By Vaibhav Verma
You are paying $47,000 a month for engineers to read code they didn't write.
Not metaphorically. Not as overhead. Literally. Your senior engineers are spending 40% of their time tracing through methods written by people who left 18 months ago, trying to understand why the payment retry logic is split across three services, why the user authentication flow touches the database four times for a single login, why a function called processOrder actually handles refunds and subscription changes too.
Nobody mentions this cost. It doesn't appear on any spreadsheet. Your finance team doesn't see it. Your board doesn't ask about it. But it's there. Compounding monthly. Quietly eating your runway.
This is the hidden cost of a codebase nobody understands.
What This Actually Costs
You already know that bad code slows things down. Every CTO has heard that technical debt is expensive. But you probably think about it wrong.
You think: "Oh, our refactoring will take a few sprints."
That's not the cost. That's future cost. The cost happening right now is different.
A developer joins your team. You sit her down for onboarding. On day three, she's assigned her first ticket: add a flag to the subscription renewal logic so that annual plans renew on a different schedule. Seems simple. Three-day task, maybe four.
She opens the codebase. The subscription logic lives in a file that's 3,200 lines long. It calls three other files. Those files call four more. She's now holding six open tabs, trying to trace the execution path. The renewal logic isn't in one place—it's split across a service layer, a model layer, a cron job, and a database migration from 2021 that somehow still runs but nobody knows why.
She spends two days just understanding the current flow. The actual change takes four hours. She's done in six days instead of three. You're $2,400 over budget on that ticket. Multiply that by fifty tickets per quarter.
But wait. It gets worse.
A production bug hits. Payments are failing for a specific subset of users. Nobody knows why. Your lead engineer spends six hours tracing through logs, trying to understand which service is actually responsible. The bug is in a transaction handler that was modified by five different developers across two years. There's no documentation. There are no comments. There are no tests that explain the intended behavior.
He finds it. It was an off-by-one error in a retry counter that got introduced in a refactor nobody told the team about. Four hours of your lead engineer's time. Your best person. The one who should be designing next quarter's architecture. Instead, she's debugging someone else's mistake from 18 months ago.
That's not a bug fix. That's a tax. And you pay it every single time your codebase is hard to understand.
The Costs Nobody Sees
Here's what you're actually paying for:
Context switching tax. Every developer who has to hold more than three related code sections in their head at once experiences a 40% productivity drop. This isn't theory—it's how human working memory works. Your team is living in that zone. Constantly. They're not focused on features. They're focused on comprehension.
Compound defects. When developers don't understand the system they're changing, they introduce bugs. Not because they're bad—because they can't see the dependencies. A change that breaks something in an unrelated part of the codebase because the developer had no way to know the connection existed. These cascade. A bug in the refund handler breaks the dunning service for failed payments. A developer fixes that, not understanding it will break bulk operations. Your team spends 30% of its time fixing cascading defects instead of building features.
Knowledge hoarding. You have one engineer who has been there since the beginning. She knows why the cache invalidation works the way it does. She knows which database calls are safe to optimize and which ones will silently corrupt data. She's become critical infrastructure. If she leaves, you've lost institutional knowledge worth three months of engineering time. You know this. You probably have three people like this. One of them will leave. Probably this year.
Junior engineer bleeding. Your junior developers spend 60% of their time asking questions because the code doesn't explain itself. Your mid-level engineers spend 40% of their time answering those questions. Neither of them is being productive. Your junior engineers also make more mistakes because they have to infer intent instead of reading it. They get frustrated. Good ones leave.
Deployment fear. Your team delays releases because they're afraid of breaking something they don't understand. You deploy every two weeks instead of every two days. That's a 7x loss in feedback speed. In a market that moves monthly, that's a death sentence. You miss windows. Competitors ship. You're always one sprint behind.
Why Your Codebase Got This Way
You didn't wake up one day and decide to make your code unreadable. It happened gradually. Maybe you moved fast when you were a startup. Maybe you hired good engineers who wrote good code, but then they left and the new engineers had different patterns. Maybe you inherited a legacy system from an acquisition. Maybe your team grew faster than your standards could scale.
Usually it's all of these. And now you have 50,000 lines of code that nobody fully understands, and you're paying $2–3 million a year in lost productivity, delayed shipping, and compounds defects.
