Impact = Core Skills × Ability to Use AI Tools
The flood of AI advancements has occupied much of my headspace as a software engineer over the past few years. But one development stands out: AI agents that work asynchronously. When GitHub Copilot can create pull requests from ticket descriptions, we’re witnessing a fundamental shift in software development.
The question isn’t whether this is impressive—it clearly is. The real question is: How can software engineers thrive during this transformation?
The Multiplication Effect, Not Replacement
Despite fears about AI replacing jobs, I believe we’re looking at this wrong. AI won’t replace software engineers—it will amplify them. The ability to leverage AI effectively is becoming a crucial complement to existing skills, not a replacement.
Impact = Core Skills × Ability to Use AI Tools
This formula reveals something important: AI multiplies your existing capabilities. Strong engineers who learn AI effectively will see dramatic impact increases. Senior engineers have the most to gain—and potentially the most to lose if they ignore this shift.
Core Skills Remain the Foundation
AI skills don’t replace fundamental engineering competencies. To grow as a software engineer in the AI era, you still need core skills like troubleshooting, writing clean code, designing robust architectures, and developing senior-level technical intuition.
These skills become even more valuable when working with AI. Your ability to read and evaluate code directly impacts how efficiently you can work with AI-generated solutions. You need to quickly assess whether an AI agent’s output is correct, maintainable, and architecturally sound.
The Stamina Advantage
As AI automates grunt work—boilerplate code, repetitive debugging, routine refactoring—the physical and mental stamina that often limits experienced engineers becomes less critical. Seasoned engineers can focus their energy on high-level problem-solving, architecture decisions, and mentoring, where their deep experience provides irreplaceable value.
Preparing for the Future
The path forward isn’t about choosing between traditional skills and AI—it’s developing both in parallel.
Double down on fundamentals. Your core skills determine how much you can multiply your impact with AI. The better engineer you are without AI, the more powerful you become with it.
Start experimenting now. The learning curve for effectively using AI in development is steeper than it appears, and early adopters will have a significant advantage.
Focus on the human elements. As AI handles routine tasks, skills like system design, technical leadership, and cross-functional collaboration become even more valuable.
The AI revolution isn’t coming—it’s here. Engineers who understand this shift as amplification rather than replacement will define the next era of software development.