Dan Haiem is the founder and CEO of AppMakers USA, helping business leaders design, build and scale apps that deliver real-world impact.
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Over the past year, our team has worked through more than 37 apps that came to us because something had gone wrong. Internally, we call this “Fix Your App,” but the work is not routine maintenance. In the majority of those cases, the root cause followed the same pattern: An issue had been identified earlier, pushed aside and treated as something the team could fix later.
What begins as a technical shortcut does not stay technical. Over time, it compounds. It affects product decisions, delays growth, increases operating costs and, in some cases, raises legal or compliance questions.
Many teams underestimate that part. “Fixing it later” can become one of the most expensive decisions a product team makes.
Technical debt rarely stays an engineering problem.
Just recently, a client came to us because their onboarding and user data pipeline kept breaking in ways their users could feel. At first, it looked like a feature problem. Once we got deeper, the issue appeared to be in how data moved through the product. Earlier fixes were layered on top of the original problem instead of solving it, so every new change created another side effect.
That happens more often than founders expect. In our app recovery work, roughly 2 out of every 3 apps we review have some version of this problem, where the visible issue is not the real issue. It is the result of an earlier shortcut that became part of the product.
If user data is involved, that same kind of compromise can move from a product headache into a privacy or compliance risk. That is how a small technical shortcut becomes a business problem.
Deloitte has reported that up to 70% of technology leaders see technical debt as a barrier to innovation. That sounds broad, but in app work, it shows up in very specific ways. A checkout flow cannot be improved because the payment logic is tangled into three other features. A new onboarding step takes weeks instead of days because the user data model was never cleaned up. A simple performance issue becomes hard to fix because the team built work-arounds on top of work-arounds.
The expensive part is not always the fix itself. It is everything wrapped around the fix, such as slowed releases, frustrated users, missed road map items, extra QA, messy dependencies and leadership time spent managing problems that should have been resolved earlier.
By the time a client says, “We need this fixed,” the issue has usually already cost them more than they realize.
Leaders do not need an engineering background to spot the warning signs. Here is what I recommend looking for.
The places where engineers consistently add buffer time, or where a "simple" change takes unexpectedly long, are almost always sitting on top of an older problem.
Ask directly: What parts of the product are we afraid to touch? The answer is usually where the debt lives.
Every work-around is a deferred decision. If your product has integrations, features or data flows that nobody fully understands anymore, or that only one person can explain, there is a structural risk. Document them. Assign an owner. Set a deadline for resolution.
Old SDKs, unmaintained libraries and rushed authentication setups are common sources of both performance issues and security exposure. A basic audit of what your app depends on, and when those dependencies were last updated, tells you a lot about where risk is concentrated.
If your app collects, stores or moves user data, check that what the product promises matches what the system actually does. Privacy policies and actual data flows get out of sync more often than teams realize, especially after fast-moving build cycles.
If adding one feature reliably causes problems in two or three other areas, it is a signal that the underlying architecture needs attention before the road map moves forward. This is one of the clearest signs that old decisions have started controlling new ones.
None of this requires a full rebuild. In my experience, it starts with honesty about where the shortcuts live and a clear plan for what happens if they stay.
There’s a common belief that teams are choosing between building fast and building carefully. That’s not really the trade-off.
The real trade-off is between paying while the problem is still contained or paying after it has spread into the rest of the product.
And increasingly, “later” does not mean a clean refactor. It means consequences that extend beyond engineering.
Every issue a team chooses not to fix moves somewhere. Sometimes it moves into the next sprint. Sometimes it moves into customer support. Sometimes it moves into churn, missed revenue or a hard conversation with users.
By the time it reaches the balance sheet, it is a lot more expensive to deal with.
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