The standard answers don't work. You can't "refactor it away" in a few sprints. Your codebase is too big. You can't hire your way out. New engineers will be just as lost as your current ones. You can't throw tooling at it. Better linters and type checkers help, but they don't solve the comprehension problem—they make the constraints more visible, which sometimes makes things worse.
What actually works is building visibility into your codebase before you need it. Not retroactively. Not when you're in crisis mode.
You need a way for your engineers to quickly understand the impact of a change. To see which services depend on the function they're modifying. To understand what was intended by a piece of code, not have to infer it through trial and error. To see which parts of the codebase are actually critical versus which parts can be safely refactored.
You need your team to understand the system. And you need PMs and leaders to understand it too—not at the code level, but at the architectural level. Because the PM who doesn't understand that their feature request requires coordinating changes across four services will keep loading more on a team that's already bottlenecked.
This is where visibility tools matter. Not because they're sexy. Not because they show that you're "modern." But because they give you leverage against the cost you're paying right now.
Tools like Glue let you index your entire codebase and ask real questions about it. How many places call this function? What happens if I change this interface? Which services are actually coupled? Why does this endpoint take three different code paths? Your engineers don't have to hold all of this in their heads anymore. They don't have to context-switch between six open files. They don't have to spend three days understanding an existing pattern before they can confidently make a change.
And your leadership gets codebase intelligence without having to ask engineers to explain everything. You can see where the real complexity lives. You can see where your biggest risks are. You can make smarter decisions about what to refactor and what to rebuild.
The Real Question
The hidden cost of a codebase nobody understands isn't actually hidden. It's happening right now. You're paying it in slow delivery, in frustrated engineers, in junior developers leaving, in bugs that cascade, in weekend pages at 2am, in your best engineer spending a week tracing through code instead of designing the next system.
You can pay it silently. Or you can decide to see it. Measure it. Fix it.
The companies that move fast aren't the ones with the newest code or the cleverest architecture. They're the ones where every engineer can understand the system quickly. Where changes propagate predictably. Where new people can be productive in weeks instead of months.
That doesn't happen by accident. And it doesn't cost $2 million a year in refactoring. It costs discipline, good communication, and the right visibility into your codebase from the start.
Start looking at your codebase not as code, but as a communication problem. Every function, every service, every module is trying to tell you something about what the business does. If it's hard to read, it's hard to understand. And if it's hard to understand, it's expensive to maintain.
Your team knows this. They're living it. Ask them what percentage of their week is spent understanding code versus writing code. Whatever number they give you, multiply it by their salary. That's the hidden cost happening right now.
Then ask yourself: what's it worth to cut that number in half?
Frequently Asked Questions
Isn't this just the cost of every legacy system? Doesn't this get better over time?
No. It gets worse. Complexity compounds. As your system grows, the number of dependencies increases exponentially. A 10,000-line codebase might have 200 internal dependencies. A 100,000-line codebase might have 8,000. The productivity tax doesn't scale linearly—it accelerates. Without intervention, every quarter gets harder, not easier.
We're a startup. Don't we need to move fast and break things? Isn't code quality a scaling problem?
Moving fast and having readable code aren't opposites. In fact, they're aligned. Yes, early on you're writing code quickly. But if that code becomes a foundation, you're choosing between moving fast now and moving slowly forever. The teams that do both—move fast and remain readable—are the ones that actually scale. Google doesn't move slower because their code is well-organized. They move faster because of it. The time you "save" by ignoring code quality gets paid back with interest. Usually around month 18.
Isn't this what code reviews are for?
Code reviews catch bugs and enforce standards. They don't solve readability at scale. A code review can ensure that a function is commented. It can't ensure that a function is in the right place, or that it doesn't have hidden dependencies, or that the team understands why the system is structured the way it is. Code reviews are hygiene. They're necessary but not sufficient. You also need visibility into the larger architecture.
How do you actually measure if your codebase is becoming hard to understand before it's too late?
Ask your engineers directly. How long does it take a new person to be productive? How many times a month do they have to ask someone what a piece of code does? How much time is spent on refactoring versus features? How many bugs are discovered in code review that trace back to misunderstanding how the system works? If any of those numbers are getting worse, you're not keeping up with your own complexity.