They have It Wrong

AI Won’t Replace Developers — It Will Multiply Them

It’s a catchy narrative. It’s also the wrong bloody one, because the truth is a lot less dramatic and a lot more interesting. “AKA the Cup Half Full”

In my view and thinking, AI won’t replace developers. It will turn strong developers into small teams.

If you want to understand where this is actually going, you have to separate “code generation” from “software development.” They’re not the same thing. Not even close.

The YouTube Demo Problem

Let’s start with what fuels most of the hype. You’ve seen the videos:

• “I built an app in 10 minutes using AI.”
• “No code. No experience. Just prompts.”
• “This tool replaced my job.”
• AI grew hair on my head – Okay, I made that one up.

And sure, AI can produce something that looks impressive. It can generate a nice UI, wire up a basic API, and give you a demo that plays well on camera. I have been impressed, but to a point.

But real software isn’t a demo. Real software is what happens after the demo:

• When users do weird things you didn’t expect
• When the database gets messy
• When requirements change
• When security becomes a real issue – And this is a real issue, just ask Loveable.Dev .
• When performance suddenly matters
• When the app has to survive upgrades, patches, new features, and real-world chaos

A shrink-wrapped product, the kind of multi-tier, production-grade system businesses actually rely on is not built by “prompting until it works.” I have never done this, honest. And for the most part, at least partly, this is where the “AI replaces developers” storyline falls apart.

Code Is Not the Job – Yes, AI can write code, I am old as heck and pretty much lived through it all. But software development isn’t “writing code.” That’s only one piece of it.

Development is:

• designing systems that don’t collapse under complexity
• building architectures that scale
• modeling data correctly so it still makes sense a year from now
• managing trade-offs between speed, cost, security, and maintainability
• anticipating edge cases and failure modes
• understanding how to debug when reality doesn’t match the happy path
• knowing when a solution is fragile even if it passes a basic test
• I could go on, I usually do.

AI can help with parts of that. But it does not own those responsibilities. And it definitely doesn’t carry the consequences when something breaks in production. Developers do.

Why “Average People/Developers + AI” Hits a Wall

Here’s what people don’t like admitting: AI-generated code often looks correct even when it isn’t. I have fallen victim to that more times than I’d like to admit.

If you don’t already understand programming, you can’t reliably tell when the output is:

• subtly wrong
• insecure by default
• inefficient in ways that won’t show up until real load hits
• missing validation
• using the wrong design pattern
• piling up technical debt at high speed

So what happens?

You get “working” code that paints you into a corner. And when it fails — because it eventually will — the person driving can’t steer out of it. They don’t have the mental model to refactor, redesign, or debug properly. They end up adding more prompts, more patches, more complexity… until the project becomes a brittle mess. AI, like autonomous driving, needs to be 99.999999% acurate, yes, those 6 9s are huge – it’s called the long tail.

That’s not building software. That’s just gambling with syntax.

What AI Really Does: It Speeds Up Real Developers

Now let’s talk about what actually works. If you’re a developer who understands architecture, algorithms, databases, and systems, I mean eat, breaths and craps, programming, AI is your fricken rocket booster. Take that Elon!

It’s amazing for:

• boilerplate and repetitive code – love love this!!!!
• scaffolding projects quickly – You need to write a small book for a prompt.
• generating test coverage – Sometimes, but yes.
• producing variations of known patterns
• refactoring and cleanup
• documentation, summaries, and comments – This makes your code look like a published author wrote your comments.
• speeding up research and implementation options – Big 10-4
• catching obvious mistakes and edge cases – Yes, with a little push

In other words, AI takes the “grunt work” off your plate so you can focus on what matters:

design, correctness, good coffee, integration, and long-term maintainability…oh and more good coffee.

But there’s a catch.

The Part Everyone Ignores: You Have to Orchestrate AI, You make AI your @#$%

AI is not a junior developer you can leave alone with a ticket. AI is more like a powerful, fast assistant that needs direction. A strong developer doesn’t just ask for code.

They:

• constrain the solution space
• define the architecture and boundaries
• specify what methods are allowed and what isn’t
• push back when the assistant drifts into a bad approach
• catch subtle flaws early
• decide when to stop prompting and write the core logic themselves
• review everything like it’s going into production… because it is
• and more…

This is the balancing act. Some tasks you can let AI do almost autonomously. Other tasks, especially core algorithms, complex formulas, tricky business logic, and security-sensitive flows, are the human developer all the way.

Sometimes the best workflow is:

1. You write the critical logic yourself.
2. AI reviews it, tests it, refactors it, and expands coverage.
3. You own the final result.

That’s not a replacement. That’s acceleration!

The Better Narrative: One Excellent Developer Becomes Ten. This is where the conversation should be. The big win isn’t “AI replaces developers.” The big win is: AI makes great developers like developers on a crap ton of Adderall and Red Bull, who can bang out perfect code like a pezz dispenser.

If you’ve got ten experienced developers, the kind you pay crap loads of money because they actually deliver, and you suspect they sleep at the office. You know the ones, the ones with Asperger’s who don’t look directly at you when you try engage with them. Well, you don’t ftricken replace them with AI, you give them AI and turn them into a god dam software factory.

That’s the productivity boom!

So if your company is smart, you should:

1. Keep your best developers.
2. Give them the best AI tools.
3. Train them to use AI properly (with standards and guardrails).
4. Measure outcomes: speed, quality, reliability, not hype.

Then you get a ton more done! And that, my friends, is how I see it.