The "if it works, ship it" trap, and the one habit that actually prevents it
There's a specific moment that happens with almost every project: the agent produces code, it passes your tests, everything's green, and there's a real pull to just move on to the next thing. Totally understandable, the whole appeal of this workflow is speed.
But there's a gap between "this works" and "I understand why this works," and that gap is where the real risk hides. Not because the code is wrong, most of the time it isn't, but because the next time something breaks nearby, you're debugging code you never actually read closely the first time.
during the BC (before ChatGPT) era, this gap barely existed. You wrote it, so you understood it, mostly by necessity. Now understanding is a separate step you have to choose to take, not something that comes free with writing the code yourself.
One habit that closes that gap fast: before merging anything non-trivial, ask the agent to explain its own implementation back to you, line by line, in plain language. Not as a formality, actually read the explanation. Two things tend to happen. Either it confirms your understanding and takes thirty seconds, or it surfaces an assumption you didn't know was baked in, which is usually the more valuable outcome.
This becomes especially important with anything touching auth, state management, or async logic, the categories where "it worked in my test" and "it's actually correct" diverge the most.
Curious what habits others have built for this. Do you have a personal checklist before merging AI-generated code, or a specific type of change you never let through without reading line by line, regardless of how confident the tests looked?
Replies
I really agree with this. These days I spend a minute asking the AI to walk me through the logic before I merge anything important. It has caught a few things I would have missed.
@muniswamy_muniswamy I like this perspective. AI can write code quickly, but I still think understanding the implementation is part of my responsibility.
@muniswamy_muniswamy Another thing I find useful is asking the AI why it chose this solution instead of a different one. The comparison gives me a much clearer picture.
Hi Neeraj, this is a good reminder. Just because the test are passing doesn't mean I fully understand what's happening behind the scenes.
@uthappa_robb One habit I've picked up is asking what edge cases the AI considered while writing the code. That often points out situations I hadn't even thought about.
WebCurate.co
I agree with this.
For me, passing tests is just one checkpoint, not the finish line. I always try to understand the overall flow before merging, especially for authentication, payments, or anything security-related. Spending a few extra minutes there can save hours of debugging later.
The explanation comes from the same context that wrote the code, so it can only tell you what it meant to do. If the assumption was wrong when it wrote it, it is wrong in the explanation too, and it reads perfectly.
Same thing on my side with support replies. A draft grounded in the wrong order reads better than one that is right, because nothing in the text is off. Reading it more carefully does not catch it. Comparing it against the record does.
So the version I trust is when the explanation says something checkable. It claims this runs after the token refresh, then go and see that it does. Do you ever check the explanation against a run, or is reading it usually enough?