The Truth About AI for Coding: Two Fallacies and a Real-World Lesson

  • 9 Apr, 2025

Generative AI has reshaped how we think about building software—but not always in the right ways. In the rush to automate everything, two big (and opposite) fallacies have taken hold in tech circles:

Fallacy #1: CEOs think AI can replace software developers.

Fallacy #2: Developers think software built with AI is trash.

Here’s the reality: both are wrong.

And I say that as someone who actually built and shipped a product with an AI-powered team—zero human staff, just me and the tools. It worked, but not for the reasons many people think.

Let’s break this down.

🚫 Fallacy #1: “We Don’t Need Developers Anymore”

Some execs see AI as a way to cut engineering costs dramatically—why pay for full-time developers when tools like ChatGPT, Copilot, or Cursor can write code instantly?

“In 2025, at Meta and other companies working on similar advancements, we’ll have AI capable of functioning as mid-level engineers, effectively writing code. Initially, these AI systems will be expensive to operate, but over time, they will become more efficient. Eventually, much of the code in our apps, including AI-generated code, will be created by AI engineers rather than human engineers." - Mark Zuckerberg

Here’s the issue: AI can write code, yes. But code isn’t a product. AI still lacks the ability to understand business context, user needs, edge cases, tradeoffs, or long-term system design.

Replacing developers wholesale isn’t innovation—it’s a shortcut to tech debt.

That said…

What AI Can Do (When Used Right)

I put this to the test with Mio Vino, a mobile app inspired by a wine-tasting trip in Tuscany. I wanted to remember the wines, the stories, and the places that made the experience special. So I decided to build an app that could help people do just that.

Instead of hiring a full team, I used AI to handle everything:

  • Product management
  • UX design
  • Frontend and backend development
  • Database setup
  • Security reviews
  • Marketing copy

Yes, AI did all of that. But it only worked because I acted as the strategic layer—I knew what I wanted to build, how it should work, and how to break down tasks in ways the AI could handle.

The result? Mio Vino went from idea to App Store in about a month. Traditional development would’ve taken 6x the time and cost nearly $60,000. AI made it fast and affordable—but not automatic.

This is the nuance execs need to understand: AI is powerful leverage, not a replacement for product thinking or domain expertise.

🚫 Fallacy #2: “AI Code Is Trash”

On the other end of the spectrum, some developers dismiss AI-generated code as unusable or dangerous. Early versions of AI tools did produce messy or overly generic code, but that’s changed—fast.

I came across this post on LinkedIn recently:

What’s the problem? While I don’t see any issue at all with playing with code and discovering new things as a mini project – heck, I encourage it! It’s how I learned how to do loads of things – with LLMs it is likely to create absolute garbage code that will never see the light of day. It will probably sit there, in a half broken state, after using countless amounts of energy and water to generate via the LLM. A complete and total waste of time and resource.

Today’s tools are surprisingly good at boilerplate, scaffolding, unit testing, and even catching subtle logic bugs. When guided properly, they can increase velocity without compromising quality. I think of it as a better version of templating and auto-complete. These too

What’s required is judgment—developers still need to review, refactor, and make decisions. But used wisely, AI reduces the grunt work and lets devs focus on architecture, UX, and innovation.

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The Middle Path: Humans + AI = Speed and Scale

Here’s the bigger takeaway: both fallacies miss the point. AI doesn’t replace developers, and it doesn’t suck either. It’s a force multiplier—especially when paired with people who know what they’re doing.

  • For CEOs: AI helps your team move faster, not disappear.
  • For devs: AI helps you skip repetitive tasks and build smarter.

The key is not whether AI can replace humans, but how it can amplify them.

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Final Thought

If you’re asking, “Can AI replace developers?”—you’re asking the wrong question. The better question is:

“How can we use AI to build better software, faster—without losing control over quality, vision, or strategy?”

I’ve seen firsthand what’s possible when you combine AI with experience, judgment, and curiosity. The future isn’t AI vs. humans—it’s AI with humans. The teams that figure that out early will win.

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Want to dive deeper into how AI can accelerate your product or engineering org? Schedule a strategy session today.

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