The Invisible Tax You Pay When You Vibe Code
Comprehension Debt Is Real, and It's Compounding
You shipped the feature. Tests pass. PR merged.
Two weeks later, something breaks and you open that file. You stare at the code. Your code. Code you wrote. Code that works.
You have no idea what it does.
Welcome to comprehension debt.
The Debt Nobody Talks About
Technical debt is code you know is bad. Comprehension debt is code you don’t understand well enough to know if it’s bad.
There’s a crucial distinction here that a Reddit commenter nailed: “We’re getting correct code, but not right code.” The code runs. It passes tests. But ask someone why it makes specific design choices, why certain patterns were used, why the architecture looks the way it does — and the answer is often “Copilot put it there.”
With AI coding assistants, we can now generate working code faster than we can understand it. Claude writes 200 lines. Tests pass. Ship it. Next feature.
Repeat this fifty times and you’ve got a codebase that works but might as well be written by a stranger. Because functionally, it was.
Legacy Code on Arrival
Here’s the uncomfortable truth that r/programming figured out: vibe coding is legacy code from day one.
One commenter called it “the payday loan of technical debt.” You’re borrowing velocity from your future self at predatory interest rates.
A freelance developer with 8 years of experience recently described a pattern he’s seeing repeatedly: companies paying good money for internal software that barely works. Tons of errors, unreasonably slow, security flaws everywhere. When he looks at the codebase, the same telltale signs: AI-generated comments, algorithms that make no sense, inconsistent patterns. Yes, it mostly works. But it works terribly.
In one case, a designer with CSS knowledge but not much more created a full React app with AI. When they hired a freelancer to fix it up, he deleted 90 files out of 100.
That’s not technical debt. That’s a technical foreclosure.
Where It Hurts
Comprehension debt doesn’t show up on sprint boards. It shows up when:
Debugging takes 10x longer because you’re reverse-engineering your own code. Your own code. Like some kind of archaeologist excavating your past self’s decisions.
Small changes require big rewrites because you can’t safely modify what you don’t understand.
You can’t explain the system to anyone, including future you. Especially future you.
Architecture decisions compound badly because each layer is built on foggy assumptions and vibes.
Everyone talks about vibe coding. Nobody talks about vibe debugging. There’s a reason for that.
The irony: you used AI to go faster, but now you’re slower because you have to re-learn your own codebase every time you touch it.
The Skill Atrophy Problem
Here’s what worries senior developers: the heavier you lean on AI, the more your own skills degrade.
Someone described AI coding assistants as “a hyper-intelligent, infinitely patient junior developer.” Another added: “overconfident and unable to learn.”
That’s the trap. A junior developer eventually becomes a senior developer. They remember painful mistakes. Their understanding of your system grows over time.
AI doesn’t. Every conversation starts fresh. It will confidently suggest the same antipattern tomorrow that you rejected today. And if you’ve stopped exercising your own judgment because the AI handles it, you won’t catch it.
Ironically, the only people who should be leaning heavily on AI for code generation are people who are already experts. They can spot when it’s wrong. Everyone else is just accumulating comprehension debt they can’t even see.
Fighting Back
You don’t have to understand everything. That’s the whole point of abstraction. But you need to understand enough.
1. The Five-Minute Rule
After AI generates code, spend five minutes actually reading it. Not skimming. Reading. Like with your eyeballs.
If you can’t explain what it does to a rubber duck, you’ve got comprehension debt.
2. Write the Comments Yourself
Don’t let AI write comments. Write them yourself, in your own words. If you can’t write the comment, you don’t understand the code.
One veteran developer pointed out: “Given that very few people comment the code, if there are comments at all it’s AI generated.” Comments have become a smell for AI slop, not a sign of good documentation.
3. Draw the Damn Diagram
For any non-trivial flow, sketch the data path. Boxes and arrows. Takes two minutes. Forces you to understand the actual architecture, not the architecture you assume exists.
4. Refactor Before You Forget
The best time to refactor AI-generated code is immediately after it works. You’ve got context. You’ve got momentum. Wait two weeks and that context is gone forever.
Future you will not remember. Future you has problems of their own.
5. Your PR, Your Responsibility
“Copilot put it there” is not an acceptable answer in a code review. It’s the same as saying “I don’t know, it was the first autocomplete option.”
The AI is a tool, like your IDE. At the end of the day, you’re responsible for every line in your PR. If you can’t defend the code, you shouldn’t be shipping the code.
The Uncomfortable Truth
I’m not saying go back to writing everything by hand. That ship has sailed.
AI leverage is real. Use it.
But leverage without understanding is just deferred confusion. Every line of code you don’t understand is a question you’ll have to answer later, usually at 2am, usually when something is on fire.
Those championing AI focus on the speed something new can be developed. But in the long term, the real difficulty is how easily it can be maintained. And you can’t maintain what you don’t understand.
The developers who’ll thrive aren’t the ones who generate the most code. They’re the ones who maintain a sustainable ratio between code shipped and code understood.
Velocity without comprehension isn’t velocity.
It’s procrastination with extra steps.