We need to talk about LLM generated code. For some reason, the standard advice in our industry has shifted toward “just ask ChatGPT” for quick fixes, and frankly, it’s killing site stability. I’ve spent the last 14 years wrestling with WordPress internals, and I’ve seen enough “slot machine” development lately to realize we are heading toward a massive technical debt crisis.
The Slot Machine Effect
When you prompt an LLM for a WooCommerce snippet, you’re pulling a lever. Sometimes you hit the jackpot—a perfectly working function that saves you two hours. However, more often than not, you get something that looks right but is fundamentally broken under the hood. It’s nondeterministic by nature. You might get a clean solution today and a hallucinated mess of non-existent WordPress hooks tomorrow.
I recently saw a “fix” for a checkout issue where the LLM generated code attempted to use a filter that hasn’t existed since the WP 4.x era. The site didn’t crash immediately, but the logic was a ghost. Consequently, the client lost three days of tracking data because the “quick fix” was never actually running. Specifically, we are seeing a trend where developers remember the “wins” but ignore the hours spent debugging silent failures.
Technical Debt in a Box
The problem isn’t just that the code might break; it’s that it often ignores WordPress Coding Standards. AI models are trained on massive datasets that include plenty of “bad” code—outdated StackOverflow answers, insecure “quick hacks,” and legacy snippets. When you inject that into a modern environment, you’re bypassing years of security evolution.
<?php
/**
* THE LLM APPROACH (NAIVE & INSECURE)
* This looks functional but misses critical WordPress security protocols.
*/
add_action('init', function() {
if (isset($_POST['update_option'])) {
update_option('my_custom_option', $_POST['value']); // Hallucinates security!
}
});
/**
* THE SENIOR APPROACH (ROBUST)
* Using proper sanitization, capability checks, and nonces.
*/
add_action('admin_post_bbioon_update_option', 'bbioon_safe_option_update');
function bbioon_safe_option_update() {
if (!current_user_can('manage_options')) {
wp_die('Unauthorized');
}
check_admin_referer('bbioon_option_action', 'bbioon_nonce');
if (isset($_POST['value'])) {
$sanitized_value = sanitize_text_field($_POST['value']);
update_option('bbioon_custom_option', $sanitized_value);
}
wp_redirect(admin_url('options-general.php?page=bbioon-settings&success=true'));
exit;
}
The Token Gambit
As highlighted in recent industry critiques, the business model of AI providers is shifting. We pay for tokens—units of work—whether the output is usable or a hallucinated disaster. In a production environment, this is a sustainability nightmare. Furthermore, the cost of “inference” is high. Providers like Anthropic and OpenAI are struggling to bridge the gap between per-token pricing and the actual quality of output.
If you rely on LLM generated code for your core business logic, you are effectively paying for a gamble. When the model returns a response that introduces a race condition or a transient bug, you still pay for those tokens. Then, you pay a senior developer like me five times the original “savings” to refactor the mess when the site starts bottlenecking under load.
Look, if this LLM generated code stuff is eating up your dev hours, let me handle it. I’ve been wrestling with WordPress since the 4.x days.
The Final Takeaway
AI is a tool, not a replacement for architectural oversight. Use it to scaffold ideas, but never “Ship It” without a line-by-line audit from someone who knows the difference between a Transient and a Global. The dopamine hit of a “working” snippet is temporary; the technical debt of bad LLM generated code is permanent.
