My own reviews have shifted now. I tend not to examine detailed semantics anymore. The AI is as good or better than me at assessing whether a chunk of code does what the author said it was supposed to do.
Instead my job is to spot design and architecture smells, broader semantic errors, violations of unspoken business requirements, etc.
For example, I was recently reviewing code that built out a transactional flow. Part of that flow involved recording the transaction somewhere user visible and I knew that should only happen after the transaction was confirmed. AI implemented it where the transaction was posted.
That starts as an issue of underspecified requirements but that always happens in the real world. Thus that's where I can provide the most valuable insight: assessing with that context, whether business, operational, historical, or forward looking.
My own reviews have shifted now. I tend not to examine detailed semantics anymore. The AI is as good or better than me at assessing whether a chunk of code does what the author said it was supposed to do.
Instead my job is to spot design and architecture smells, broader semantic errors, violations of unspoken business requirements, etc.
For example, I was recently reviewing code that built out a transactional flow. Part of that flow involved recording the transaction somewhere user visible and I knew that should only happen after the transaction was confirmed. AI implemented it where the transaction was posted.
That starts as an issue of underspecified requirements but that always happens in the real world. Thus that's where I can provide the most valuable insight: assessing with that context, whether business, operational, historical, or forward looking.