Why Your Mindset is the Ultimate Superpower Right Now

Hey there! 👋

You've seen the headlines, right? The constant back-and-forth about AI?

Lately, I feel like I'm seeing two main camps yelling past each other:

📢 Camp 1: "AI is taking over! Programmers are doomed!"
📢 Camp 2: "AI is crap! It hallucinates, generated code is full of security flaws, can't scale..."

Sound familiar? It feels very black and white, doesn't it?

But here's the thing I've learned, both from building with AI daily and from my decade in hardware development: That binary thinking is paralyzing.

The Hardware Lesson We Need for AI

In my "past life" when I was in the hardware industry, making a physical product was expensive and slow (it still is). Circuit design, firmware programming, enclosure engineering, certifications... a single mistake could cost months and a fortune. You can't just upload a "fix" as you can with a website, say.

So, what was the smart way?

Prototype. Test. Iterate.

Get something functional out fast, test it in the real world, see if the market actually wants it, and then refine it. Waiting for perfection meant never launching.

But crucially, in each phase, you needed to be acutely aware of what you had, what you didn't, and the limitations of your current tools and components.

And not just in hardware - this rapid iteration approach has proven successful across all industries. From software development to building startups and even traditional businesses. Time and time again, it proves better to start quickly with a minimal viable product and improve it based on real feedback, rather than spending months planning the "perfect" solution that might not even match market needs.

And guess what? AI is handing us the ultimate prototyping tool on a silver platter, but that same awareness is just as vital.

It's Not About the Tool, It's How You Use It

Forget the extreme hype and the extreme dismissal for a moment. Let's get practical.

Imagine two people trying AI coding tools:

• Person A (The Curious Explorer): Sees AI as a slightly flawed but powerful assistant. Asks: "How can this help me build something faster?" They jump in, experiment, guide the AI, fix its mistakes, and quickly build a working prototype or feature. They learn by doing.
• Person B (The Skeptical Perfectionist): Focuses only on AI's current flaws. Thinks: "This code isn't production-ready," or "This misses edge cases." They either dismiss it or get stuck trying to make the AI perfect before starting, ultimately building nothing.

Who's making progress? Who's learning the new way of working? 🤔

The difference isn't just skill. It's mindset.

Why THIS is the Golden Age for Beginners (Seriously!)

If you're new to tech or coding, listen up: This is your golden moment. 🎉

Seriously. AI is leveling the playing field like never before. The ground is shifting so fast that even agile startups are struggling to keep pace (don't even get me started on corporations!).

Think about it: new AI tools pop up almost daily. Teams, even small ones, can't just pivot their entire workflow overnight.

But you? As an individual? You can.

You can grab the latest AI assistant, the newest technique, and start experimenting today. You can build something using capabilities that big players haven't even dreamed of, let alone implemented. You don't need years of legacy knowledge; you just need to be quick and curious. That's your superpower right now. Take advantage of it! 😉

Your power right now isn't decades of experience. It's:

• Openness: No ingrained habits holding you back.
• Curiosity: A willingness to dive in and see "what happens if..."
• Speed: Leveraging AI to build and learn faster than anyone thought possible.

Forget waiting to be an expert. That definition is changing anyway. Start building now. Think of AI as your incredibly powerful partner.

Experienced Pros: Your Opportunity (and Challenge)

Been coding for years? Leading a team?

Your experience is invaluable. But clinging to only the old ways is risky. The challenge is simple, but not easy: Learn and experiment.

I get it. Change is uncomfortable. But think about it: when you onboard a junior engineer, do you expect perfect code immediately? No! You guide them, give them processes, review their work.

You can guide AI too. Treat it like a very knowledgeable, context-hungry junior dev you need to manage effectively.

Worried about security? Scalability? Bad practices? Good!

Use your experience to:

• Prompt AI with specific constraints: "Write this function using secure coding practices like X and Y."
• Give it context: Explain the system architecture.
• Set up processes: Use AI for drafting, but maintain rigorous code reviews and testing.

Saying "AI can't do X" sometimes translates to "We don't yet have clear processes to guide anyone (human or AI) to do X effectively." While directing AI well takes practice, the principle holds: AI often possesses a vast knowledge base; the key is guiding it with the right context and constraints.

Take What Works, Leave What Doesn't

Stop thinking "AI or nothing." Think "AI and..."

• Use AI to accelerate prototyping.
• Use AI to brainstorm solutions and critically evaluate them.
• Use AI to handle boilerplate code.
• Use your expertise to guide, review, and refine.

Know its limitations, work around them, and leverage its strengths. Don't let the fear of imperfection stop you from harnessing incredible power. Remember, many successful startups wouldn't exist if they waited for perfection or knew every obstacle upfront!

The Real Action Tip: Mindset First, Tools Second

More than any specific tool or technique, the most crucial step is adjusting your mindset and putting it into action. Today.

If you're a beginner:

• Fire up an AI assistant (ChatGPT, Claude, Copilot, whatever!).
• Approach it with pure curiosity. Ask: "How can you help me build [a simple website/a small game/a basic script]?"
• Follow its lead, ask clarifying questions, fix its mistakes, and keep going. Don't aim for perfection, aim for progress. (Just maybe don't try building a banking app on day one, okay? 😉)

Once again: Just be aware of what you have and what you don't.

If you're experienced:

• Pick a small, non-critical task or feature you need to implement.
• Before diving into your usual methods, talk to an AI. Explain the context ("I'm building X, need to add Y...") and your initial thoughts ("I was thinking of doing it like this...").
• Ask for its approach. Ask about potential pitfalls you see. Challenge it. Use it as a sparring partner.
• See if it offers a new perspective or speeds up even a small part of your workflow. Treat it like that very knowledgeable, context-hungry junior dev.
• Be transparent about your concerns. Tell the AI: "I'm worried about security/performance/maintainability." Ask it to address these specific concerns in its solution.
• Take small steps forward. Maybe start by having AI generate unit tests for your existing code, or ask it to review your architecture for potential issues before implementing anything new.

The goal isn't to replace your skills; it's to augment them.

The gap is widening between those experimenting and those waiting. Choose to be an experimenter.

 

Stay curious!

Primož

P.S. Know someone stuck in the "AI is crap" or "AI is the apocalypse" loop? Forward them this. Maybe shifting the focus to practical experimentation and mindset can help them get unstuck.