AI Surprised me in a good way

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There’s a moment that caught me off guard recently.

Not a breakthrough in code.
Not a clever refactor.
Not even a production issue solved at 2 AM.

It was something simpler—and much bigger.

I realized I had fully accepted AI-driven development.

The Workflow That Changed Everything

I built a system that feels almost unreal when you step back and look at it.

Here’s what happens:

  • A bug or feature is created in Azure DevOps
  • An application polls for new work
  • When it finds an item, it:
    • Creates a branch
    • Writes or updates the code
    • Generates tests
    • Runs those tests
    • Updates documentation
    • Runs a separate agent for code review (with a report)
    • If everything passes… creates a PR

All of this is powered by a combination of:

  • Agents
  • Skills
  • Prompts
  • Tools

In other words… a small army of AI doing what used to take hours (or days).

The Unexpected Realization

After watching this system run, I leaned back and had a surprising thought:

“I can focus on being a software engineer again.”

That hit harder than I expected.

What Happened to Software Engineering?

Somewhere over the last 20 years, something shifted.

I didn’t notice it happening.

Like many developers, I became increasingly focused on:

  • Writing code
  • Fixing bugs
  • Churning out features

Important work? Absolutely.

But in hindsight… it crowded out something bigger.

Engineering.

What AI Gave Me Back

With AI handling the repetitive execution layer, I’ve rediscovered the parts of the job that actually define software engineering.

Here’s what I can focus on now:

1. Understanding the Problem

Not just what to build—but why it matters.

2. Working with the User again

Seeing the system through their eyes.
Understanding friction, confusion, and real-world use.

3. Planning the Implementation

Designing before building. Thinking before typing.

4. Test Cases & Test Plans

Not just writing tests—but defining what should be true.

5. Documentation (the kind people actually read)

  • Source documentation
  • User documentation
  • Training materials

6. Release Management

Understanding timing, impact, and communication—not just deployment.

7. Architectural Impact

Seeing how one change ripples across the system.

8. UI Proof of Concepts

Exploring ideas before committing to them.

9. Business Rules

Clarifying logic instead of burying it in code.

10. Staying Current

Actually having time to keep up with:

  • C#
  • HTML
  • Modern development practices

11. Security

Thinking about it early—where it belongs—not bolting it on later.

The Irony

For years, we’ve said:

“Don’t just be a coder. Be an engineer.”

But the reality is, most of us were buried in coding.

AI didn’t replace that work—it lifted it off our shoulders.

This Isn’t About Replacing Developers

Let’s be clear.

This isn’t:

  • “AI writes everything now”
  • “Developers are obsolete”

It’s something much more interesting.

AI is taking over the mechanics of development…

AI does not magically fix bad systems; it amplifies what already exists.

So we can return to the discipline of engineering.

The New Role of the Developer

If you step back, the role is shifting:

BeforeAfter
Write codeDefine intent
Fix bugsDefine correctness
Create featuresDesign solutions
Review codeReview outcomes

Final Thought

I didn’t expect this.

I thought AI would make me faster.

I didn’t realize it would make me better aligned with what I originally loved about this profession.

Not just building software…
But engineering solutions.

And honestly?

That’s a pretty great place to be.

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