Is it safe to use AI-generated code in my projects?

Using AI-generated code is safe only if you treat it like code from a stranger on the internet — with healthy skepticism and thorough review. It's not inherently dangerous, but it's not inherently trustworthy either. AI coding assistants are pattern-matching machines. They've been trained on billions of lines of public code, some of it brilliant, some of it buggy, and some of it outright malicious. When you ask for a function, the AI gives you the most statistically likely next token, not the most secure one. I once asked an AI to write a simple Python script for handling user uploads. It worked perfectly. It also had a path traversal vulnerability that would let someone overwrite files outside the intended folder. The code looked clean. It ran without errors. And it was broken in a way that only a security review would catch. That's the trap. AI code often looks correct because it's well-formatted and follows common patterns. But security flaws are invisible in the syntax. The biggest risks include hardcoded API keys, outdated library calls with known vulnerabilities, and logic errors that expose data. Before you use any AI-generated code, you should understand every line of it. Run it in a sandbox first. Check for dependency issues. And never, ever paste code containing credentials or tokens into a public AI tool — those chats can be used for training. The tip here isn't to avoid AI code. It's to use it as a starting point, not the final draft. Let it do the typing. You do the thinking.