We've all heard the whispers, the hushed conversations in the corridors of the tech world. It's a monster lurking in the shadows, growing larger with every line of hastily written code and every rushed deployment. It's the Tech Debt Time Bomb, and it's ticking louder than ever.
On one hand, this is a good thing—job security! Someone needs to be around to continue to fix all of these problems. But for how long? You never know when someone on your team wins the lottery, you never know when the infrastructure trends of an entire industry may decide to shift sideways or chase a new rabbit down a hole. Today, Generative AI is the lit fuse for what will become a major problem down the line. It is the new, shiny toy that can reduce thousands of hours of coding down to a handful of days.
Remember that ol’ philosophy of “move fast and break things?” A lot of that stuff is still broken, and Gen AI will only continue to break things more completely. Now, after decades of breaking things, the new mantra seems to be—begrudgingly—“go back and fix stuff.”
Tech debt happens when the demands of the short term start to drag on long-term ROI. The challenge is that we rarely notice the long-term impact until it is far too late. The patch that was created on Wednesday to fix Tuesday’s problem eventually causes performance issues months down the line. Quick solutions rarely bring about great, long-term results.
In short: Code = Tech Debt. Always and perpetually, throughout the entire tech industry, all of the time.
A recent study by Stripe found that developers spend a staggering 33% of their time dealing with tech debt, costing businesses an estimated $3.61 trillion globally.
And according to a Protiviti survey of more than 1,000 tech leaders, nearly 70% of organizations view tech debt as a blocker to their ability to innovate.
This issue isn't a result of laziness or short-sightedness. We know that companies trust their CTO and IT departments to conduct their due diligence when it comes to adopting new technology into their organization. Sadly, few can accurately predict the future, which means the long-term impacts of any innovation are famously unpredictable. Who could have predicted an app would go from a way to keep tabs on your friends to something that is blamed for everything from the loneliness epidemic to destabilized global governments? No matter how stern the vetting process, any new technology can potentially bring about security concerns, workflow incompatibility, and other bugs to fix down the line.
Code—of any weight, length, or duration—promises tech debt. This is the kind of debt that never gains negative interest nor is it forgiven. It never goes away, it is always a consideration, and eventually the size of your company’s tech debt effectively puts your organization underwater. Trying to fix your tech debt problem almost always results in more debt—code fixing code that was coded to fix previous versions of code.
Anyone who has worked in tech for any amount of time has likely seen their share of Frankensteinian systems. The tech history of some of our developers is haunted by having to manage and triage ad hoc code solutions. What started as a robust bit of script quickly aged into the “legacy code” at the core of the company’s product. As the needs of the company, the customers, and even the business environment changed, the code had to be modified to stay relevant and useful. Even the simplest changes can take weeks to develop. Still, they were prone to errors and even creating new problems, and the documentation was usually incoherent at best, if it existed at all.
These challenges are amplified when the variable of time enters the equation. Shareholders and stakeholders want higher-revenue, higher-performing platforms as soon as possible. If your code is causing outages, every minute of downtime could be a significant toll on revenue from your userbase. When time is quite literally money, why not use a magic bullet?
If you hired someone who knew how to write in every language, understood how the languages worked with one another, and could write and test mountains of code in the blink of an eye, all your problems would be solved. Right? This is exactly what should have happened with generative AI, but it hasn’t.
As with anything in this world, you get to pick two of the three: Fast, Cheap, or Good. Generative AI does what traditional coders have done for decades (create tech debt), but at an exponential rate. The wave of Generative AI seems to have caused problems long before the promise of the solution ever showed up. Code may show up instantly, but testing that code and finding out why it fails is next to impossible because developers are usually blind to the creative process that goes into code.
If you can’t watch it go up, you have no idea how far to tear down before things start working again.
Generative AI has promise. But for organizations that carry tech debt (as a safe assumption, let’s say everyone), using AI to resolve code issues can amplify problems and ramp up the interest on the debt.
There it is again: go fast, break things. The barrier to entry for AI has never been lower—for better or worse. The widescale rollout of applications means more people than ever can discover what is possible while also collecting information on how AI systems can be improved. Just like every other tech fad gold rush, companies are pressured to either jump on the bandwagon or get left in the dust. By the time the stampede passes, what is left?
Developers have long known the importance of planning and consideration of the variables for everything they code into their systems. For a lot of businesses, this mindset seems to have gone out the window. Not enough testing, oddly designed systems, iffy documentations… more debt.
AI is dependent on vast amounts of data. But your company is dependent on very specific types of data—all of which should be as accurate and complete as possible. If AI ingests data that is missing, flawed, or biased, the results will be inaccurate and potentially harmful. No sense in cooking with bad eggs. If your data isn’t top notch, then AI will only bring a world of headaches. Generative AI is the fastest way to make sure you create a messy web of systems that is impossible to update, scale, or even understand.
So, what then?
The solution for any kind of debt is a sustainable mindset: Don’t spend more than you make, and don’t take on more than you can sufficiently manage. Same goes for tech debt. If code is always the source of your tech debt, then remove yourself from a code-dependent environment.
Nextworld is an entirely no-code environment for this exact reason. No code for our users, no code for our internal staff—the entire platform is designed to be codeless. Why? Faster development and no errors. If custom code only invites problems, revoke the invitation.
Until recently, “no-code” was synonymous with “limited capabilities.” If you wanted no-code apps to work with the rest of your system, you had to adjust your system or how your data was formatted—most of which required some kind of custom code to make the integration happen and the limited capabilities worthwhile. More code, more debt. Fortunately, we are in an age when no-code platforms mean the end users can do more than what they likely could with their coded applications. Nextworld is the enterprise-grade, no-code platform with intuitive tools that create purpose-built apps. The platform unlocks flexibility, whether you are creating a single app that can seamlessly integrate with your current stack or designing a complete solution that updates and adopts integrations without the need for code revisions.
And, most importantly, no-code is how our Native AI is possible. This is the fundamental difference of how Nextworld makes enterprise platform management easier, more integrative, and futureproof, no matter what comes next in our industry. Plus, it is the right kind of fast. The kind of fast that is perpetually sustainable with everything from your legacy tech to the applications you’re onboarding today, plus whatever innovations the future holds. Nextworld is the platform that puts you ahead of what’s next.
Learn more about how to eliminate tech debt by removing the root of the problem:
Custom code.
