By Arjun Mehta, Principal Engineer at Glue
Every engineering team talks about technical debt reduction. Far fewer actually do it well. Most approaches fall into one of two categories: ignoring debt until the system collapses under its own weight, or declaring a "debt sprint" that produces a flurry of refactoring and zero lasting change. Both are bad.
I have spent fifteen years writing, inheriting, and paying down technical debt across systems of every size. What I have learned is that reducing technical debt is not a heroic effort. It is a system. A boring, repeatable system that works if you commit to it.
This playbook covers the four stages of sustainable debt reduction: assess, prioritize, execute, and sustain. No hand-waving. No "just rewrite it." Just practical steps you can start using this week.
Assess: Map Your Debt
You cannot fix what you cannot see. The first step in any serious technical debt reduction effort is building a clear picture of where your debt actually lives.
Most teams have a vague sense that "the billing system is a mess" or "nobody wants to touch the notification service." That is not an assessment. That is folklore. You need specifics.
Start by gathering data from three sources:
Your codebase. Look at code complexity metrics, test coverage gaps, outdated dependencies, and files with high churn (frequently changed). Areas that get modified often but lack tests are high-risk debt. For deeper strategies on making this visible across the organization, check out our guide on technical debt visibility.
Your team. Engineers know where the bodies are buried. Run a short survey or dedicate a retro to cataloging debt. Ask: "What slows you down? What are you afraid to change? What would you fix if you had a free week?" You will get surprisingly consistent answers.
Your incident history. Production incidents are debt making itself known. If the same systems keep breaking, that is not bad luck. That is deferred maintenance catching up with you.
According to research from Jellyfish, developers spend between 23% and 42% of their time dealing with technical debt and maintenance rather than building new features. That is not a rounding error. That is a quarter to nearly half of your engineering capacity going to debt service.
Combine these inputs into a debt inventory. It does not need to be fancy. A spreadsheet works. Each item should include: what the debt is, where it lives, how it manifests (slow builds, frequent bugs, painful deployments), and a rough severity rating.
Prioritize: Impact vs. Effort
Now you have a list. It is probably long and depressing. That is normal. The mistake most teams make here is trying to tackle everything, or worse, picking items based on what is most annoying rather than what matters most.
A practical prioritization framework has two axes: impact and effort.
Impact means: how much does this debt cost us? Cost can be measured in developer time lost, incident frequency, onboarding friction, or blocked feature work. A tangled authentication module that every new feature has to work around has high impact. A slightly messy utility function that nobody touches has low impact.
Effort means: how much work is the fix? Some debt items are a weekend project. Others require a multi-quarter migration. Be honest about this. Underestimating effort is how "quick refactors" turn into six-month projects that never finish.
Plot your items on a 2x2 grid. High impact, low effort items go first. These are your quick wins, and they build momentum and credibility. High impact, high effort items need dedicated planning and should be broken into phases. Low impact items go on the backlog, and some of them will stay there forever. That is fine.
Kong's 2023 survey found that technical debt consumes roughly 40% of IT budgets and reduces development speed by about 30%. When you put dollar amounts next to your debt items, prioritization conversations with leadership get much easier.
The Stripe Developer Coefficient report estimated that technical debt costs the global economy approximately $85 billion annually. Your company's share of that number is worth calculating.
Execute: The 20% Rule
Here is the part where most playbooks say something vague like "allocate time for debt reduction." Let me be more specific.
The 20% rule works like this: dedicate roughly 20% of each sprint's capacity to debt reduction work. Not a separate debt sprint. Not "we will get to it when we have time." A standing allocation, every sprint, treated with the same seriousness as feature work.
Why 20%? Because it is small enough that product stakeholders will agree to it, and large enough to make real progress over time. At a typical two-week sprint cadence, 20% gives you about two engineer-days per sprint per engineer. That adds up.
Practical execution tips:
Pair debt work with feature work. If you are building a new feature in the payments module and the payments module has known debt, bundle the cleanup with the feature. This is more efficient than doing them separately and produces cleaner results.
Set clear definitions of done. "Refactor the user service" is not a task. "Extract the notification logic from the user service into a dedicated module with 80% test coverage" is a task. Debt work needs the same specificity as feature work.
Track it. Use the same tracking system you use for features. If debt work is invisible in your project management tool, it will be invisible in planning discussions. Check out approaches for tracking technical debt that keep it visible to both engineering and leadership.
Celebrate it. Seriously. When someone cleans up a module that has been causing pain for two years, that deserves recognition. Debt reduction is thankless work by default. Make it thankful work by choice.
The 20% rule also gives you a natural forcing function for prioritization. You cannot do everything, so you must do the most important things. This is a feature, not a bug.
Sustain: Prevent Re-accumulation
Paying down debt without changing the habits that created it is like paying off a credit card while continuing to spend beyond your means. You will end up right back where you started.
Sustainable technical debt reduction requires changes at the process level.
Code review standards. Your team's code review process is your first line of defense against new debt. Establish clear guidelines for what is acceptable: test coverage requirements, documentation expectations, complexity thresholds. Make it safe for reviewers to push back on shortcuts.
Architecture decision records. When teams make significant technical decisions, write them down. Include the context, the options considered, the decision made, and the trade-offs accepted. Future engineers (and future you) will thank you when they understand why the system looks the way it does.
Dependency management. Outdated dependencies are slow-growing debt. Set up automated dependency update tooling and review updates regularly. A quarterly dependency audit takes a few hours and prevents the kind of "we are fourteen major versions behind" crisis that requires a dedicated project to resolve.
Onboarding as a debt detector. New team members are excellent at finding debt. They stumble over confusing code, missing documentation, and brittle systems. Treat their onboarding pain as signal. If every new hire struggles with the same module, that module needs attention.
For engineering leaders and CTOs, Glue provides a way to track where technical debt is accumulating across your codebase and how it is affecting team velocity. Instead of relying on periodic surveys or gut feelings, you get continuous visibility into which areas of your system are generating the most friction. This turns debt reduction from a political negotiation into a data-informed conversation.
Technical debt reduction is not a project with an end date. It is an ongoing practice, like testing or code review. The teams that do it well are not the ones who occasionally declare war on debt. They are the ones who quietly, consistently keep their systems healthy as part of how they work every day.
The playbook is simple: assess honestly, prioritize ruthlessly, execute consistently, and build habits that prevent re-accumulation. The hard part is not knowing what to do. The hard part is doing it when there is always another feature to ship.
But that is exactly why you need a system. Willpower fades. Systems persist.
FAQ
How do you reduce technical debt?
Start by mapping your debt through codebase analysis, team input, and incident history. Prioritize items by impact versus effort, focusing first on high-impact, low-effort wins. Allocate a consistent percentage of sprint capacity (around 20%) to debt work rather than batching it into occasional sprints. The key is consistency and treating debt reduction as ongoing practice, not a one-time project.
What is the best way to prioritize tech debt?
Use an impact-versus-effort framework. Impact measures how much the debt costs you in developer time, incidents, onboarding friction, or blocked features. Effort measures how much work the fix requires. High-impact, low-effort items come first. Attach real costs where possible, because putting dollar figures next to debt items makes the prioritization conversation concrete and easier to justify to stakeholders.
How much time should teams spend on tech debt?
A common and effective guideline is 20% of sprint capacity, which translates to roughly one day per week per engineer. This is large enough to make meaningful progress and small enough to maintain product momentum. Some teams flex this number based on debt severity, going higher during particularly painful periods and lower when the codebase is healthy. The important thing is that the allocation is consistent and protected, not treated as optional slack time.