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# AI coding agents are creating a new kind of technical debt: code nobody on the team fully understands.

**[THAMIZHSELVAN M](https://daily.dev/sources/ogbitmnj2z44sg5oudcgn)** · [@thamizhselvanm](https://daily.dev/thamizhselvanm) · 2 min read · 24 upvotes · 10 comments

## Summary

An opinion piece argues that AI coding agents introduce a new form of technical debt: code that works and passes tests but that no one on the team truly understands the reasoning behind. The author calls this 'understanding debt' and suggests that as agents get better at producing working code, teams risk accepting more code without grasping why it was designed that way. The piece ends by asking developers whether they read every line an agent generates or mostly trust tests and review key parts.

## Content

I've started thinking that AI coding agents are creating a different kind of technical debt.

Not bad code.

Code that works perfectly well, but nobody on the team really understands.

You ask an agent to add authentication.

It changes 8 files.

You ask it to fix a bug.

It changes another 5.

You run the tests.

Everything passes.

So you merge it.

A few weeks later, something breaks in a completely different part of the application.

Now someone has to understand why those 13 files were changed in the first place.

And this is where I think AI-assisted development gets interesting.

With normal development, the person writing the code usually has some mental model of why the code exists.

With AI-generated code, it's very easy to have:

"I know what this code does."

without actually having:

"I know why this code was designed this way."

Those are two very different things.

I've started calling this "understanding debt."

The codebase may be clean.

The tests may be green.

The architecture may even look good.

But the team's understanding of the system slowly decreases.

And I think this could become a bigger problem as coding agents become better.

Because the better they get at producing working code, the easier it becomes to accept code without understanding it.

Maybe the next important metric for AI-assisted development shouldn't only be:

"How much code did the agent write?"

It should also be:

"How much of the resulting system can the developer still explain?"

I'm curious how other developers are handling this.

Do you read every line generated by your coding agent?

Or do you mainly trust the tests and review the important parts?

#AI #AICoding #SoftwareEngineering #Programming #DeveloperTools #CodingAgents

## Community discussion

Top comments from developers on daily.dev.

**@akkitto** · 9 upvotes

> _yawn_
>
> This has nothing to do with AI. **Nothing.**
>
> Since decades companies produce code, which nobody understands, especially when the original author goes.......

**@confidentcoding** · 3 upvotes

> Yes. We know.

**@andradei** · 3 upvotes

> It always existed. AI just accelerated this process like it did almost everything else.
>
> It's good to mention it, though, especially for those who didn't realize it by now.

**@ristotoldsep** · 2 upvotes

> Green tests don't prove the team understands the design. That's the scary part.

**@elmarchavez** · 2 upvotes

> AI amplifies both the good and bad qualities of an engineer. Sadly, most of us don't have the discipline to look at code anymore. That's the reality nowadays.

## Similar posts on daily.dev

- [Why AI coding debt is different](https://daily.dev/posts/why-ai-coding-debt-is-different-ne1tftltr) · InfoWorld · 0 upvotes · 0 comments

---

Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#code-review](https://daily.dev/tags/code-review), [#technical-debt](https://daily.dev/tags/technical-debt)

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