When AI Builds Your App But Can't Fix What It Breaks

Something has shifted in the last couple of years, and honestly, I think it's mostly a good thing.

Founders with great ideas no longer have to sit on those ideas waiting until they can afford a developer, find a co-founder, or teach themselves to code from scratch. Tools like Cursor, GitHub Copilot, Bolt, Lovable, and a dozen others have genuinely lowered the barrier to entry for getting software in front of real users. I've spoken to people who have launched working MVPs — complete with authentication, subscription billing, and a reasonable UI — without writing a single line of code themselves.

That's remarkable. And I mean that sincerely, not sarcastically.

But here's the part nobody talks about loudly enough: getting something running and getting something right are two very different things. And I'm seeing the consequences of that gap more and more in my inbox.

The Promise Is Real

Let me be clear before I say anything else — I'm not here to dismiss AI-assisted development. I use it myself every single day. It helps me move faster, think through problems from different angles, and prototype ideas in a fraction of the time it would have taken me a few years ago.

For a non-technical founder, the ability to describe a problem in plain English and get working code back is genuinely transformative. You can test whether your idea has legs before spending tens of thousands on a development agency. You can show investors something real. You can talk to customers with a live product rather than a slide deck. That's powerful stuff.

And PHP itself keeps getting better in ways that support all of this. The PHP 8.x release series has brought property hooks, asymmetric visibility, lazy objects, and a raft of improvements that make the language more expressive and the code easier to reason about — which matters when you're trying to move quickly whether you're a developer or working with AI-generated output.

The Problem Nobody Warns You About

Here's what I'm actually seeing when founders come to me after the honeymoon period ends.

AI tools are brilliant at producing code that looks correct and mostly works in a happy path scenario. But they don't have 25 years of scar tissue. They haven't shipped a SaaS product that fell over under load at 2am on a Saturday. They haven't had to explain to a client why their customer data was exposed because an Eloquent query forgot a where clause. They haven't felt the slow creep of technical debt turning a nimble codebase into something nobody wants to touch.

Some of the most common things I find when I look under the hood of an AI-built Laravel project:

Security issues that aren't obvious. Mass assignment vulnerabilities, missing authorisation checks on routes, API endpoints that don't properly validate who's asking for what. The app works fine in testing when you're the only user. In production with real adversarial users, it's a different story.

No real error handling. AI tends to write the happy path beautifully. It often forgets that third-party APIs go down, that users will submit unexpected input, and that queued jobs need to handle failure gracefully.

Database structures that make sense now but hurt later. I've seen schemas that would have caused serious headaches the moment the client needed a basic reporting feature or wanted to add multi-tenancy. Changing a database structure in a live application with real customer data is painful and risky work.

No tests. If AI does generate tests, they're often testing the implementation rather than the behaviour, which means they give a false sense of confidence and don't catch regressions.

Performance time-bombs. N+1 queries hiding everywhere. No caching strategy. Jobs being run synchronously that should be queued. Everything feels fine with ten users and becomes a nightmare with a thousand.

Code that nobody can maintain. Large, tangled controllers doing too much. Business logic spread randomly between models, controllers, and one-off helper files. No consistent structure. This isn't a dig at AI — it's the natural result of building iteratively with prompts rather than with an architectural plan.

None of these things stop the app from launching. Some of them won't bite you for months. But they all come due eventually.

What I'm Increasingly Doing

Over the past year or so, I've found myself working with a growing number of founders and early-stage teams who built their initial product with AI tools, got some traction, and are now hitting walls they can't get past.

Sometimes it's a specific bug that no amount of prompting seems to fix. Sometimes it's performance that's suddenly terrible now that real people are using the app. Sometimes it's a security scare that's shaken their confidence in what they've built. And sometimes it's simply that they want to keep growing the product but the codebase has become a tangle that's impossible to extend without breaking other things.

What I offer in these situations is a bit different from a traditional development engagement. I'll sit down — sometimes literally over a video call — and go through what's been built. I'll explain in plain English what's causing a problem and why it's a problem. Not to make anyone feel bad, but because understanding the 'why' helps you make better decisions going forward.

Then I'll help fix it, as quickly and cost-effectively as possible.

And here's where my use of AI actually becomes an advantage rather than a threat: because I have the experience to know what good code looks like, I can use AI tools to produce it faster while still catching the things that need catching. I'm not prompting blindly and hoping for the best. I'm directing, reviewing, testing, and shaping the output with 25 years of context about what breaks in production, what scales, what's maintainable, and what's genuinely secure.

The difference between an experienced developer using AI and a non-technical founder using AI isn't the tool — it's the judgment applied to the output.

You Don't Have to Start From Scratch

One of the first things I tell people in this situation: the work you've done isn't wasted. In most cases, we're not talking about throwing everything away. We're talking about identifying the specific pain points, understanding what's fragile, and fixing or rebuilding those parts in a way that gives you a solid foundation.

Sometimes that's a targeted security audit and a round of fixes. Sometimes it's a database migration and some query optimisation. Sometimes it's introducing proper service layer architecture so the codebase is actually extensible. And yes, sometimes a part of the app is genuinely too tangled to unpick cost-effectively and needs a clean rebuild — but even then, the rebuild goes much faster when there's an existing product to reference.

If you've built something with AI tools and you're starting to feel like the foundations aren't quite right — or you've hit a bug or a performance problem that nothing seems to fix — I'd genuinely love to have a chat. No judgement. The fact that you got something built and in front of customers at all is something to be proud of.

Let's just make sure it can carry the weight of what comes next.

Interested in getting your AI-built Laravel app reviewed or rescued? Get in touch — I'm always happy to take a look.