I have been building websites and software since 1996. In those 30 years the tools have changed a lot. Hand-coded HTML gave way to PHP, then Rails, then React, and now Next.js. But nothing has moved the needle on speed like AI-assisted development.
You can describe a website in plain English today and have a working prototype in minutes. That is impressive. It is also risky in ways the industry is not talking about enough.
The Speed Is Real
Tools like GitHub Copilot, Claude, and ChatGPT have changed how fast you can go from idea to deployed site. Scaffolding a project, writing boilerplate, building responsive layouts. Work that took days now takes minutes.
For small businesses in Arizona that means lower development costs and faster time to market. In many cases that is exactly what happens.
But speed without oversight creates problems that do not show up until it is too late.
Security Nobody Audits
AI models generate code based on patterns in their training data, and that training data includes millions of examples of insecure code. Stack Overflow answers with SQL injection vulnerabilities. Tutorials that store passwords in plaintext. API examples that hardcode secrets in the frontend.
When a developer writes code by hand they think about security as they go. When AI generates fifty files in thirty seconds, who reviews each one for:
- Cross-site scripting (XSS) vulnerabilities in rendered content
- Server-side request forgery in API routes
- Authentication bypasses in middleware
- Exposed environment variables in client-side bundles
- Unvalidated inputs that open the door to injection attacks
Too often the answer is nobody. The person prompting the AI may not know what to look for. The AI does not understand security. It generates patterns, and those patterns frequently include vulnerabilities. We have audited sites that were "built with AI" and deployed without any security review. The speed that made the build cheap makes the breach expensive.
Over-Complexity as the Default
AI has a bias toward complexity. Ask for a contact form and you might get a form library, a validation schema, a custom hook, an error boundary, a toast notification system, and an analytics event layer. All you needed was a <form> that sends an email.
Over-engineered code has real costs:
- Maintenance. Every abstraction is a future debugging session. Code that nobody on your team understands is code nobody on your team can fix.
- Performance. More JavaScript means slower pages. Slower pages mean worse SEO rankings and higher bounce rates. Google measures Core Web Vitals and does not care how cool the animation library looked in a demo.
- Dependency risk. AI reaches for the newest packages. Today's hot framework is tomorrow's abandoned dependency with unpatched CVEs.
The best code is the simplest code that solves the problem. AI optimizes for pattern completion, not simplicity. Those are different things.
Everything Is Starting to Look the Same
Visit ten small business websites built this year. Count how many have:
- A hero section with a gradient background and a "Get Started" button
- Three feature cards in a row with icons
- A testimonial carousel
- A "How It Works" section with numbered steps
- A dark footer with four columns
Eight out of ten will have that exact layout. Maybe nine. AI tools have converged on a median design language. It is clean and professional and completely interchangeable. Your plumbing company website looks like a fintech startup which looks like a dental practice which looks like a law firm.
Your website is supposed to differentiate you. When every site looks like it came from the same template, the only differentiator left is price. That is a race to the bottom.
Real design starts with understanding the business, the audience, and the competition. AI can execute a layout. It cannot originate a design that actually speaks to a specific audience.
What We Recommend
We tell our clients:
- Use AI for speed, not for decisions. Let it scaffold and generate boilerplate. Do not let it make architectural or design choices unchecked.
- Do a security review. If AI generated the code, assume it has vulnerabilities until a human proves otherwise. This is the cost of the speed you gained.
- Keep it simple. If you cannot explain what every dependency in your project does, you have too many.
- Invest in real design. A custom design that reflects your brand will outperform a generic template every time. The money you save using AI for development should go toward better design, not toward skipping it.
- Work with developers who understand both. The right partner uses AI to move faster while applying judgment and experience that AI does not have.
The Bottom Line
AI has not made web developers obsolete. It has made the gap between good developers and everyone else wider. The good ones use AI to deliver better work faster. The rest use it to ship more code with less understanding of what they built.
If you are an Arizona business looking at your web presence, the question is not whether AI was involved in building your site. The question is whether someone who understands security, performance, and design was involved too.
We use AI tools at Agave IS. Every line of code still gets reviewed by a human who has been doing this for three decades. That is the difference between a site that is fast to build and a site that is built to last.