How to reduce tech debt during software development

Quick summary

Technical debt can quietly slow software development. Features take longer to deliver, maintenance demands increase, and engineering teams spend more time working around existing systems instead of building new capabilities.

For B2B SaaS companies, the challenge often extends beyond code quality. Architectural decisions involving multi-tenancy, workflow orchestration, integrations, and infrastructure can create long-term maintenance burdens as products and customer bases grow.

The good news? Reducing technical debt doesn't always require rebuilding your software from scratch.

By adopting reusable components, standardizing workflows, improving development practices, and leveraging managed infrastructure, software companies can address existing technical debt while reducing the risk of accumulating more.

In this guide, we'll explore what causes technical debt, how to identify its warning signs, and how a low-code development platform can help teams build more maintainable, scalable software.

Why listen to us 

Launchpad is the platform B2B software companies use to ship real products, not demos. It’s built on a foundation based on Pega’s workflow engine, which has powered enterprise automation for 40 years. The hard parts like multi-tenancy and scale are proven, not theoretical. 

You can see it in the teams that build with us. Fielo runs production software for customers like Google and Audi. Connex uses our solutions to ship products with reduced tech debt. Quavo increased their revenue by 25X after partnering with us.

We have a strong opinion about architectural debt. Teams come to us to get out from under it, so we see exactly how it builds up and what it costs. Everything in this guide comes from real experience.

What is technical debt?

Technical debt is what you owe later for moving quickly now. The programmer Ward Cunningham came up with the idea back in 1992, when he compared rough first-draft code to taking out a loan. Borrowed speed is useful as long as you pay it back. If you don't, every change you make afterward costs a little more, until eventually the code costs more to maintain than the original shortcut ever saved you.

Some debt is completely fine. Shipping a rough first version to land a customer or test an idea is usually the right call, and good teams take on debt deliberately all the time. It only becomes dangerous when nobody's tracking it, and nobody's paying it down. Left alone, it seeps through the codebase until you can't even say how much you're carrying.

In a real software product, it rarely looks dramatic. It's the boring stuff that gets you, such as:

• A hard-coded integration that breaks every time a third-party API changes.
• An auth flow someone threw together in a weekend and never hardened.
• Billing logic copied into three services that have drifted out of sync.
• An MVP database schema that was only ever meant to be temporary.
• Tests skipped to hit a launch date that nobody went back to write.

None of this feels urgent. Put it all together, though, and it's why a change that should take an afternoon eats two days.

What causes technical debt in modern SaaS teams

Most of the debt dragging SaaS teams down has nothing to do with careless developers. It comes from the same structural choices, made over and over on every project, and five of them show up again and again:

• Rebuilding common features. Every new product gets its own authentication, billing, and notification systems built from scratch, and the team then owns the maintenance of that undifferentiated work indefinitely.
• Disconnected tooling. A stack assembled one tool at a time leaves gaps that get filled with brittle glue code, the kind nobody fully understands and everybody hopes someone else will maintain.
• Custom infrastructure. Hand-rolled multi-tenancy, deployment, and scaling logic need constant attention. Over time, they become the corners of the system that engineers learn to step around rather than touch.
• Poor workflow orchestration. When business logic is scattered across multiple services, the rules and processes are not managed in a single, centralized location. As a result, even a small change to a business process can require updates in many different files.
• Scaling MVP architecture. The shortcuts that won the first customer rarely survive contact with the hundredth. Yet teams keep stretching them well past the point where they should have been replaced.

Look at that list again, and the pattern jumps out. Almost none of it is about a bad line of code, but about how the whole thing is put together.

Code debt vs system debt

It's worth splitting technical debt into two kinds because you don't pay them back the same way.

Code debt is about how something is written. It's the tangled function, the copy-pasted logic, and the test nobody wrote. As it all exists inside a single file, a focused refactor usually clears it out.

System debt, or architectural debt, is another beast. It's the data model fighting against multi-tenancy, or your workflow logic smeared across half your services. Besides, it doesn't exist inside any one file. It lives in how they all connect, which is exactly why cleaning up individual functions does nothing for it.

