Every founder we talk to eventually asks some version of the same question. “Why does adding one button now take three days when it used to take an hour?” The honest answer is usually technical debt. Not a vague hand-wave of an answer either. There’s a real mechanism behind it, and once you understand it, you stop feeling like your app is cursed and start making sensible decisions about when to fix things and when to leave them alone.
This matters more for AI-generated code than for code a human team wrote slowly over months, because technical debt in AI code builds up at a different speed and in different places. We’ve opened up dozens of apps built with Cursor, Bolt, Lovable, v0 and Replit Agent, and the pattern is consistent enough that we can usually tell within ten minutes how much debt we’re looking at, and whether it’s the kind that can wait or the kind that’s already costing money.
Technical debt in plain English
The loan metaphor gets used a lot, often badly, so let’s do it properly. When you take on technical debt, you’re borrowing time. You ship a feature fast by skipping something that proper software engineering would normally require: a shared function instead of three copy-pasted versions, a database constraint instead of trusting the frontend to validate, a test instead of eyeballing it once and moving on. That’s the loan. The interest is what you pay every time you touch that area of the code afterwards, because now there are three copies to update instead of one, or the broken validation lets bad data in and someone has to clean it up by hand.
Like a real loan, debt isn’t inherently bad. Borrowing to ship a landing page variant two days faster, when you need to know by Friday whether anyone wants the product, is a sensible trade. The problem is that most AI-built apps don’t borrow deliberately. Nobody sat down and decided “we’ll skip input validation here to hit a deadline.” The AI tool just didn’t write it, because nothing in the prompt asked for it, and nobody reviewing the output knew to check.
That’s the part founders find hardest to accept at first. Debt they didn’t choose to take on is still debt. It still charges interest. The bill doesn’t care whether you signed for the loan on purpose.
Why AI tools pile it up fast
Three things make AI-generated code accumulate debt faster than code written by a team that’s planning as they go.
First, duplication. Ask an AI tool to add a feature that’s similar to an existing one, and it will very often write a new version from scratch rather than extending what’s already there. Over a few dozen prompts, you end up with five different functions that each validate an email address slightly differently, because each was generated in its own context window with no memory of the other four. Fix a bug in one and the other four still have it.
Second, no structure. A human developer, even a junior one, tends to organise code into some kind of shape: this folder is for payments, this one for user accounts. AI coding tools follow whatever pattern the prompt implies, which changes from session to session. The result is a codebase where related logic is scattered across files with no obvious relationship between them, which is exactly the condition our non-technical founder’s guide to code quality walks through from the other direction, how to spot it without reading a line of code yourself.
Third, and this is the big one, patches on patches. When something breaks in a vibe-coded app, the usual fix is another prompt: “this isn’t working, fix it.” The AI tool doesn’t diagnose the root cause unless explicitly asked to. It adds a conditional, a try/catch, a special case, right on top of the broken logic, because that’s the smallest change that makes the symptom go away. Do that fifteen times on the same feature and you get a function that’s technically correct but unreadable, where nobody, including the AI, can confidently predict what happens if you change one line.
The symptoms you can see without reading code
You don’t need to read a single file to notice technical debt building up. Watch for these instead.
Estimates keep growing for features that sound similar to ones you shipped before. If “add a filter to the search page” took one day in month two and now takes a week in month eight, something underneath has got harder to change, even though the ask looks the same size from where you’re sitting.
Bug fixes create new bugs. You report that the checkout button doesn’t work on mobile, it gets fixed, and now the desktop version is broken. That’s a strong signal that the codebase has tangled dependencies where changing one thing ripples into places nobody expected.
Developers (yours, ours, or a freelancer’s) start every conversation by saying some version of “we need to understand how this works before we touch it.” That hesitation is the cost of debt being quoted back to you in plain speech.
And the one we see most often: the same category of bug keeps reappearing in different forms. If you’ve had three separate incidents involving user data showing up in the wrong account, that’s not three unrelated bugs, that’s one structural issue in how data access is handled, patched three different times in three different places.
Good debt vs bad debt
Not all debt needs paying off, and treating all of it as urgent is its own kind of waste. The distinction that actually matters is whether the debt sits in a part of the app that changes often or rarely, and whether it’s load-bearing for revenue or trust.
A messy but stable settings page that you haven’t touched in four months and have no plans to touch is fine to leave alone. It’s ugly, but it’s not costing you anything right now. Debt in your payment flow, your authentication, or anywhere user data gets stored is a different category entirely, because a mistake there doesn’t just slow down your next feature, it can lose customer trust or money outright. We’ve written before about the real cost of free AI-generated code, and the apps that get expensive are almost always the ones where debt sat untouched in a high-stakes area for too long.
The useful question isn’t “is there debt here?” because the answer is almost always yes. It’s “does this piece of debt sit between me and either shipping fast or staying safe?” If the answer is no on both counts, leave it and spend your time elsewhere.
Paying it down without stopping feature work
The founders who handle this well don’t stop building to do a big rewrite. They fold debt repayment into the work they’re already doing. When a feature touches a messy area of the code, that’s the moment to clean up that area, not just add to the mess. It costs a bit more time on that one ticket and saves a lot of time on the next five.
It also helps to separate “needs tidying” from “needs replacing.” A disorganised but functionally sound codebase benefits from the kind of structured cleanup described in our guide to upgrading vibe-coded apps to production standard. A codebase where the debt has compounded so far that nobody can safely change anything is a different problem, and sometimes the honest answer is in our piece on when a rebuild beats a rescue. Knowing which situation you’re in before you commit budget to either path is the whole game.
Most apps we assess fall somewhere in the middle: fixable without a rebuild, but not fixable by continuing to patch symptoms. That middle ground is where a proper assessment earns its keep, because it tells you exactly how much debt you’re carrying and where it actually bites.
Every change breaking something else lately? That’s debt talking. Get in touch for a free assessment and we’ll tell you exactly how much you’re carrying and what to do about it first.