Technical debt, explained for the people paying for it.
If every new feature seems to take longer than the last and your developers keep asking for time to "refactor", you are probably paying interest on technical debt. This guide explains it in business terms, including the new kind created by fast, unreviewed AI-generated code.
Technical debt is the future cost of shortcuts taken in software today.
Like a business loan, some technical debt is sensible. Launching with a simpler design to meet a deadline or test a market can be exactly the right call. The problem is interest: every shortcut left in place makes later changes slower, riskier and more expensive, and that interest compounds.
Business owners rarely see the debt itself. They see its symptoms: estimates that keep growing, bugs that return after being fixed, a developer who is the only person able to touch a certain part of the system, or a simple request that is somehow "a big job".
The goal is not zero debt. No healthy software has none. The goal is to know roughly how much you carry, where it sits, and whether you are paying it down faster than you are adding to it.
The common types of technical debt
Debt builds up in different ways, and each needs a different fix. Naming the type helps you have a sensible conversation with your team or vendor.
Deliberate shortcuts
Known compromises made to hit a date. Fine if recorded and repaid; harmful when forgotten once the pressure passes.
Outdated dependencies
Frameworks, libraries and servers that were never upgraded. Eventually they stop receiving security fixes and upgrades become projects in their own right.
Design that no longer fits
An architecture built for the business you were three years ago. Nobody made a mistake; the business simply outgrew the original assumptions.
Missing tests and documentation
Without automated tests, every change risks breaking something unrelated, so developers slow down or avoid touching fragile areas altogether.
Unreviewed AI-generated code
AI tools produce working code quickly, but often duplicated, inconsistent or poorly understood by the team. Debt now accumulates at the speed of generation.
Knowledge concentrated in one person
When only one developer understands a system, their holiday, resignation or burnout becomes a business risk rather than an HR matter.
How to tell technical debt is hurting your business
You do not need to read code to spot these. If several sound familiar, the interest payments are already significant.
Similar features take longer each time
Delivery slows even though the team has not changed or shrunk.
Fixing one bug creates another
Releases need a round of emergency fixes, and customers notice regressions.
Estimates come with long lists of caveats
Developers struggle to predict effort because they cannot see what a change will affect.
Onboarding a new developer takes months
The codebase is hard to understand without a guided tour from the original author.
Security updates keep getting postponed
Upgrading a library is considered too risky, so known vulnerabilities stay in place.
Nobody can explain the AI-written parts
Large blocks of generated code were accepted because they worked, and no one on the team can confidently change them.
How to reduce technical debt without stopping the business
A full rewrite is rarely the answer. Sustainable repayment happens alongside feature work.
Make the debt visible
Ask the team to list known problem areas with a rough cost of leaving each one alone. A short, honest register beats a vague sense of unease.
Prioritise by business impact
Fix the debt that sits in parts of the system you change often or that carry security or revenue risk. Ignore ugly code in corners nobody touches.
Reserve steady capacity
Many teams allocate a fixed share of each sprint to repayment. Consistency matters more than the exact percentage.
Use AI to understand and test legacy code
AI-assisted tools are genuinely helpful for explaining unfamiliar code, generating missing tests and drafting upgrades, with engineers reviewing every change.
Stop adding new debt carelessly
Code review, automated tests and clear rules for accepting AI-generated code prevent the register from refilling as fast as you clear it.
How business owners should discuss technical debt with developers
Developers often struggle to justify debt work because they describe it in technical terms, and business owners understandably hear "time not spent on features". Ask them to translate each item into consequences: slower delivery on a named roadmap item, a security exposure, higher hosting cost, or reliance on one person.
Equally, be wary of a team or vendor that blames all slowness on debt and proposes a full rebuild. Rebuilds take longer than planned and create fresh debt of their own. An independent review of the codebase is a sensible step before approving anything large, especially if much of the code was produced quickly with AI tools and has not been reviewed by someone senior.
Questions we often hear
What is technical debt in simple terms?
Technical debt is the extra future work caused by choosing a quicker or easier solution in software now instead of a more robust one. Like financial debt, it can be useful in the short term, but the interest shows up as slower development, more bugs and higher risk until it is repaid.
Is technical debt always bad?
No. Taking on deliberate debt to launch sooner or test an idea is often a good business decision. It becomes a problem when it is not recorded, not repaid, or allowed to build up in the parts of the system the business depends on most.
Does AI-generated code create technical debt?
It can, quickly. AI tools make it easy to accept large amounts of code that works today but is inconsistent, duplicated or not understood by the team. With senior review, tests and clear conventions, AI can also help reduce debt by explaining legacy code and generating missing tests.
How do you measure technical debt?
There is no single number. Useful indicators include how delivery speed changes over time, the share of work spent on bug fixes, test coverage in critical areas, the age of key dependencies, and how long new developers take to become productive. A code audit can turn these into a prioritised view.
Should we rewrite our software to get rid of technical debt?
Rarely as a first choice. Full rewrites commonly take far longer than expected and pause feature delivery. Incremental improvement of the most-changed, highest-risk areas usually delivers better results, with a rewrite reserved for systems that genuinely cannot be upgraded.
Related reading and tools
Worried technical debt is slowing you down?
Describe the symptoms you are seeing and how your software was built, including any AI-generated code. We will tell you what is likely going on and whether it needs a review, a plan or simply patience.
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