In the previous article, I argued that AI isn't simply changing the tools we use to develop software, but shifting our work to a new level of abstraction. In this one, I want to address the problem that immediately follows: if we're going to write less and less code directly and agents are going to produce an increasingly larger part of it, how the hell do we know whether what they code is actually right?
Because the answer obviously can't be “trust the AI, it's very smart”.
Even though I personally develop code with AI today with practically no review, I don't blindly trust AI. Just as I don't blindly trust an engineer on my team. I don't even blindly trust myself.
Blind trust is a security hole. And not blindly trusting someone doesn't mean distrusting them, it means having mechanisms to prevent their mistakes, or mine, from causing problems.
That's why we've spent decades building mechanisms and methodologies around software development to detect, and avoid as much as possible, our mistakes. XP. Scrum. Tests. Code reviews. Pair Programming. CI. Static analysis. Permissions. Observability. Environments. Containers. Auditing...
