Why AI Produces Bad Architecture
The AI can’t possibly understand your product vision, your business logic, your goals. It doesn’t know whether your application is going to require serving 10 users or 10,000. It simply wants to predict the next token to satisfy it. And this is the first issue.
This is exactly what it all means:
• Lack of Modular Design: The code generated by AI systems will often have a lack of proper separation of concerns. The tightly coupled elements make scaling a challenge.
• Excessive Use of Patterns: Computers may end up spamming the best design patterns, whether applicable or not. This leads to the over-engineering of simple problems.
• Shortcuts in Scalability: “AI systems are optimizing for getting the job done rather than getting it done right. You’ll end up with a functional feature, but one that will fail when subjected to stress.”
The thing is, AI doesn’t have bad intentions. It simply doesn’t know any better. And it doesn’t know to avoid hurting you in your product.
Introduction
Within the quest to deliver code faster with AI-assisted development tools, there is something that is subtly going out the window – software architecture. Additionally, while AI solutions such as GitHub Copilot or ChatGPT may be able to spit out code at incredible speeds, there is no understanding of good software architecture. That is a function of a human being.
As a company that specializes in App&Tech, like Appricotsoft, we have had our fair share of startups and scale-ups that use AI software to develop their MVPs, only to pay a bitter price down the road. In today’s blog, let us show you why it is happening, how it is affecting you, and what you should do about it.
What Happens When You Build on Bad Architecture
In the beginning, everything goes well. Your MVP is up and running. People from the financial world are expressing interest. Users are flocking to your site. But then there’s:
• The time it takes to develop the addition or improvement is longer
• Bugs occur in scattered areas of the application.
• Entire modules of code need to be rewritten to accommodate a single new requirement.
• “Fragile” or “untouchable” – devs complain.
This is known as technical debt, and it adds up quickly. Expect to need a software audit or, better yet, a complete rewrite.
We had a founder at Appricotsoft who came to us when they got stuck. They had built an MVP using their own AI assistance to bring to market quickly, but a few months into scaled user engagement, the underlying architecture issues were made manifest. “It wasn’t working well, but it wasn’t failing in a way that was obviously wrong.”
AI Won't Save You from These Problems
In fact, they are often created by AIs themselves. Code quality plummets without human interference. Architecture is not about syntax; it’s about system comprehension, trade-offs, and business needs. This is something that AIs are incapable of inferring.
So, first off, let’s get one thing straight: it isn’t a rant against AI. We actually use AI every day at Appricotsoft – for testing, documenting, and debugging our applications. Nevertheless, it is not our systems designer.
You are risking these things if you are using AI technology without monitoring:
• Security Vulnerabilities
• Lack of consistency in names and structure
• Duplicate logic
• Zero documentation
Worse still? Founders often don’t even know a problem exists until it’s too late.
Learning Which Good Architecture Looks Like (Yes, Even in MVPs)
Your MVP is not necessarily a bulletproof enterprise software. However, it is likely to follow proper architectural hygiene practices.
Here’s what we recommend and implement for our clients:
✔️ Modular, reusable components
✔️ Business logic tier separated from UI tier
✔️ Scalable deployment environment (Docker, CI/CD pipeline setup)
✔️ APIs and interfaces documentation
✔️ Audit trails, even for early products
So, when you build an architected MVP, it’s ensured that your version 2.0 will never have to “burn it all to the ground.” This saves you time, money.
What You Can Do: Founder’s Checklist
Not technical? That’s fine. Here are things you can do to keep architecture on schedule:
• Get a professional audit – Code audit in the startup or AI code might give insight into errors early
• Questions to ask about architecture reviews – Ensure that your development team or vendor takes architecture into account when developing.
• Insist on documentation – If your code is not accompanied by docs, get a human to write them.
• Monitoring performance trends – If new functionality is impacting performance, then it’s probably an architecture problem.
• Don’t follow the features blindly – Every Quick Solution might bring Permanent Pain.
Even one architecturally aware developer on staff can help turn this ship around.
The Role of Appricotsoft
We, at Appricotsoft, have worked with several startups to help them develop a scalable platform from the MVP created using the latest technologies like AI. There is a need to work on a combination of speed and system
Here’s how:
• We conduct early technical audits for startups to highlight issues even when they’re small and easily fixable.
• “Our team consists of architecture – first developers, also known as system thinkers, who think about systems, not screens.
• We assist in refactoring code generated by AI to be production-worthy.
• We implement your business logic into scalable architectures, so your app can grow alongside your operations.
You don’t have to throw away that MVP of yours; you only have to have us by your side to make it the best. We are proud to say that this is what we do best.
Conclusion: You Can’t AI Your Way Out Of a Broken Foundation
AI loves to generate. But it does not love to plan. And it certainly does not know what your product needs to turn into in six months.
“That’s your job. And ours.”
Poor architecture doesn’t bite right off the bat. It bites hard when it bites, however. Don’t wait for that to happen. Let us help you build something that will last.
👉 Read more about how to verify AI-generated code before shipping
👉 See also: Why AI-created products fail after launch
But if you’re not sure whether your app is on shaky grounds, then let’s talk. We’d be happy to examine your stack to see where you can improve.