Rapid Growth
Like any tool, AI is only as good as the person using it. It can write code and generate content, but it doesn’t understand individual business needs, long-term requirements, or the practical implications around security, performance and edge cases.
I’ve embraced AI and use it daily for specific tasks. It’s particularly useful for repetitive work and code review, spotting issues like a missing brace buried deep in a large codebase far faster than I ever could. Used this way, AI saves time and, ultimately, saves clients money. That’s a good example of experience using technology properly.
AI can, of course, do much more than just find errors or speed things up. But like any powerful tool, in the wrong hands it can create problems that only surface later, often at a much higher cost. It’s easy to confuse confidence with tools for real understanding of a project, its constraints and the consequences of the decisions being made.
I’ve worked with AI-generated code enough to know it’s a mixed bag. When it’s good, it’s genuinely impressive. When it’s poor, experience makes that obvious and makes it possible to steer it in the right direction, explain why something doesn’t work, and adjust it to fit the purpose. You can’t rely on AI without understanding the code it produces. If you don’t understand it, you can’t fix it.
Experience shows up in knowing what adds value to a business and what doesn’t. It’s understanding when a plugin is appropriate, when custom code is necessary, and how today’s decisions will affect a site months or years down the line. AI can assist with many parts of that process, but it isn’t responsible for the outcome.
If something breaks, introduces a security issue, or fails to meet requirements, that responsibility still sits with the person building the site. Experience isn’t about rejecting new tools it’s about using them properly, understanding their limits, and delivering work that holds up over time.