Reduce technical debt in agile projects by making it visible in the work queue, prioritizing it by its effect on product change and risk, and preventing new debt from compounding through small, frequently integrated changes and reliable automated feedback. Scrum does not prescribe a separate technical-debt backlog or a fixed percentage of sprint capacity for debt work; teams should make the trade-offs explicit and improve the quality of their delivery system over time.
What technical debt looks like in an agile project
Technical debt is not limited to messy or old code. It is a condition in the product or delivery process that makes future work harder, riskier, or more expensive. It may appear in a legacy component, fragile tests, a manual release step, unclear interfaces, or a dependency that repeatedly slows planned changes.
Describe the specific impediment and its consequence rather than filing a vague item such as “clean up the code.” A useful debt item identifies the affected behavior or component, an example of the problem, the impact seen so far, the likely cost of deferring it, and a next step small enough to evaluate.
How should we prioritize technical debt in the backlog?
In Scrum, the Product Backlog is the ordered, single source of work undertaken by the Scrum Team. The November 2020 Scrum Guide, by Ken Schwaber and Jeff Sutherland, describes it as “an emergent, ordered list of what is needed to improve the product.” That supports making meaningful debt visible alongside feature, defect, and operational work rather than hiding it in an unreviewed list. The guide does not require a separate technical-debt backlog. Scrum Guide
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For each candidate, compare the consequences of delay and the likely value and risk of the proposed fix. Discuss the order with the Product Owner and Developers, using evidence where available.
- Risk reduced: Does the debt expose users or the organization to a confirmed defect, security concern, reliability failure, or operational risk?
- Recurring rework: How often does the issue cause corrections, incidents, workarounds, or repeated investigation?
- Upcoming product changes: Which planned change is blocked or made more difficult by leaving it in place?
- Feedback quality: Would the work make builds, tests, review, or release feedback faster and more dependable?
- Intervention size and reversibility: Is there a small, safe change that reduces the cost, or is the proposal a broad rewrite with uncertain benefits?
- Dependencies: Does the change require coordination with another team or system?
A repeated source of defects or a risky dependency can merit earlier work than code that is merely untidy. Make the cost and trade-off visible rather than relying on an automatic rule. A 2021 multinational practitioner survey with 184 responses, including practitioners in Brazil, Finland, and New Zealand, found that practices for verifying and maintaining the structure and clarity of implemented artifacts were seen as particularly helpful for reducing debt. The authors also noted competing stakeholder interests. These are survey findings, not causal proof or a representative global estimate. 2021 practitioner survey
Should technical debt be a separate backlog?
Not necessarily. Put debt that matters into the Product Backlog so it can be ordered against other product work. A team can use labels, filters, or a view to make debt easier to find, but the view should not become a second, invisible queue that bypasses prioritization.
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Record debt when it is discovered, even if it is not selected immediately. Link related incidents, repeated rework, or blocked changes when there is evidence. Distinguish confirmed defects and security exposures from maintainability concerns or speculative redesigns; they have different consequences and may need different urgency.
How much sprint capacity should we reserve for technical debt?
There is no fixed percentage prescribed by the Scrum Guide. A blanket allocation can obscure the real trade-off: a team might need to address a high-risk defect now, while a low-impact cleanup can wait for a more appropriate opportunity. Use backlog ordering and delivery evidence to decide what fits in a Sprint.
If a team experiments with a recurring allocation, treat it as a local hypothesis, not a Scrum rule. Review whether it reduces the specific delays, failures, or rework the team intended to address, and adjust it if the evidence does not support continuing.
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Set a shared, testable Definition of Done
The Definition of Done establishes a shared understanding of what it means for work to be complete. The Scrum Guide says an Increment must meet the Definition of Done, and Developers are accountable for adhering to it. Choose criteria to fit the product’s real quality needs rather than copying a universal checklist. Scrum Guide
Make the applicable criteria objective and checkable. Depending on the product, they may include:
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- Relevant build, test, dependency, or security checks passing.
- Code review completed according to the team’s practice.
- Required operational, support, or user documentation updated.
- Necessary monitoring, configuration, or migration changes accounted for.
A Definition of Done is a quality floor, not a promise to add every imaginable check. Expand or refine it in response to product needs and observed failures.
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Prevent debt from compounding with continuous integration
Integrate small changes frequently into a shared mainline, build and test them automatically, and treat a broken build as a priority. Short feedback loops make regressions easier to locate and fix. DORA’s Continuous Integration guidance recommends frequent integration, small batches, automated builds and tests, and prompt attention to broken builds. It says tests should take a few minutes, with about 10 minutes as an upper limit according to the DORA research it cites; use that as guidance, not a universal law. DORA: Continuous Integration
Common obstacles include long-lived branches, slow or unreliable tests, manual build steps, and delayed repair when the mainline breaks. Address the bottleneck that is actually slowing or destabilizing the team rather than adopting tooling for its own sake. Reliable, quick tests are more useful than a large test suite that routinely gives late or ambiguous feedback.
Continuous delivery aims to keep software deployable and releases low risk. It does not mean every change must be automatically deployed to production; continuous deployment is a separate practice and may not suit every product. Increasing release frequency without improving process and architecture can increase failure rates and burnout, while tools alone do not create the practices needed to realize their benefits. DORA: Continuous Delivery
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Use retrospectives to remove recurring causes
Use the retrospective to identify patterns behind debt and delivery friction, such as unclear standards, fragile tests, repeated merge conflicts, manual release work, or a component that regularly causes rework. Choose an improvement that addresses a high-impact cause, make it actionable, and inspect whether it helped. The Scrum Guide frames the retrospective as an opportunity to improve quality and effectiveness; impactful improvements can be addressed promptly or added to the Sprint Backlog. Scrum Guide
Measure whether the work improved delivery
Choose a small set of measures tied to the problem you are trying to fix. Useful signals include elapsed time from change to release, waiting time in review or testing, work returned for correction, time to recover a broken build, recurring defect or rework rates, and change fail rate. Interpret them diagnostically: do not reward a team simply for closing more debt tickets or optimizing one number at the expense of product outcomes.
DORA recommends value-stream mapping to find slow or error-prone steps. Mapping elapsed time separately from value-add time can reveal where work waits and how often it is sent back because it was not right the first time. Use those findings to choose a local improvement and agree on a practical future state with the teams involved. DORA: Value Stream Management
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