It started, as these things often do, with a tweet.

Someone posted a screenshot of their IDE with a glowing autocomplete suggestion that was — and I’m not exaggerating — better than what I would have written. Cleaner. More idiomatic. With edge cases I hadn’t even considered.

I felt two things simultaneously: excitement and a quiet, creeping dread.

So I decided to run an experiment. For one week, I would let an AI coding assistant write as much of my code as possible. Not just autocomplete — I’m talking full functions, full modules, tests, the works. My job was to be the architect, the reviewer, the one who says “yes” or “no.” The AI would be the hands.

Here’s what happened.

Day 1: The Honeymoon

The first day was intoxicating. I described what I wanted in plain English, and the AI produced working code in seconds. A CLI tool that parsed log files and generated summary reports? Done. A small API endpoint with input validation? Here you go. A batch script to reorganize my photo library by EXIF data? Already written.

I felt like a tech lead with a team of junior developers who never slept, never complained, and never asked for raises.

Productivity was through the roof. I shipped more on Day 1 than I typically ship in three days.

Day 3: The Cracks Appear

By the middle of the week, the honeymoon was over.

The AI had written a caching layer for a small web service I was building. It looked correct. The tests passed. But when I actually read the code — really read it, the way you read code when you’re about to deploy it to production — I noticed something troubling.

It was plausible. Every line made sense in isolation. But the overall architecture was subtly wrong. It had chosen a caching strategy that would work fine with ten users and fall apart with ten thousand. It had made assumptions about my database that were reasonable but incorrect. It had handled the happy path beautifully and the error cases with a kind of cheerful optimism that would make any ops engineer nervous.

This is the thing nobody talks about: AI-generated code doesn’t look broken. It looks almost right. And “almost right” is the most dangerous kind of wrong.

Day 4: The Skill Question

Here’s where it got philosophically interesting.

To catch the AI’s mistakes, I had to understand the code better than the AI did. I had to know enough about caching strategies, database behavior, and error handling to spot the subtle issues. Which means the AI didn’t eliminate the need for expertise — it increased it.

Think about that. The tool that’s supposed to make coding easier actually demands that you be a better programmer to use it safely. It’s like how power steering didn’t make driving easier for beginners — it made it possible for experts to drive faster.

I started to wonder: what happens to the junior developers? If the AI writes the code and a senior developer reviews it, where does the learning happen? Where does the intuition come from — the kind of deep, gut-level understanding that you only get from writing bad code, debugging it at 2 AM, and swearing never to make that mistake again?

Day 5: The Unexpected Gift

But here’s the twist. On Day 5, something shifted.

I stopped thinking of the AI as a code generator and started thinking of it as a thinking partner. Instead of asking it to write entire modules, I started asking it questions. “What are the trade-offs between these two approaches?” “What edge cases am I missing?” “How would you test this?”

The answers weren’t always right. But they were always interesting. The AI would suggest approaches I hadn’t considered, point out failure modes I’d overlooked, and occasionally propose something genuinely clever that I wished I’d thought of first.

This was the real value. Not the code generation — the ideation. The AI was like having a rubber duck that talks back, except the rubber duck has read every programming book ever published and doesn’t mind being wrong.

Day 7: The Verdict

So, one week later, what did I actually learn?

1. AI doesn’t replace programmers. It replaces the boring parts of programming. And honestly? That’s enough. Nobody enjoys writing boilerplate, configuring build tools, or writing the fiftieth CRUD endpoint. Let the AI do that. Save your brain for the hard parts.

2. Reviewing AI code is harder than writing it yourself. When you write code, you know what you were thinking. When you review AI code, you’re reverse-engineering someone else’s (non-existent) thought process. It requires a different kind of attention, and it’s exhausting.

3. The best use of AI is conversation, not generation. The most valuable moments weren’t when the AI wrote code for me. They were when it helped me think. When it challenged my assumptions. When it said, “Have you considered…?” and I realized I hadn’t.

4. Expertise matters more, not less. In a world where anyone can generate code, the people who understand why the code works — and why it might not — are more valuable than ever. The AI is a multiplier, and it multiplies whatever you bring to the table. Bring deep expertise, and it makes you superhuman. Bring shallow knowledge, and it makes you confidently wrong at scale.

5. The dread was misplaced. I was afraid the AI would make me obsolete. Instead, it made me faster. Not in a “I can do less work” way, but in a “I can tackle harder problems” way. The ceiling got higher, not lower.

The Bigger Picture

We’re living through a strange moment in the history of our craft. The tools are changing faster than our understanding of how to use them well. Every week brings a new model, a new capability, a new reason to either celebrate or panic.

My advice? Neither celebrate nor panic. Pay attention.

Try the tools. Push them to their limits. Notice where they’re brilliant and where they’re brittle. Develop your own judgment about when to trust them and when to reach for the keyboard yourself.

And remember: the goal was never to write code. The goal was to solve problems. If an AI helps you solve problems faster, that’s not a threat — that’s a win.

Just make sure you understand the solution well enough to fix it at 2 AM when it breaks.

Because it will break.