Give an AI coding agent a prompt, and it might generate a frontend, connect an API, create database models, write authentication logic, and even add tests.
A few years ago, building all of that could take days. Now, you can get a first version in minutes.
Would you trust the code it generated with real users, real money, and real production data?
Because there's a big difference between code that works in a demo and software that's ready for production.
And I think that's one of the most important things developers need to understand about AI-assisted development. Working Code Doesn't Always Mean Correct Code
Imagine you're building a simple application where users can manage their personal projects.
You ask an AI coding agent to create an API endpoint that returns a project by its ID.
If the application doesn't verify ownership or access permissions, a user might be able to access data they shouldn't see.
The code works exactly as written. The problem is that it doesn't enforce the application's security requirements.
This example assumes authentication middleware has already verified the user and populated req.user. A real application also needs appropriate validation, error handling, and database-specific considerations.
The lesson is that a successful response doesn't prove that an endpoint is secure or correct.
Someone still needs to understand what the code should protect. AI Can Pass Tests and Still Miss Important Problems
You test it with these scenarios: A customer makes a successful payment. An invalid payment is rejected. The payment amount appears correctly. The confirmation message is displayed.
What happens if the payment provider confirms a payment but your database update fails?
For example, payment systems often need idempotency: processing the same payment operation or webhook more than once should not accidentally charge a customer twice or duplicate an order.
They also need server-side price validation and reliable reconciliation with the payment provider.
An AI agent can help implement these safeguards. But developers must verify that the safeguards exist and behave correctly.
Passing tests means the tested scenarios passed. It doesn't mean every important scenario has been covered. The Most Dangerous Bugs Aren't Always Obvious