Transforming Productivity: How AI Fixed the Human Problem in Software Development

I’ve spent 17 years in software development and seen many changes in how we write code. But none has been as important as the AI tools we use today. According to 3 years old McKinsey’s research, developers can finish tasks up to twice as fast with AI. But speed is just one small part of the story.

There’s been endless debate about whether AI writes good or bad code. Some argue it produces buggy, overly complex solutions. Others praise its ability to follow patterns and standards. These discussions miss the point. The real revolution isn’t about whether an AI can write perfect code - it’s about how AI is changing human behavior.

When developers talk about AI, they focus too much on “Is the code good?” instead of asking “Are developers finally doing what they should have been doing all along?” This shift in perspective reveals AI’s most powerful impact on software development.

What’s truly amazing isn’t just that developers work faster — it’s that they now do things they always knew they should do but never did before.

How AI Fixes the Human Problem: Laziness and Excuses

Before AI, most developers avoided writing tests. They saw testing as a waste of time rather than a key part of quality software. Over the years, I’ve heard every excuse:

“We’ll add tests later when we have time.”

“This is just a prototype.”

“The deadline is too tight for proper testing.”

“We need to ship now and improve quality later.”

“I already tested it manually - it works on my machine.”

“Writing tests takes too much time. I could build another feature instead.”

“Nobody will notice if we skip tests just this once.”

The biggest difference between humans and AI is, strangely enough, our worst work habit: laziness and our ability to make excuses. This isn’t just about testing - it affects every aspect of quality:

• Documentation: “The code is self-documenting” (it never is)
• Code reviews: “Just approve it, I’m sure it’s fine”
• Error handling: “We’ll add proper error messages later”
• Accessibility: “Only a small percentage of users need that”
• Performance: “We can optimize it if users complain”

I’ve seen million-dollar projects fail because of these attitudes. Few companies I worked with had to rewrite their entire codebases because tech debt from “temporary” shortcuts piled up until the system couldn’t be maintained.

Developers have always known the right way to code. We go to conferences and talk about clean code, testing, and documentation. Then we go back to work and ignore these standards because we’re rushing to finish features.

From Knowing to Actually Doing

Here’s the big change AI has created: it has closed the gap between knowing what to do and actually doing it.

When a developer can simply say, “Cursor, write tests for this component” or “Copilot, document this function,” there’s no more friction. There’s no reason not to do the right thing when it’s as easy as typing a short request.

I’ve seen and heard this transformation in real teams:

• A developer who never wrote documentation in 5 years suddenly had complete API docs because AI made it painless
• A team that increased test coverage from 20% to 80% in a month after adopting AI tools
• Junior developers who now write error handling as good as seniors because AI suggests proper patterns

Just having tests makes code better. Tests help document the code, catch bugs, and force better design. By making it easy to create tests, AI tools have made our code better overall.

We go to conferences and talk about clean code, testing, and documentation. Then we go back to work and ignore these standards because we’re rushing to finish features.

Better Quality Happens Naturally with AI

In the past, rushing to finish code meant cutting corners on quality. Developers weren’t writing bad code because they didn’t know better; they wrote it because they were racing to meet deadlines.

This created a harmful cycle:

1. Skip quality practices to ship faster
2. Encounter bugs and maintenance problems
3. Spend more time fixing issues than writing new features
4. Feel even more time pressure
5. Skip even more quality practices

AI has broken this cycle. When generating code takes seconds instead of hours, there’s finally time to think about quality. Also, AI tools have learned from high-quality code, so their suggestions usually follow best practices automatically.

I’ve seen this myself: AI doesn’t just write tests; it often writes better tests than many developers. Human developers sometimes test the wrong things—like language features instead of business logic. They also write too many tests that become hard to maintain. AI tends to be more focused and practical.

When a senior developer writes a test, they often think “What might break?” but a junior developer thinks “How do I make this test pass?” AI approaches testing more like a senior, focusing on real use cases and edge conditions.

And this doesn’t even include specialized tools like AI code reviewers that further improve quality.

What’s Coming Next: Software Development Agents

What we see now is just the beginning. The next big step is full software development agents that can handle entire tasks with little human help.

Imagine describing a feature and having an agent:

1. Create all the needed components
2. Write the business logic
3. Write complete tests
4. Document the code
5. Create a pull request with a proper description

This isn’t just a dream! We’re already seeing early versions of these abilities in new tools. The line between “I’m writing code with AI help” and “AI is writing code with my guidance” is starting to blur.

The Real Change in Productivity

When we talk about AI helping developers, we usually focus on metrics like “time to build a feature” or “lines of code per day.” But these miss the bigger change.

The real revolution is that AI has removed the barriers to doing things right. It’s not just that developers can work faster—it’s that they can finally work better without slowing down.

Tests get written. Documentation exists. Code is cleaner. Design is better thought out. And all of this happens faster than before.

As someone with 17 years in the industry, I’ve seen the gap between what we say at conferences and what we actually do day-to-day. Developers have always worked below the quality standards we talk about. AI is finally helping us close that gap, not by forcing us to change, but by making quality the easiest path to take.

And that, more than any speed improvement, is the true productivity revolution.

_{This article was proofread and edited with AI assistance.}