February 11th, 2026, posted in for_founders
by Miruna
AI has become a staple in software development projects. Developers use it to automate tasks, to get inspiration, to learn, or even to build entire pieces of software.
But when is it too much? When could you say you’ve used AI too much as a software developer? Can it make you regress? Or can it ruin apps you’re working on?
Here at UPDIVISION, we’ve been testing AI tools in software development for the last few years. We’ve adapted them to our needs and even used it to create our own tools. It helped junior developers learn faster, but with some caveats - as we explain further in this article.
But at the same time, we also saw AI ruin bits of code we’d worked on. It generated sloppy code that we had to take extra time to fix. It subtly encourages juniors not to learn and just generate entire apps.
In other words, AI has its pros and cons in software development. Used well, it can be very powerful and useful. But it doesn’t always work the way you want it to - especially when it doesn’t know what you actually want.
So in this article, we’re going to talk about when to use AI and when to stop using it in software development.
When to use AI in software development
People associate AI in software development with revolutionary software and tools. When, in reality, most developers use it to speed up their work, to get quicker code reviews, suggestions, or to help them find the best solution for the problem they’re trying to solve.
In other words, the best use of AI in software development is as a helper, as a lending hand that guides developers and helps them save time - not one that does all their work for them.
So in this section, we’re going to tell you what, from our expertise, are the best situations where you should use AI in software development.
Use AI as a coding partner
You can use ChatGPT alongside AI agents such as Cursor and Cline as “draft partners”. These tools help you get ideas (or code, directly). To make sure you’re making the best use of it, take a detailed look at what it generated and make sure it works for your use case scenario.
In other words, use AI to add to your own skills, not replace them. It’s supposed to aid, not do your work for you. Plus, you gotta make sure the solution it generates actually works for your project. You might risk ruining entire features, otherwise.
Don’t let AI build entire apps for you, but rather lend a helping hand. You’ll still have all your freedom and you can choose to use its solutions or not, or implement them as you see fit.
Use AI to speed up research
Do you need to find that very tiny detail out of many articles and documentation files? Or even codebases? If you don’t have time to skim through everything in order to find information, AI can help you speed up your research.
But be careful - AI isn’t foolproof. It’s likely to “omit” what you’re looking for. It might not look everywhere it should, or it won’t sort through information logically. If you can’t find the piece of information you need even with AI, consider taking the time to do research yourself.
If AI isn’t giving you the information you’re looking for, don’t waste time redoing prompts. Try using other AI models and not relying on the same one all the time: Claude might provide different info compared to Gemini, for instance.
Use AI to refactor code
You’ve been given an old piece of code that doesn’t work too well, but you don’t even know where to start. You know it needs refactoring, but you don’t need what, where, or maybe even why. AI can help find errors, inconsistencies, or even suggest ways you can improve a piece of code.
Avoid straight-up making AI fix your code. Use it as a helper, as a way to find issues you need to fix. And then fix those issues yourself, or get inspired through its suggestions.
Don’t forget - it’s not always right, and it could be using untested information put online by random people.
Use AI to bugfix
When having trouble finding the root cause of a bug, and you’re in a time crunch, it’s not a bad idea to ask AI to help look through your code and find what’s causing the problem. AI can help describe what’s going on within the app and even suggest what file or lines of code might contain the issue.
However, just like anything you use AI for, you have to be careful. If you choose to use AI to help you fix bugs, you have to make sure its solution 100% works for your project and doesn’t break existing functionality.
Use AI to help with complex architecture
We don’t recommend doing this too much, and again, be careful and pay attention when you do it. If your project requires a complex architecture, you can use AI for ideas on how to structure files & folders, and how to connect these with one another.
Use AI to help with code quality
AI is also useful to “audit” your app’s code. It can look for security flaws within your code, and it can locate places where you’ve already implemented a solution and which it can use as a point of reference. This way, you avoid duplicating the same solution in slightly different ways.
It helps keep your code cleaner and safer. But, just like our other suggestions, make sure to carefully review its suggestions before implementing. Don't rely completely on it to cover the entire codebase in one go, use multiple prompts to make sure it reaches all files and: make sure you find the best AI model for your use case.
When to stop using AI in software development
If you Google “when to stop using AI in software development”, an AI tool will give you the answer. And that, ironically, helps us point out when not to use it. When you look up something like this, you’re looking for real people giving their answers. But AI has become so ingrained in our day to day lives, that you’re forced to see its “opinion” first.
In software development, when and when not to use AI is a lot more specific. As much as it can help speed up your process, it can hinder your ability to learn & improve, and it can create issues within your code that will take months to fix.
So here are a few situations in which you should stop using AI in software development.
Stop using AI when you don’t understand
Alright, so you’re using AI because you need a solution for your code. But what happens when AI gives you a solution, but you don’t understand how it works. It does, but you don’t even know why. It just somehow fits into your codebase.
That’s not an ideal situation. What happens in the future if bugs show up? How can you fix a piece of code you don’t even understand? And worst of all - what will happen if another developer takes over the project? Will they be able to figure it out? Most likely, they’ll spend extra time understanding that solution and trying to work with it. You might be “saving time”, but your team will spend more of it fixing what you did.
Stop using AI as a junior dev
As a junior developer, you might be tempted to use AI to code because it’s the latest shiny new thing. Everybody is talking about it and saying you need to know how to use it to code. You might even be pushed to use it by your higher-ups.
But when you’re a junior developer, AI can do more harm than good to your code - and your development skills. Oftentimes it’ll confuse you, lead you on the wrong path without you realizing, and with your lack of experience you might not even understand the solutions it’s giving you. You’d be slowly sabotaging your growth.
If you really must use it, carefully review its recommendations and check with your senior colleagues to make sure you’re not breaking major projects or hiding ticking time bombs into an app’s code.
Stop using AI just because “it works”
If you aim to use AI just to implement its solutions without actually going through them, you’re setting yourself up for failure. Just because they work, doesn’t mean they’re actually good. You’re putting your trust into many lines of code you’re not even looking at.
When doing this, you risk adding new errors or critical issues to your code, without even meaning to. This is especially true for backend code, where we handle security, but even on frontend code, for instance on forms where users fill in data.
“It works” now, but what about later? Is what you should have in mind when implementing code generated by AI. Take the time to review what it gives you before you risk creating cracks in your code.
All in all, AI can help software developers move faster, check how secure & well-structured their code is, and it can help inspire & educate them. But it’s also an important lesson on responsibility and trust - how much can you truly rely on code that’s not written by a human?
Looking for software development services, with or without AI? Contact us and let’s see what we can build together.
