Building CopyCat in 15 Hours

Why I Decided to Build It

I’ve always wanted a clean, lightweight clipboard manager for macOS. Something simple. Fast. Private.

But most tools I found were either:

• Expensive one-time purchases

• Subscription-based

• Or overloaded with features I didn’t need

So I thought, why not build my own?

As someone with years of development experience, building a clipboard manager wasn’t impossible. But what surprised me was how much AI accelerated the entire journey.

AI Was My Assistant — Not My Replacement

I used Cursor AI and ChatGPT throughout the development process.

But I want to be very clear: AI didn’t build the app for me.

It worked with me.

I drove the architecture. I made the decisions. I verified everything. I tested everything. I rejected suggestions when needed.

AI reduced friction — but I steered the direction.

That collaboration dynamic made all the difference.

9 Hours to a Working Core

The first 9 hours were focused purely on building the core:

• Clipboard monitoring

• History storage

• Local persistence

• UI structure

• Retrieval and filtering

Instead of spending hours debating architecture, I would ask:

• What’s the cleanest way to structure this?

• What are the best patterns for lightweight clipboard tracking?

• How should I model this data?

Within seconds, I had structured suggestions.

Were they perfect? No.

But they were strong starting points.

That alone saved days of overthinking.

AI helped me:

• Draft architectural approaches

• Generate boilerplate code

• Suggest efficient polling strategies

• Identify potential memory risks

What normally might take research, StackOverflow digging, and trial-and-error got compressed into fast iteration cycles.

6 Hours of Refinement and Optimization

After the core was ready, I spent around 5 more hours polishing.

This is where AI felt like a senior engineer sitting next to me.

I would paste sections of code and ask:

• Is this memory-safe?

• Can this be optimized?

• Is this over-engineered?

• Where could this break under load?

Not every suggestion was correct — but almost every suggestion improved my thinking.

And that’s powerful.

AI accelerated decision-making. Instead of waiting days to discover structural weaknesses, I could analyze and refine instantly.

Speed of Prototyping Changed Everything

The biggest shift was momentum.

Normally development looks like this:

Think → Implement → Debug → Rethink → Refactor → Repeat.

With AI, it became:

Think → Discuss → Refine → Implement faster.

It reduced hesitation. If I had an architectural doubt, I resolved it in minutes instead of postponing it.

That speed creates flow.

And flow creates productivity.

Confidence — But With Responsibility

One thing I was careful about: never blindly trusting AI.

Every generated snippet was:

• Reviewed

• Adjusted

• Tested

• Sometimes rejected

I simulated edge cases.
Checked memory behavior.
Inspected performance with larger clipboard histories.

AI doesn’t understand your app. You do.

The balance between AI assistance and developer judgment is critical.

AI gave speed.
Experience gave direction.

The Apple Review Moment

Clipboard apps deal with sensitive data. I genuinely expected rejection or at least review friction.

But CopyCat was approved in the first release.

That wasn’t just a product milestone — it validated that:

• Architecture was clean

• Permissions were correct

• Privacy boundaries were respected

That felt like silent confirmation that the decisions made during development were solid.

What I Learned

This experience changed how I view development.

AI is not replacing developers.

It is amplifying developers.

It:

• Reduces friction

• Speeds up iteration

• Encourages experimentation

• Supports architectural thinking

But it still needs:

• Judgment

• Verification

• Responsibility

Building CopyCat in 15 hours wasn’t about shortcuts.

It was about focused collaboration.

It felt like building at the speed of thought.

And that has permanently shifted how I see the future of software development.

AI is not a magic solution.

It’s a development partner.

And when used correctly, it unlocks a new level of execution speed — without compromising quality.