CODE TUNER INSIGHTS
Can a Fast-Growing Product Outgrow Its Maintenance Model?
Rapid feature growth can increase codebase complexity faster than maintenance practices can absorb it. Learn what to watch as a product scales.
More customers, features and integrations are usually signs of progress. They also change the amount and kind of maintenance a software product needs.
A team can keep the practices that worked 18 months ago and still find the product becoming harder to change. The maintenance model may no longer fit the system it supports.
Separate useful growth from deterioration
A larger codebase is not automatically a worse one. More code may support new markets, broader use cases and valuable customer capabilities.
Investigate when the effort required for comparable changes rises disproportionately, complexity accumulates in important areas or recent development quickly needs repair. The issue is whether the organisation can keep changing what it has built.
Absolute totals need context. More tests, dependencies or technical-debt findings may simply reflect a larger product.
An old routine may no longer be enough
Imagine doubling the size of an office while keeping its original maintenance schedule. A one-off cleanup may help temporarily, but it does not solve the recurring mismatch.
Software can face the same problem. If new work continually adds more maintenance demand than the team can absorb, periodic remediation may treat the symptoms while the backlog rebuilds.
Consider a repeatable allocation targeted at the areas where problems accumulate, alongside changes in development practices that address the inflow. Keep the amount under review rather than assuming it should grow automatically with code volume.
Warning signs in a growing product
New areas become difficult quickly
Recently built functionality repeatedly enters the remediation backlog. Investigate whether delivery practices, design boundaries or verification need attention before expanding the cleanup programme.
Understanding takes longer
The team needs more investigation to establish how changes affect the system. Knowledge may be fragmented across components and teams.
Features cause more knock-on work
Changes that once stayed within one area increasingly require changes elsewhere. Examine whether dependencies are growing unnecessarily or responsibilities are becoming less clear.
Maintenance demand grows faster than capacity
More engineering time goes into preserving existing behaviour, leaving less room for planned development. Distinguish temporary release effects from a sustained trend.
Compare trends with the work they represent
Review consistent measures over time and connect them to actual changes:
- Is comparable feature work becoming more expensive?
- Are complexity and dependency concerns concentrated in recently expanded areas?
- Are new warning signals appearing faster than useful product growth would suggest?
- Is maintenance demand increasing faster than the team can manage it?
Ratios can add context, but there is no universal unit of product value. Do not assume that dividing findings by lines of code gives a complete picture of maintainability.
McKinsey’s automotive-software analysis describes how rising complexity can increase maintenance demands and constrain innovation. The sector’s figures should not be applied directly to every software business, but the mechanism is a useful question to test in your own product.
Adjust maintenance while protecting momentum
A growing product does not necessarily need to stop feature development for a major cleanup. Start with the areas where deterioration is clearest and explain what recurring effort the intervention should reduce.
Reserve a bounded amount of capacity, improve the practices contributing to the problem and review whether the trend stabilises. If the evidence points to wider deterioration, revisit the scope rather than continuing an ineffective local response.
The practical question is whether maintenance is keeping pace with the way the product evolves. Answering it early can help protect the ability to keep growing.
Make the next engineering decision with better evidence.
Code Tuner analyses technical debt, complexity and codebase health to support engineering judgement and investment decisions. Explore how Code Tuner can help your team.