In SaaS, system debt is the expensive one. Multi-tenancy, per-customer configuration, and the sprawl of interconnected workflows all exist at the architectural layer. This is precisely where debt is hardest to see early and most painful to remove once it has set.

What architectural debt actually costs you

If you’re running a B2B SaaS company, architectural debt isn’t some quiet engineering problem buried in the codebase. It lands straight on your margins and starts with repetition. 

Every product kicks off from a slightly different base. So, your team rebuilds the same plumbing again and again, then keeps a separate copy for every customer or product line you support. Each new build takes longer than the last, not shorter, and the engineers who should be working on what differentiates you are stuck keeping old systems alive. The cost isn't small for this.

Stripe's Developer Coefficient found that developers spend over 17 hours per week dealing with maintenance issues, such as refactoring and debugging, plus an extra 4 hours dealing with “bad code.” McKinsey puts a number on the business side, too. It pegs technical debt at 20 to 40 percent of the value of a company's entire tech estate. While CIOs say another 10 to 20 percent of their new-product budget gets swallowed up servicing it (Tech debt: Reclaiming tech equity | McKinsey).

For a B2B SaaS company, that math is unforgiving. Growth ultimately comes from hiring more engineers, not from leverage. Your headcount climbs faster than your revenue, and your margin keeps narrowing as the codebase ages and the maintenance load grows.

Why fast-moving teams create more debt

It's tempting to blame speed, but it isn't the problem. Speed with no structure under it is.

Moving fast means taking shortcuts, and under a deadline, that’s usually smart. The catch is what happens next. Those shortcuts quietly harden into architecture before anyone revisits them. The temporary fix becomes the foundation on which the next three features are stacked, and nobody ever circles back to clean it up.

AI has made this easy to do at scale, mostly because it writes code faster than anyone can review it, and the damage is already showing up in the numbers. Google's 2024 DORA report found that a 25 percent jump in AI adoption came with a 7.2 percent drop in delivery stability. Veracode's 2025 study went further, finding that across more than 100 models, 45 percent of the code shipped with security flaws, rising to 72 percent for Java.

The stakes are bigger than security alone. Microsoft CEO Satya Nadella has warned that AI could “collapse” traditional SaaS business applications altogether, with AI-native startups offering superior solutions at lower prices. The companies most exposed are those still propping up brittle architectures because they can’t ship new capabilities fast enough to keep up.

That doesn’t make debt inevitable, though. AI just magnifies whatever you’ve already built. Point it at a solid architecture, and it speeds up good work. Point it at a shaky one, and it churns out debt faster than ever. Either way, it comes back to the underlying structure, which we dig into in our guide on building enterprise software with AI.

How low-code platforms reduce technical debt

The shift that changes the trajectory is simple to state and harder to accept. Code-level refactoring alone may not resolve architectural debt. The foundation itself may have to change. That’s where low-code platforms earn their keep. Instead of helping you mop up debt after the fact, they go after it where it's most expensive, and they do it in a handful of concrete ways:

• Reusable components. You build a feature once and use it everywhere, which kills off the copy-paste sprawl that quietly multiplies what you have to maintain.
• Standardized workflows. There’s one way to model a process, so when it changes, you change it in one spot instead of chasing down every copy in the codebase.
• Shared logic. Your business rules live in one place rather than being rewritten inside every service, so they stay consistent as the product and the team grow.
• Visual orchestration. You can actually see how the system fits together, so fragmentation shows up early, when it’s still cheap to fix, rather than blowing up as a production incident six months later.
• Built-in infrastructure. Multi-tenancy, security, and scaling come managed instead of hand-built, so the priciest kind of system debt never gets the chance to pile up.

The payoff is simple. Your team stops sinking hours into plumbing and starts spending them on the product people are actually paying for. There’s one caveat, though. Not every low-code tool clears this bar, since plenty are built for quick prototypes, not real production systems. B2B SaaS asks a lot more of security, scale, and reliability, so the platform you choose matters as much as the decision to use one.

The “build once” architecture model

The most durable way to reduce technical debt is also the least exciting one, which is to stop creating the architectural kind in the first place. The idea fits in three words: build once, reuse everywhere, and it cuts hard against how most teams work.

