Controversial opinion: AI coding assistants aren’t just changing how we code—they’re accidentally becoming the most effective therapy for impostor syndrome in tech.
I know what you’re thinking. “Another AI hype article?” Bear with me. This isn’t about productivity gains or lines of code per minute. This is about something more fundamental: how AI made me realize I wasn’t a fraud.
The Setup: 5 Years of Professional Self-Doubt
Picture this: 5 years into my career as a Software Engineer, working at companies like BDO Canada, shipping features used by thousands, mentoring junior developers, speaking at conferences. On paper, I was successful.
In my head? I was a complete impostor.
Every code review felt like an exam I hadn’t studied for. Every new project felt like I was about to be exposed as someone who just got lucky. Sound familiar?
Then GitHub Copilot entered my workflow six months ago. And something weird happened.
The Plot Twist Nobody Saw Coming
I expected AI to make me feel more replaceable. Instead, it made me feel more valuable than ever.
Here’s why this is mind-blowing:
AI Doesn’t Have Ideas (But I Do)
Copilot can autocomplete my functions brilliantly. It can generate boilerplate code that would take me 20 minutes in 20 seconds. But you know what it can’t do?
- Understand the business problem behind the code
- Make architectural decisions that scale
- Debug complex system interactions across microservices
- Communicate with stakeholders about trade-offs
- Mentor team members through technical challenges
Watching AI struggle with the exact things I excel at was like holding up a mirror to my actual skills. For the first time in 8 years, I could see what I brought to the table.
The “Collaboration Effect”
Working with AI feels like pair programming with a really fast, really knowledgeable junior developer. And here’s the kicker: when you pair program, you realize how much you actually know.
Every time I had to guide Copilot’s suggestions, every time I caught its mistakes, every time I provided context it couldn’t understand—I was proving to myself that I wasn’t just copying and pasting my way through my career.
The Uncomfortable Truth About Impostor Syndrome
Here’s what nobody talks about: Impostor syndrome isn’t just about self-doubt. It’s about not understanding your own value.
Most developers suffer from what I call “skill blindness”—we can’t see our own expertise because we’re too close to it. We focus on what we don’t know (there’s always more to learn) instead of acknowledging what we do know.
AI acts like a skill revealer. When you watch it excel at syntax but struggle with strategy, when you see it generate code that works but isn’t maintainable, when you find yourself constantly refining its output—you’re forced to confront the reality of your expertise.
The Data Doesn’t Lie
Since integrating AI into my workflow, I’ve noticed some interesting patterns:
My code reviews became more strategic. Instead of nitpicking syntax (AI handles that), I focus on architecture, performance, and maintainability. My feedback became more valuable, not less.
My debugging skills improved. AI-generated code fails in interesting ways. Debugging these failures made me better at understanding why code breaks and how to prevent it.
My communication skills became crucial. The better I got at prompting AI, the better I got at articulating requirements—a skill that transferred directly to working with human teammates.
The Productivity Paradox
Here’s the paradox that’s driving the impostor syndrome cure: AI makes you more productive by making you focus on what humans do best.
Before AI:
- 40% of my time: Writing boilerplate code
- 30% of my time: Looking up syntax and APIs
- 20% of my time: Actual problem-solving
- 10% of my time: Strategic thinking
After AI:
- 10% of my time: Writing boilerplate code (AI handles most)
- 5% of my time: Looking up syntax (AI knows it)
- 45% of my time: Problem-solving and debugging
- 40% of my time: Strategic thinking and architecture
Notice what happened? I’m spending 85% of my time on uniquely human skills now. And guess what? I’m actually good at those things.
The Skills AI Can’t Replace (And You Probably Have)
If you’re reading this and still thinking “but I don’t have any special skills,” here’s a reality check. These are skills I thought were “basic” until AI showed me they weren’t:
1. Context Switching Mastery
Jumping between a React frontend bug, a Node.js API issue, and a PostgreSQL query optimization problem requires mental models that AI just doesn’t have.
2. Requirement Translation
Taking a vague stakeholder request (“make it faster”) and translating it into technical solutions requires human intuition about business needs.
3. Code Empathy
Understanding why previous developers made certain decisions, reading between the lines of legacy code, and making changes that respect existing patterns—this is human intuition.
4. Failure Intuition
That gut feeling when something “doesn’t look right,” even when tests pass. The ability to predict where systems will break under load. This comes from experience, not algorithms.
5. Team Dynamics
Knowing when to push back on a technical decision, how to mentor without overwhelming, when to refactor vs. when to ship—these are human skills.
The Controversial Take: Embrace AI to Beat Impostor Syndrome
Here’s my controversial advice: Start using AI coding assistants not to replace your skills, but to reveal them.
Week 1 Challenge:
Use GitHub Copilot, Cursor, or Claude for all your coding tasks for one week. Pay attention to:
- What suggestions you accept vs. reject (and why)
- What context you have to provide
- What problems you solve that AI can’t
- What decisions you make that AI suggests incorrectly
Week 2 Reflection:
Write down every skill you used that AI couldn’t replicate. I guarantee the list will be longer than you expect.
The Meta-Realization
Here’s the meta-realization that changed everything for me: I was suffering from impostor syndrome about impostor syndrome.
I thought everyone else was supremely confident while I was secretly struggling. Turns out, watching other developers work with AI revealed that everyone is just figuring it out as they go. The difference between junior and senior developers isn’t confidence—it’s pattern recognition and decision-making speed.
AI doesn’t have patterns from 8 years of debugging production issues at 2 AM. AI doesn’t have the scar tissue from launching features that broke at scale. AI doesn’t have the intuition that comes from thousands of code reviews.
But I do. And if you’ve been coding professionally for more than a year, so do you.
The Future Is Human + AI
The uncomfortable truth about the AI revolution in programming: it’s not replacing human programmers. It’s revealing what human programmers actually do.
For years, we’ve defined programming as “typing code.” But programming is actually:
- Problem decomposition
- System design
- Trade-off evaluation
- Team coordination
- Business alignment
- Continuous learning
AI can help with typing code. It can’t help with being human.
The Call to Action
If you’re reading this and still battling impostor syndrome, I have a challenge for you:
- Start using AI tools in your daily workflow
- Pay attention to every time you guide, correct, or improve its output
- Document the decisions you make that AI can’t
- Realize that these decisions are your expertise
The goal isn’t to prove you’re irreplaceable (nobody is). The goal is to understand what you actually bring to the table.
The Bottom Line
AI didn’t kill my impostor syndrome by making me feel special. It killed my impostor syndrome by showing me what I was already doing—and helping me see that it was valuable.
You’re not an impostor. You’re just human. And in a world of increasingly sophisticated AI, being human is becoming more valuable, not less.
The future belongs to developers who can work with AI, not against it. But more importantly, it belongs to developers who understand their own value in that partnership.
So here’s to killing impostor syndrome with artificial intelligence. Because sometimes the best way to appreciate human intelligence is to work alongside something that doesn’t have it.
What’s your experience been with AI coding assistants? Has it changed how you view your own skills? Share your thoughts in the comments below or reach out to me on LinkedIn or Twitter. Let’s continue this conversation.
About the Author: Piyush Mehta is a Software Engineer at BDO Canada LLP, tech speaker, and open source contributor. When he’s not debugging production issues or mentoring junior developers, he’s probably overthinking the future of AI in software development. You can find more of his thoughts on technology and career growth at piyushmehta.com.
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