking about your own evolution.
IMO, the builders who thrive in the AI age won't be the ones who resist it or the ones who blindly embrace it. They'll be the ones who stay grounded in their values, amplify their impact thoughtfully, and help shape the direction we're all heading.