The usual approach rebuilds the same core layers for every product and every customer, which is exactly how architectural debt snowballs. A build-once model breaks that loop, and Launchpad is built around it from the ground up, not retrofitted to look the part. It shows up in three places:

Reusable application layers

You define your core layers once, and your UX, workflows, data models, and integrations become shared building blocks. On Launchpad, these layers are model-driven components, so a feature you build for one app is reused across the rest rather than copied into them. 

Every new product is assembled from parts that have already proven themselves in production, so there's less to write and far less to maintain later.

Tenant provisioning is built in

Multi-tenancy is the classic source of system debt, mostly because teams insist on building it by hand and then spend years wrestling with the result. 

Launchpad handles tenant provisioning for you, so onboarding a new customer is a configuration step rather than a fork of your codebase or a separate branch to babysit. The architecture stays the same, no matter how many tenants pile on top.

Configurable deployments

Customers will always want different setups. The only question is whether you give them that with code or with configuration. As Launchpad runs on a managed runtime, configuration does the heavy lifting. So each variation is a settings change rather than a new branch of your architecture. One foundation ends up powering many products with a fraction of the upkeep.

Put those three together, and you get the build-once model without having to build the build-once machinery yourself. That’s how you grow your customer base and your product portfolio without growing the pile of debt that usually comes with them.

Warning signs your team is accumulating tech debt

Technical debt rarely walks up and introduces itself, so you learn to spot it by the marks it leaves. If more than a couple of these feel a little too familiar, your architecture is already taxing how fast your team can move:

• Small, routine changes take way longer than they should.
• You keep rebuilding the same core features for every new product or customer.
• Releases break things in corners of the system that seemed totally unrelated.
• Engineers quietly steer clear of certain modules because they're too risky to touch.
• Onboarding a new customer somehow means standing up a whole custom codebase.
• Your roadmap stalls while the maintenance pile just keeps growing.
• Your most senior people spend more time patching the past than building the future.
• Nobody can explain, from start to finish, how the whole system fits together.

If several of these warning signs appear consistently, investigate the underlying causes. Examine whether the problems originate in code quality, testing practices, architecture, or development processes before deciding how to address them.

How Launchpad helps reduce technical debt

Launchpad is built around the build-once model. That's exactly why it works against the architectural debt that most damages SaaS teams. It pairs no-code development with a fully managed, production-ready runtime, so you ship enterprise software without rebuilding the foundation every time you start something new. In practice, that shows up as a few concrete things:

• Enterprise infrastructure built in. Multi-tenancy, security, and scaling are handled for you, so the most expensive category of system debt never starts piling up.
• Workflow orchestration. Pega’s battle-tested engine keeps your business logic in one place, instead of letting it splinter across a growing sprawl of services.
• Reusable, model-driven apps. Build an application once and reuse it across products and tenants, so your upkeep shrinks even as your portfolio grows.
• Ready for production on day one. There’s no painful rewrite waiting between your prototype and your launch, which frees your engineers to build the IP that sets you apart instead of the plumbing that doesn’t.

You can see it in how fast teams ship. Fielo, which counts Google and Audi among its customers, reduced development time by over 66 percent after moving to Launchpad. That fits with what McKinsey found across the board. Teams actively managing their tech debt can free up as much as 50 percent more of their engineers’ time for work that actually moves the business (Tech debt: Reclaiming tech equity | McKinsey). That’s exactly what a build-once foundation is for.

Reduce debt at the root, not the surface

The hard truth about technical debt in SaaS is that it's hardly ever really about the code. It's an architecture problem wearing a code problem's clothes, which is why patching functions one at a time so rarely changes anything for long. You can keep cleaning up code forever, but as long as the foundation stays put, the interest just keeps compounding underneath you. 

The teams that finally get out do something bigger. Instead of recreating the same underlying infrastructure and components for each new product, they can build reusable foundations that span multiple products. By relying on shared layers, managed infrastructure, and common workflows, they can maintain a consistent and unified architecture as the organization grows. 

That's what it takes to reduce technical debt and actually keep it down. You trade a permanent maintenance tax for faster releases and a lot more room to build the things customers are happy to pay for.

Want to see how it looks for your own product? You can try Launchpad Explore for free, or book a strategy session, and we'll map the route from wherever your architecture stands today.