Why AI Coding Agents Create More Work, Not Less

While everyone's debating whether AI will replace developers, I'm living through a different reality entirely - a reality where artificial intelligence is creating a never-ending appetite for more code, more features, and ultimately, more human work. Let me explain.

The Math That Everyone's Missing

To fully understand what's actually happening, consider this simple example. Before AI, a developer might write 100 lines of code (illustrative for this example) in a day. It is thoughtful, deliberate work where each line is carefully crafted and considered.

Now, assuming that AI is handling 90% of the heavy lifting, you'd think the same developer will be writing only 10 lines per day, right? Wrong. Dead wrong.

When coding becomes "easier," the scope of what we attempt explodes. Those 100 lines of daily output will balloon to 1,000 lines. The AI writes 900 of them, sure, but the developer is still responsible for 100 lines of human-written code - the same amount as before, just scattered across a much larger codebase. Even with AI doing 90% of the coding, the sheer increase in scope means developers are still writing as much or more human code as they did previously.

But it gets worse. That remaining 10% isn't the easy stuff. It's the hardest parts. The edge cases. The architecture decisions. The debugging of code that almost works but has subtle bugs that take hours to track down.

What I've discovered is that AI coding agents don't reduce the work. On the contrary, they shift the bottleneck and doing so with effects we have never considered. When the cost of writing code plummets, suddenly every idea becomes feasible. Every feature request gets a "yes". Every optimization seems worth attempting.

Word processors were supposed to create the "paperless office" but instead, they made it so easy to create documents that we ended up drowning in them. AI coding agents are doing the same thing to software development.

Developers will find themselves saying “yes” to projects they would have never consider before. Building prototypes that turn into production systems. Adding features that seemed impossible just months ago. The barrier to entry will drop so low that the demand will exploded to fill every available minute.

The Burnout Nobody's Talking About

Here's what the code productivity evangelists won't tell you. Reviewing and maintaining AI-generated code is exhausting in ways that writing your own code never was. When you write code yourself, you understand every decision, every trade-off, every shortcut. When AI writes it, you're constantly context-switching between architect, code reviewer, and debugger.

The developer is not just writing more code. The developer is thinking more about code, debugging more systems, and maintaining more complexity than ever before. The cognitive load hasn't decreased, it has been multiplied several orders of magnitude overall.

Imagine you're on a treadmill that's perfectly calibrated to your running speed. Initially, you're jogging at a comfortable pace of 6 mph, feeling in control and maintaining good form. Then AI comes along and offers to handle 90% of your running. You'd think this means you could slow down to a casual 0.6 mph walk, right? But that's not what happens.

Instead, someone cranks the treadmill up to 60 mph. The AI handles 90% of that (equivalent to 54 mph) but you're still responsible for running at 6 mph, the same speed as before. Huge difference! The scenery is flying by ten times faster, creating an overwhelming sensation that you're accomplishing more while actually working just as hard.

But unlike a real treadmill where you could simply step off, the professional pressure to keep up with this new "productivity standard" means there's no easy way to escape the machine. The faster AI enables us to go, the faster we're expected to run.

Why This Means More Jobs, Not Fewer

This brings me to the counterintuitive conclusion that's emerging from my experience that AI coding agents aren't going to eliminate developer jobs. They're going to create demand for more developers.

Think about it economically. If the cost of building software drops dramatically, what happens to demand? It explodes. Companies that could never afford custom software solutions suddenly can. Ideas that were too expensive to prototype become viable. The software that seemed impossible becomes merely difficult.

This explosion of possibility will place enormous pressure on development teams. Developers will be increasingly overwhelmed by the need to write more crucial code, debug more AI-generated solutions, and maintain increasingly complex systems. To handle this load, companies will face a choice: either push existing developers to work harder and longer hours, or significantly increase their development staff. Most likely, we'll see both happen simultaneously – developers working harder than ever before while teams grow to distribute the mounting cognitive burden.

The Real Revolution

The revolution isn't that AI will write our code - it's that AI will make code so cheap to produce that we'll drown in demand for it. Every business process will become software. Every workflow will get automated. Every idea will get prototyped.

And someone will need to manage all of that complexity. Someone will need to make it maintainable, secure, and reliable. Someone will need to understand how it all fits together.

That someone is us - the developers. We're not being replaced. We're being multiplied. The question isn't whether there will be jobs for developers in an AI-powered future. The question is whether there will be enough developers to meet the explosive demand that AI coding agents are about to unleash.

From where I sit, having lived through this transition firsthand, I can tell you: we're going to need a lot more developers, not fewer. The productivity paradox is real, and it's just getting started.