"As my AI usage goes up my imposter syndrome goes up. Also you lose the sense of pride, right? I mean I used to be so proud of myself when I figured out something tricky and now I can just give that away to AI (and may even be encouraged to)."

This perspective hit me hard. It's all I've thought about for the last 12 hours.

The Pride Shift

Pride used to come from solving hard problems through sheer coding skill. The ability to write complex code from scratch was the badge of honor. With AI, the source of pride has shifted. Now it's about building something valuable, and the skill is architecting solutions and guiding AI effectively.

Think of it like the transition from doing long division by hand to using a calculator. Pride in manual calculation gives way to pride in solving complex engineering problems. You shouldn't feel like an imposter for using a calculator. AI is simply the next level of that abstraction.

AI Doesn't Eliminate Hard Problems, It Shifts Them

AI excels at boilerplate code, standard patterns, syntax and API lookups, and common algorithms. But you remain critical for architectural decisions, problem decomposition, debugging AI output, applying domain knowledge, conducting code reviews, handling integration challenges, and identifying edge cases. You're still figuring out the tricky things. Just at a higher level of abstraction.

Reframe Your Wins

Instead of measuring success by lines of code written or algorithms figured out from scratch, shift your focus to outcomes. Did you ship a feature that helps users? Did you identify the right problem to solve? Did you catch a critical bug that AI missed? Did you design an elegant architecture? Did you make good trade-off decisions? Did you guide AI to produce production-quality code?

Shift from pride in process to pride in outcomes.

Understanding the Imposter Syndrome Loop

I understand why AI can make imposter syndrome worse. The logic goes: AI wrote this code, not me, so I didn't really do the work, therefore I'm not a real developer, and so I'm an imposter.

But let's reality-check that narrative. Did you know what to build? That's identifying the problem. Did you prompt AI effectively? That's communication skill. Did you review and understand the code? That's code literacy. Did you catch errors or improve the generated code? That's quality control. Did you integrate it into the system? That's systems thinking. Did you ship something valuable? That's execution.

If you answered yes to most of those, you DID the work. AI was your tool.

This Has Happened Before

The 1960s brought high-level languages. Skeptics said real programmers use assembly. Reality: it enabled more complex software.

The 1980s brought IDEs and debuggers. Skeptics said real programmers use vi or emacs (people still argue this). Reality: productivity increased.

The early 2000s brought Stack Overflow. Skeptics said real programmers don't copy and paste. Reality: knowledge was democratized.

The 2010s brought frameworks like React and Rails. Skeptics said real programmers build from scratch. Reality: faster iteration became possible.

The 2020s bring AI coding assistants. Skeptics say real programmers don't use AI. Reality: still being written, but likely positive.

Every generation fears the new tool. Every generation adapts. Skills evolve upward.

What Developers Who Adapt Are Saying

Developers who've embraced this shift describe feeling less like typists and more like architects. They take pride in designing systems that scale to millions of users rather than writing perfect binary searches. They recognize that the hard part was never syntax. It was always understanding what to build and why. Their value isn't in memorizing APIs but in judgment, taste, and knowing what good looks like.

Practical Advice for Growing Into This

Keep a "Wins Journal" to track contributions that AI couldn't make: catching security vulnerabilities in AI-generated code, designing data models that made features possible, debugging race conditions that AI couldn't see. Review this when imposter syndrome hits.

Balance AI use with manual practice. Code without AI help one day a week. Read the source code of libraries you use. Contribute to open source where you're forced to explain your thinking. This maintains your baseline skills and confidence.

Focus on what AI can't do. AI can generate code patterns, follow instructions, optimize locally, work fast, and know syntax. Only you can understand user needs, question assumptions, see the big picture, be creative, work thoughtfully, know the trade-offs, and be the decider.

Change your language. Instead of saying "AI wrote this code for me", which feels passive and imposter-inducing, try "I used AI to implement my solution faster" or "AI helped me explore options, I chose the best one." You are the driver, AI is the GPS. Language matters.

The Uncomfortable Truths

Was spending three hours debugging really something to be proud of? Was memorizing obscure API syntax really a valuable skill? Was writing boilerplate for the hundredth time actually fulfilling?

AI is removing the parts that felt like work but weren't actually valuable. The discomfort you feel might be realizing that some of what you were proud of was actually busywork, or adjusting to a new definition of "skilled," or mourning a familiar way of working. That's normal. It's also growth.

Combat Imposter Syndrome by Teaching

Write blog posts about how you solved problems (with AI!). Mentor junior developers. Explain your decisions in pull requests. Give lightning talks about your approach. Teaching forces you to articulate your value beyond code generation.

Reframe the Question

Instead of asking "Am I still a real developer if AI writes my code?" ask whether you're delivering more value than before, solving harder problems than before, learning and growing, and making good decisions. If yes, you're not an imposter, you're evolving.

Looking Ahead: The Next 5-10 Years

Developers who embrace AI early, focus on high-level skills like architecture and product sense and judgment, become "AI-native" developers, and use AI to deliver ten times more value will thrive. Those who resist AI out of pride, cling to low-level implementation skills, become bottlenecks, and might struggle.

It's a choice.

A Final Reframe

"I'm not an imposter for using AI. I'm a professional for using the best tools available. My value is in knowing what to build, why to build it, and whether it's built well. AI helps me do that faster."

One More Thing

The developers who feel imposter syndrome about using AI are often the best developers. They care about their craft, have high standards, are self-aware, and want to earn their accomplishments. That's not imposter syndrome. That's integrity.

Channel that energy: become an AI expert, focus on higher-level skills, deliver more value than ever. You're not losing your skills, you're upgrading them.

That tricky problem you used to solve manually? You'll still solve tricky problems. They'll just be at a higher level of abstraction and more impactful.

The Bottom Line

Every tool changes what it means to be skilled. The alternative is to insist on being a blacksmith in the age of factories.

Embrace the change.