The Understanding Gap

Last week, I lost a whole day of coding not due to a computer crash or forgetting to save, but because I trusted AI too much.

Here's what happened:

I used an AI coding assistant to build a complex feature. Initially, it felt remarkable. The AI understood my needs, generating code faster than I could type. But as the project grew, something strange happened: the AI lost context. It started suggesting solutions that contradicted its earlier code.

When I tried to understand the system it had built, I realized I couldn't — I had been trusting the AI's decisions without understanding them.

I had to start over.

Not just with the code...
But with my approach.

The Pattern I Can't Unsee

Our understanding becomes more fragile the easier AI makes something to create.

Think about it:

• We let AI write code we don't understand
• We accept solutions that are not explained
• We create systems that are difficult to maintain

The irony?

In our rush to code faster, we're making our work more vulnerable. Each line of AI-generated code becomes a potential debt we'll have to repay with interest when things go wrong.

This isn't just about coding or AI tools.

It's about accepting a dangerous trade-off:

• Immediate speed for long-term comprehension
• Generation before understanding
• Shipping before preparation

The pattern repeats across every AI interaction until the context deteriorates.

The Wake-Up Call We Need

We're building a world where coding is easier, but true understanding is rare.

The question isn't whether AI will make programming faster — it's whether we'll still know how to program when AI misguides us.

Is the real innovation ensuring we understand every line of code we deploy, rather than making code simpler to write?

That's a future worth creating.